Google Analytics | The Complete Guide | 2020

How does it work?

How does it all work then? The bottom line is, is that Google Analytics is a web analytics tool that tracks the behavior of your website visitors as well as the performance of your website through a little piece of code installed on your web pages. But what it doesn’t do, is make sense of it! Google Analytics is not a mind-reader, so you’ll have to tweak the setup if you want to have accurate data showing up in your reports.

Remember that Google Analytics works by collecting data, and based on your admin settings (aka the configuration stage) it will process that data, (the data you’ve asked it to process in your admin settings) so that you can then you can go ahead and look at the data you were after in your reports.

So, our next step is for you to understand how you should structure your analytics accounts so that Google is collecting the right information about your website ecosystem. Getting this step correct is crucial, as it can have a massive impact on your overall data.

When we first learned about the concept of account structure in Google Analytics (GA) it kinda boggled our minds a little, so we came up with The House Model© to help work out what the right structure should be for your business - you can thank us later!

So, what do I mean by a ‘House Model’? When you log in to your admin settings you're going to get something that looks like this, (and just as a side note here if you can't see what I can see, then you don't have the correct access needed, we will cover the different types of user access when we do an admin deep dive). Either way, for now, we're just going to go over the concept of your account structure.

Now it doesn't look like much does it, three tidy columns? You might have even had a peek at this sometime or another, and it may be assumed that whoever set this up for you has got it all done correctly, but don’t be fooled, that is not always the case. We will get to that drama later, in our admin audit lessons!

So, let's start from the top. If you imagine that your website is a house, and this is a house that you're going to spend a lot of time making homely and cosy. You do this because you want to invite some visitors, otherwise known as customers, users, etc. These ‘customers’ are going to arrive to your house - your website, via different types of marketing that you are doing. So, when we're setting up our tracking, we're asking Google to track the people that are coming into our house. More on that later, for now - let’s dive into each part of our model.

Account Level aka “The Roof”

When we are talking about the Account level, I want you to think of this as the roof of your house. It’s a logical way for you to group all the data together, for all your different digital assets - such as your websites and apps, all under one roof. Anything you do at the Account level will affect the whole house, so be careful!

Let's say I punch a hole into my roof, that is going to impact my property, especially if it rains! Each account will be assigned an account number, for example UA-12345.

Property Level aka “The Floor”

Think of your property level as the floor to your house. Your floor can be your website, or app.

At the Property level, you will be given your tracking ID which is linked to the roof (your account) e.g. UA-12345-1 or UA-12345-2 depending on how many floors you have. You will add that tracking code to your website or app and Google Analytics will start to independently collect data to that floor. But remember, anything you do at the Property level affects your View (your windows). More on this in a moment.

It’s worth noting that you can have more than one property sitting under one roof. Think of companies and brands that have more than one business, but they all sit under one company account.

View Level aka “The Windows”

Think of your View level as the windows to a floor (Property). These windows give us a unique perspective of the data for a property. At the view level, you can determine the specific data you want to see for your property, aka floor. Think of it like this, you are looking through the window to see what your website or app visitors are doing on your floor.

By default, you get one window for your floor, which means you have one window to go and have a look at what your customers are doing, but Google actually recommends that you have three views per property. We broadly agree, and they are as follows:

Raw View aka Your Back Up

When you look through this window, you are going to see EVERYTHING! All the mess, spam, real traffic, everything. It’s like a back up of all your data or your website or app.

Test View aka Don’t Break Your Account

This is where you test your View settings. If you make a mistake, it’s okay! (It’s in your test view) It's like a sandbox, if you make a mistake it's fine, as it was your test view. This is the view where you check your settings and see how they work, then when you are happy you can roll them over to your third view - which is the one in which you’ll spend most of your life.

Reporting View aka Show Your Work

This is the View you use to base your decisions on. The settings have been tested, you now have super nice clean data to use to pull insights, build reports, and show your boss how amazing your work is going!

After your recommended three views, you can create additional windows that can be used to give you a different perspective on your data. This is not at all essential however.

So, to summarize, if I do anything to my roof, otherwise known as Account level, then it's going to impact the floor or floors beneath it, the Property level, if I do anything to the floor then it's going to impact any windows, the View level that are associated with that floor, and if I do anything to my windows (my reporting views) it will only impact that reporting view. If I clean a window on one side of your house it doesn't magically clean the rest of the windows, so the same principles apply here.

It's also important to note that once your data has been processed it cannot be reprocessed so any properties that you create and then fire that code to your website, you will only get that data the day that it starts to fire. Any reporting views (your windows) will only show data from the day that you create them. They are not retroactive - Google is not a time traveller.

In fact, the general rule of thumb here, anything you create in GA will only take action the day you create it.

Filters aka Drapes and Blinds

In addition to the settings at View level, you can also use filters. Think of filters as dressing your windows with drapes and blinds, which change how you see the data from your floor.

Filters can dramatically improve the quality of your reports because they allow you to modify the data that you can see within each view, so we think they're pretty cool. Don’t worry, we will dive into filters in the next lesson! Just so you know that they are there thought. For now.

Let's take a look at an example shall we? If I add a curtain and a set of blinds to a window and I try to look through that window to see what my customers are doing, when they're inside your house, those drapes and blinds are blocking you from seeing certain people. That you may or may not want to filter out. For example, you wouldn't want to see staff walking around your house - you don't want them counted as sessions and users, you only want to see the customers!

One of the most common mistakes that we see in Google Analytics is that people only have one default view setting, they either have no filters or the filters that they have are wrong, or the settings are incorrect. Things like time zones are common issues, you can set your views to report on data for a particular time zone over another. For instance, if I'm wanting to see what's going on with traffic in the United Kingdom, I don't want it to be set to a US time zone, because it's going to give me incorrect data about when people are visiting my website. It might be the case that we look extra busy at lunch (evening in the UK) and make poor decisions based on that information.

More dangerously, we often see problems where people just have the wrong house setup entirely! They have a bungalow when they should have a townhouse, or people that have townhouses that should really be massive skyscrapers or people with skyscrapers that should have the flat bungalow. So as you can see, account setup is crucial for you, your data and your business.

Let’s walk through the different types of houses you can expect to see when it comes to Google Analytics and your account structure.

Let’s take a look a basic site shall we? If we’re looking at say for example: www.coloringindepartment.com If you have a website on 1 domain you would have:

1. An account

2. A property

3. 3 views

   1. So 1 roof UA 12345,

   2. 1 floor UA 12345-1

   3. and 3 windows (test, raw, reporting)

This is a typical account structure for most websites.

Now let’s look at a Company with Multiple Brands, here are some examples:

www.coloringindepartment.com

www.coloringincon.com

www.coloringinapp.com

If you have a company and you own several businesses that all have their own unique domains, visitors to one website are tracked separately to another. UA-12345-1 UA-12345-2 UA-12345-3

When you are a company that has several businesses that all have their own unique domains, you want to make sure that one website is tracked totally separate to the other. Why? Because they are independent of each other you might end up having a house that looks a little bit more like a skyscraper, which is cool!

You still have your account number UA-12345 at the top, and then property numbers for each independent website. Obviously, it goes without saying that each of these floors will have at least 3 views: raw, test, and the reporting view.

Slightly different from our last example, let’s take a look at a Multi Domain Website. Here are a few typical URL examples:

www.coloringindepartment.com

Shop.coloringindepartment.com

Account.coloringindepartment.com

If you have a company and you have several domains for the same user journey, for example you have the generic website, your shop.com and customer account websites then you need to use cross domain tracking. So, instead of having several floors where you wouldn’t see the customer journey or be able to create goals etc, you use the tracking code for 1 property across all websites. That way Google Analytics is thinking that all domains are the same, from a tracking perspective. UA-12345-1 ON ALL DOMAINS.

Knowing this is a total lifesaver for companies that have several domains or subdomains but they are used across the same ecosystem. I think the confusion is that Google says that you should independently track your domains and subdomains. The problem is, in doing that on my current floor right now, I can't see what people are doing on the floor above or below me.

If you treat them all as independent floors or properties it means that I cannot see the customer journey, I'm not able to create goals, or any insights into how well my marketing and business is doing, which is obviously a bad thing!

So when you do want to see the full customer journey across different domains, (from a customer perspective it's the same business) you need to implement cross domain tracking.

I'm now going to log in to a Google Analytics account so you can check over the settings and see what your account properties and views look like, again this is just to make sure that you have the correct account structure for your particular business.

Firstly, navigate to Admin, and then look at the three columns we mentioned earlier, Account, Property, and View.

Secondly, here’s where you will see your Account number.

Admin>Account Settings

Here is where you will find your Property settings and how many are linked to the Account

Admin >Tracking Info> Tracking Code

Here is where you will find your View ID

Admin > View Settings

If you delete a property or view, they used to be lost forever, now you have a Trash Can where you can recover your data, but you only have 35 days before it is deleted, gone forever, and you will be wiping tears from your keyboard if you didn't mean to delete the data.

This is how you delete a view, and this is where it lives until it gets deleted. It is simple to restore.

Admin > View Settings > Move to Trash

Admin > Trash Can> Restore

Make a note as to what your account numbers are, and how many Views you have on your account. That’s all you have to do for now.

We strongly encourage you to complete the relevant template at the end of this Module, so you can follow more closely in the next one!

Work through the steps from the last module, looking at your Admin settings, write down the Account UA number, the name and Property ID, and any View(s) and their View IDs using our Admin Audit template.

Reflect on your current House setup, do you need more views? Do you need to set up Cross Domain Tracking? Is there anything that needs deleting?

At this stage, you don’t need to run off and start to manually edit your Admin, rather think strategically about the setup as our next few modules will deep dive further into your setup.

If you’ve done this, then you can come with us, into the next module on your journey!

These are of course optional - but they add a different take, even more depth, or just a fascinating look at how the other half live

Take this quiz to check that you've understood the Module!

We touched on filters when talking about The House Model © in module two, where we showed you how to correctly structure your Google Analytics account. Filters provide a way for you to change and modify the data that you can see in each view, which is pretty cool if you ask me.

If you remember the ‘how Google Analytics works’ bit from Module 1, filters work in the configuration stage. You are basically saying, “hey Google, collect data on this website for me, but I have edited the configurations so that when you process my data and I look at my reports, I see what I want to see”.

And again, ladies and gentlemen, remember that we are talking about a computer program here (there’s no empathy!). That little bit of javascript that you put onto your website means we have to follow a few rules, or the computer will just say no to you! Unhelpful.

In theory, all you are asking Google to do is collect data and then depending on the set of rules that you define, it will change the data you see in your reports.

Let’s look at some examples, shall we? When you create a filter in Google Analytics you have the option to:

• Include data, for example, only include traffic from the USA

• Exclude data, for example, do not include traffic from the static IP address for your company

• Modify the data, for example, you could make all the page URI data lowercase

• Rewrite the data, for example, you could change a form ID that is not that user-friendly to read like hs_form_18 to ‘contact form’

Like a lot of things in Google Analytics, unfortunately filters are not retroactive, so if you added a filter today, it will only be applied to the data from today, you cannot go back in time and recollect, configure and process the data.

Creating filters also permanently changes the data that you see in your reports. So if you make a mistake, we can guarantee that your data will flatline, you will be sad, and someone may shout at you (okay maybe not shout at you!). But it’s why you always, I repeat always, try out your fancy filters in your Test View. That way you can see how the data is working, and if it is going okay before you push live.

Please note these things, and don’t worry, we will go over these points in more detail in this module:

• Filters take about 24 hours to work on your account, so when you apply them to your test view, you should ideally check in a day later. I would like to have at least 7 day’s worth of data to look over and check before I call it either way. You may need more time to check how they are working, depending on what your normal traffic looks like.

• One filter input is the output of the next filter, so your filter order can make a big difference to your data.

• Filters are assigned to your View, but if you edit a filter at View level, it will impact any other View that has that filter added to it. This is because filters sit in a big bulk at the Account Level, and thinking about our House Model © anything you do to your roof is going to impact the floor and all windows associated with it.

• Google Analytics is case sensitive, so even if you think “I don’t think I need any filters” that is probably not true, if you have, say, a few URLs that are a mix of lower case and upper case, they will show up in your reports as different pages, and therefore you have fragmented your data, not ideal.

As you can see, there is always a use case for filters, the trick is to think strategically about what you need, in what order, and how to create them. Filters can be super powerful, can clean up your reports and help solve data discrepancies and endless fragmented data.

On that happy note, let’s walk through some common use cases of filters.

Common examples for filters in Google Analytics are removing things like staff. If you have a static IP address and lots of staff all firing up your website every day, they will show up as users and sessions, which is going to mess up your data, big time! Google Analytics will calculate your conversion rates based on sessions to the website, if those sessions are your staff, you may be diluting your conversion rates.

Another example is to create filters to zoom in on users and sessions from a particular country. We use that here at The Coloring in Department, we have a view to show all of our data, and then we have views to show traffic just from the UK, just for the USA and just for Australia etc.

Now you know how we keep saying filters are really powerful? Well, this is because they can clean up your data and ensure you get the data that you really want to see, instead of sitting down at the computer and scratching your head trying to work out why the numbers are not adding up.

Over the years, we at The Coloring in Department, are lucky to have gotten our hands on so many Google Analytics accounts! From all the people we have taught, and all the analytics accounts we have seen, and the many, many, audits we have done, whenever there has been a question around data discrepancies, or why the data is all fragmented, the answer, most of the time, is due to the Admin setup (more on that delight later) and Filters. Common culprits.

Aside from removing staff and looking at a country, it can be hard to know what kinds of filters to apply. Where do you start? Well, the examples we are about to share with you come from the many audits we have done, where something has not been quite right, and we worked out how to fix it! To save you the hassle of figuring it all out yourself, we have a whole list of filters that you can add to your account right away!

A great place to start is by grouping a set of filters together that have common themes so that you can see the right people, the right content, and improve the reporting readability.

With this in mind, let’s jump in to the typical filters you would want as a baseline foundation, and why you need them.

See the right people

I can not stress this enough, you want to see the right people in your data, you do not want to dilute those conversion rates and over-inflate your user and session counts.

Filter: Exclude Staff

Purpose:

You don’t want staff showing up as visitors, because they are not your visitors! This filter works really well for big companies where you know the static IP address or range of IP addresses.

If you are a smaller business or work from home and your IP address changes then you would struggle to get this filter to work for you, that being said, you really only want to definitely use this filter when you are a larger business and the staff visits are messing with your overall metrics.

Filter: Exclude Dev Sites and Staging Areas

Purpose:

When you are working in your development or staging environments, sometimes, if you forget to put a filter in place to exclude this traffic, you can head into trouble - as you think you have visitors looking at product pages, or completing a checkout, but the money doesn't end up in your pocket.

By all means, set up a View for Development and Staging sites so you can see how it works and if the tracking is correct, just make sure you set up a filter to not include traffic from your development environments.

Filter: Exclude Agencies

Purpose:

Just like our previous example, if you have agencies that are working on your marketing channels and your website, you may want to look into excluding traffic from them so visits to your website are not counted as customers.

Filter: Only See a Particular Country/City

Purpose: If your business is working in different markets, you may want to create a view and add a filter to just see users from particular countries or cities. This is particularly handy as your view settings have the option to select a currency and timezone. So, you could have a filter for a view just for the USA and have the time-zone and currency to match. Easier to watch the dollars roll in.

Filter: Include Hostname (Your Domain(s))

Purpose:

Google Analytics has a weak spot where you can push data into a GA account, like session data, even when someone has not visited your site, GA can still register visits and gather data. To stop this from happening you can add a filter which is telling GA to only collect data from your domains (hostnames).

You are saying to Google, please only collect data from people that are on www.mywebsite.com, this stops traffic coming in from other websites or naughty people who may be using your tracking code. If you have cross-domain tracking in place, then you can add all the domains and subdomains into one hostname filter.

Filter: Exclude Fake or Spam Sites

Purpose:

It is possible that some nasty spammer will try and fake visits to your website, and you get fake traffic from what you think is a valid website, you see them listed in your Referral reports, but, unfortunately it is all fake. Why do people do this? Many reasons, mostly malicious. So, make sure you remove these fake visits from your traffic.

See the right website content

Once you have the right users and sessions being counted correctly in GA, you move on to getting the right type of content into your account. We are mostly talking here about getting your Behaviour reports (aka what do people do when they are on your website) tidy, so these filters can help you view your website content in a cleaner light.

Filter: Show Full Hostname

Purpose:

If you have cross-domain tracking setup across a few domains/subdomains, this filter is an absolute MUST. Let's say you are using cross-domain traffic across shop.website.com, website.com, and account.website.com. In your Behaviour > All Pages report, GA will show the URI (which is the bit after your domain).

This means that for this example, all three sites homepage will show up as / and all the pages will be /pagename etc. Adding this filter would show the FULL URL so you can see correctly what traffic is from shop.website.com etc

Filter: Include subdomain

Purpose:

Following on from the show full hostname, you would have a view with a filter to show the full URL, and you can then have views with a filter to just show traffic from shop.website.com or account.website.com.

Filter: Include Directory

Purpose:

You can then build filters to just show traffic from a directory. For example, you have a blog and you just want to see what is going on there, you could add a filter to just show traffic from the blog.

You could also do this if you have a site that is using multiple languages eg website.com/fr/ for French pages, website.com/es/ for Spanish pages, etc You can build a view with the settings set to that country, and then a filter to show traffic from the directories/blog that match the country.

Improve reporting readability

This final example here, on filters, that you should have in your filter playbook is based on making the reports easier to read, and making sure you don’t fragment your data. Which is surprisingly easy to do.

Filter: Append a Trailing Slash

Purpose:

Once upon a time, if you didn't type or hadn’t clicked on a link that was exactly correct, it would say “page not found.” I’m talking about how you can type or link to website.com/blog/ and if someone used website.com/blog you still get to the same page.

Problem is, Google Analytics is case sensitive and will record the URL as a hit within a users session. So, you end up with content reports and you have fragmented your data. Having a filter to add a trailing slash across all your URLs means you have a tidy All Pages report and you don’t accidentally undervalue pages on your website.

Filter: Remove Query Parameters From URL

Purpose:

Sticking with the same theme as the previous filter, GA will record the URL from a session. If you have query parameters in your URLs which can be populated by people using, say the Search feature on your site (e.g. website.com/?q=analytics) or maybe you are selling something on your site and the order ID gets dynamically added to the final page (e.g. website.com/product/cart/order=id17201) you will soon get a very long report when you look at your All Pages report.

We will talk about setting up E-commerce tracking and site search later, but for the purpose of knowing what people are doing when they are the website, you don’t want to have multiple URLs with query parameters. Adding a filter to remove query parameters and order ID data will consolidate your pages and you get a cleaner report.

Filter: Lower Case/Uppercase URL/Campaign data/Search Terms

Purpose:

Again, Google Analytics is case sensitive, you could fragment your data (again) by having multiple pages that are a mix of lower and uppercase e.g. website.com/GoogleAnlayticsCourse or website.com/Googleanalyticscourse could take you to the same website, but GA would record them as two unique pages.

Now, you can go around everyone in the company and stress the importance of sticking to a standard site-wide hierarchy and URL structure, but hey, we are human, and people forget, but you can add a filter to catch all and just strip them all to lowercase so they get counted as one page and not two pages.

The same applies for things like site search, you may get users that type a mix of upper and lower case, so you can dig around in that haystack for possible combinations, or add a filter to pull all site search queries into lowercase so you can consolidate, ditto for campaign data, you may have people that forget how to tag your campaign e.g. campaign=May2018 and campaign=may2018. More on that particular issue in the tracking module, later.

Filter: Rewrite Dimensions

Purpose:

The final one for this theme is readability. Sometimes, the way our websites are built can make our job hard. Let’s say you have a contact form that comes into your website data as ‘ht_form_9785672-contact’ and maybe you have more than one of these... well wouldn't it be nice to have a filter that would change this to something like “Sales Contact Form”, yeah, you guys have guessed it, there is a filter that can tidy that up for you!

Now that we have given you some food for thought with our filter themes, let's dive into the next lesson about how this actually works in GA.

Just when you thought you had filters all figured out, Google Analytics will want to know what type of filter to add. There are two types of filter options in Google Analytics; Pre-defined (by Google) and Custom (by your good self).

First, let’s take a look at pre-defined filters. These types of filters were created so you do less work when it comes to actually creating a filter. They are small, but are still very powerful when it comes to improving the quality of your data.

In pre-defined filters, you have the option to ask Google Analytics to include or exclude, a source or a destination, that can be identified in some way. Let’s take a look at an example.

You would use this option to remove your static IP address for your company, which was our first example earlier.

• Select filter type > Exclude

• Select source or destination > Traffic from the IP address

• Select expression> That is equal to

• Text box> IP address eg 123.23.456.677

Now, to the second of the filter types - Custom Filters. They allow you to move beyond including or excluding an ISP domain, IP address, subdirectory or hostname. Custom filters are a little more challenging because you have more control over your data, and more flexibility and range in parameters. We actually used some as examples earlier too though.

They are primarily used when you want to include or exclude more than you can in a pre-defined filter, like:

• Exclude/Include: When you want to include or exclude traffic from a Country, Region or City

• Lower/Uppercase: Change all the site search terms to lowercase or uppercase to make them easy to read.

• Search and replace: To make a list of product IDs into a more user-friendly format, like productID12345 could be replaced with Google Analytics Course.

• Advanced: for when you are using cross-domain tracking and you want to see the full URL.

Regular Expression (or regex for short)

For a lot of the sweet magic to happen in custom filters, you need to add in some regular expression, or regex, for short.

This comes back to our point that we made earlier on, that GA is a computer program, and you need to talk to it in its own language in order for your filter rules to be applied. This “expression” is part of its language.

A standard definition of regex is “a sequence of symbols and characters expressing a string or pattern to be searched for within a longer piece of text.” Basically, you are asking Google to match this sequence in some way.

If you were to ask GA to use a filter to only show traffic from ‘New York or LA’ you are going to get a blank face from GA and zero data in your reports.

That’s because you need to use regex to translate your request, you need to be speaking its language. In this case, you need to use this | pipe symbol, which is regex for ‘or’. This means our filter rule would say ‘New York|LA’ then the computer will reward you with the data - based on New York -or- LA.

The first time I looked at regex I was very nervous, but don’t be. You can, of course, learn how to use it, or if you don’t feel confident, or can’t be bothered, you can copy and paste the regex in your own filter, test view first though! Don’t crash the car.

If you are feeling a little nervous, we have some further resources for you guys to help create common filters in our themes that we have previously talked about. They appear at the end of this module.

Let’s have a look at the Google Analytics admin section to see where to find your filters, at both account and view level, how to create them, test them, and change the filter order.

First up, click on your Admin Icon button.

Admin> Account>All Filters

At Account level, you will see ‘All Filters’ this is showing you everything you have, filter wise, across your account, given how your GA account is structured, this means it is showing you all the filters that are being used across any properties and views that are associated with this Account.

The interface will default to show you the first 10 rows of data, if you have more than 10 rows, you just need to click on ‘Show rows’ and select how many rows you would like to see using the dropdown. You can also use the > sign to tab through the data.

If you click on one of the filters in the ‘All Filters’ report at account level (they have blue text) you can see how the filter has been created and which view it has been assigned too. Bonus points.

Admin> View> Filters

At view level, if you move over to the third column and using the dropdown option, you can see which filters have been assigned to a particular view by clicking on ‘Filters’. Notice how the interface looks very similar to the account level ‘All Filters’ report.

However, this is just showing the filters on this view, and if you click on one of the filters you will notice that there is no option here to see where else the filter is applied, you can only do that in the account ‘All Filters’ report. You can edit the filter, and this is where you can make a mistake. Going back to a point we made at the start of this module, if you edit a filter at view level, it will impact any other view that that filter has been assigned.

Your view level ‘Filters’ report also shows you the ‘Rank’ for each of your filters, you will notice they all have a number assigned to them. This is the filter order for your view, and this is where on occasion we see that a company may have the right filters, but they were in the wrong order, so the data did not collect correctly.

We talked about this at the start of this module. One filters input is the output of the next filter, so your filter order can make a big difference to your data. Remember the coffee analogy.

To change the filter order, you need to click on ‘Assign Filter Order’ and click on the move up or move down buttons, when you are happy with the order you click ‘Save’.

We recommend you do an audit of what you have on your account and view levels, and reflect if the filters you have are correct, if you are missing any, or if they are in the wrong order, we will cover that in the next lesson.

Shall we go through an example of creating some filters? Yeah, let’s do that.

Creating a pre-defined filter ; Hostname filter

Using one of our previous use cases, if you wanted to safeguard your content so that Google Analytics only records users and sessions that actually visited your site, as opposed to recording traffic from ghost referral spam or people hitting your account with fake data, you can create this filter.

Side note, we get asked this all the time, why do people do this?!. Good question, but in truth, some people are just naughty and have nothing better to do with their time!

• Step 1: Click on Admin> All Filters

• Step 2: Click on + Add Filter

• Step 3: You need to type a useful name to your filter, enter this in the Filter Name text box

• Step 4: Now click on the Select Predefined option

• Step 5: Select from the dropdown options

  • Select Filter Type = Include Only

  • Select Source or destination = Traffic to the hostname

  • Select Expression = that are equal to

  • Hostname = website\.com If you have more than one domain you would add some more regex like the | eg website\.com|shop.website\.com

• Step 6: Add to a Test View

Step 7: Verify a filter

If you want to verify the filter you can click on ‘Verify this filter’ to see how this filter would affect the current view's data, based on traffic from the previous 7 days.You can only do this when you look at the filter at the view level. So head over to your Test view and click on the filter you just created.

You can then click on ‘Verify this filter’. We would still recommend that you leave the filter for a few days to check in on how it affects your data, and for some verifications, it just won’t give you an answer when you do a verify check. For example, if you wanted to verify a lowercase filter, and data was in the account, it would work, anything that is based on geolocations will not work.

Step 8: Filter Order

This is this last step here, but it could mean the end to your efforts if you get this wrong. In the Test view click on ‘ Filters’ and then click on ‘Assign Filter Order’ you can then move the filter up or down depending on the order you want.

When all is working fine and dandy, you can move the filter to your chosen reporting view, but remember to check the filter order!

To move a filter to a reporting view, select ’All Filters’ at Account level, click on the filter you want to move over, then between the two boxes where we see ‘Apply Filter to Views’ you select Add>>, and if you wanted to take it off you select << Remove.

Creating a custom filter ; Append trailing slash to URI.

Again, using one of our previous use cases, if you wanted to make your reports more readable and avoid fragmenting your data with duplicate pages, if you (like us) have a URL structure where there is a trailing slash at the end of it...but, people link to us, or marketing campaigns can be sent out where people forget to add on the /.

You still get to the website page, but you have now in your reports, for 1 page, showing as 2 different URLs, (I am doing the whole facepalm emoji right now), this filter will tidy that up for me.

• Step 1: Click on Admin> All Filters

• Step 2: Click on +Add Filter

• Step 3: You need to add a useful name to your filter, enter this in Filter Name

• Step 4: Now click on the Select Custom option

• Step 5: Click Advanced

Now, this is where we need to use regex, which is where some people get a little nervous, take one look and just run! But trust me on this, please do not be afraid. And remember you do all of this in a test environment anyway, so you really can’t get it that wrong!

• • Select Field A -> Extract A

    • Request URI = ^(/[a-zA-Z0-9/_\-]*[^/])$

  • Select Output To -> Constructor

    • Request URI = $A1/

  • Step 6: Add to a Test View

  • Step 7: Change the filter order in the Test view

  • Step 8: Assign to Reporting view when happy, and check filter order again.

Now that you have an understanding of the use cases for filters, how you can use predefined and custom filters to get your nice clean data, and very importantly how to test those filters and make sure that you assign the correct filter order.

The next step, and our recommendation to you, is to audit your current Google Analytics setup and just list the filters that you have at Account level followed by the filters that you have at your view levels.

Thinking about our themes as a start; when you need filters to check you are collecting data from the right people, and that data is across the correct websites, and then finally the data is being processed in a much more readable way.

You’ll still want to be investigating if the filters have been tested, if you feel like they have been configured correctly and if you are missing any additional filters.

This step is going to form part of your wider Admin Audit, which we will cover in later modules, but knowing that you have the power to improve the quality of your reports, think about any questions that you have had about your data quality, what is missing from your account?

Luckily for you, we have a checklist that you can download which gives you some typical filters that you may need for your setup, these are all the filters we talked about as use cases in this module.

However, I am not a mind reader (my, that would be a talent!) so there are going to be some filters that you will need to identify and assign yourself. The way that we do this is through a simple process.

Always remembering that filters change the data permanently, from the day that you create them and there's no going back when you have actually created them, you need to think strategically.

You can use the Admin Audit Template that we have provided, and by the way, this is how I have mapped out filters for all of the Google Analytics audits that I've done over my career. I think about the type of filter that I need, starting with giving the filter a name, and then I write out the purpose for creating that filter, as you work through this process, you can make notes about additional information or support you may need to complete it.

Things like e.g. if I know I need to create a filter to exclude staging environments, I will make a note to go and speak to people within the company to double check and validate the addresses of all of the staging websites.

The trick here, if you can't validate the purpose for the filter, then it shouldn't be on your list, and occasionally the answer that I'm looking for will not come from adding a filter. It could be something much simpler, like adding a segment to a report. Naturally we will deal with that in the segments module.

Once you have your final list of filters, and you have confirmed the purpose of the filter, I would type out for each of the views what my final filter list should look like and I use this to base my filter order upon.

You may think that this is tedious, and maybe some of you think that it's not necessary, but I've had more than one occasion where there are multiple reporting views and because nobody physically wrote out the filters that were assigned to that view, mistakes happened, big time.

One example that comes to mind is where a reporting view was created for the staging area and they had a filter to only include traffic from staging environment, but nobody set up a filter to exclude the staging environment on the other reporting filters - wrong data happened. When they are mapped out, listed, and recorded as part of your measurement plan, it stops balls from being dropped.

Now, some of you are now thinking - what is a measurement plan? And how do we do that Admin Audit? Well coming up in the next few modules we are going to focus on just that!

These are the templates that feature in this Module, they are two of many, many templates - and they outline the overall filter creation process for you in a short and sweet way. Don't try to do it all at once, follow the process!

Using our template to review, log into your Google Analytics account and head over to Admin> Account> All Filters and list the filters you currently have on your account, and which views they have been applied to.

From this audit, review each view to check the filter order for each in turn.

Do you have any other filters that you should consider? Check against our common filter checklist, and complete the filter planning document where you will outline your filter name, the purpose for the filter, and any notes about that filter, such as do you need additional information in order to implement your findings.

These are of course optional - but they add a different take, even more depth, or just a fascinating look at how the other half live

Take this quiz to check that you've understood the Module!

We've mentioned the term “admin audit” and also the idea of a measurement plan in previous modules, but what exactly is it, and why do you need one?

Well, the idea behind a Google Analytics audit is for you to identify what your current setup looks like, never assuming that the settings are correct and that somebody, somewhere, has gone off and changed your configuration so that you have a perfect setup.

In truth, we have yet to see a perfect setup and just as rare, any formal documentation on how a website’s Google Analytics setup has been carried out.

So, as a result, you end up with departments and businesses using Google Analytics data to justify their strategies and tactics, however, nobody really knows if the data is correct or who was responsible for creating it. Hardly ideal foundations to build trust in the data. Even less, the decisions made based on it.

Which, we think is weird, think about it, if you have a new content management system (CMS) for your website you will likely get training and documentation on how it all works and how it has been built. Same goes if you were using a new email service provider, hello documentation and training!

But, because there is no real formal training in Google Analytics most people are self-taught, and maybe don't know about the concept of having a measurement plan.

The bottom line is, you need to know what your current setup looks like, the ultimate goal here, is to have valid clean data that you will use to drive growth for your business.

You need to have the right data to do this, and tailor your analytics account to match your business and marketing needs.

Once you have an idea regarding the health of your analytics account, you can start to write out a measurement plan.

A measurement plan is the formal documentation that’s going to outline the details of your technical setup, whilst always keeping the business and marketing objectives in mind, because that's why you're using Google Analytics in the first place.

So, if your boss wants to know how many people are watching the videos she has paid for, you need to set up the account in a way that can record that information, otherwise, you can’t report on it. Sad times.

So, this document is a list of all your suggestions, with the justification of why you need to make changes to your account. It will also have a detailed action plan of who does what, and when, as well as occasionally, why.

Especially as there are likely going to be some resources and some budget needed to get the configuration to where you need it to be. Clearly, it becomes a lot easier to get said resources if you have a solid business case for it.

So, instead of just tweaking your account here and there, emailing IT or development for help, or trying to talk to your boss about why you may need budget and resources to complete a task in GA, have a measurement plan outlining what you need to do for your job - and why it should matter to him or her.

Your formal measurement plan should be reviewed and updated every 6 to 12 months or whenever you feel it would most likely need to be reviewed. Your business requirements and technical setup will naturally change over time, your site is not static and is ever growing, so are your marketing strategy and tactics.

You need to adapt and review your analytics plan to check if anything needs to be updated or changed so that the data you get is always correct and you're not missing anything. We would also recommend that you keep the measurement plan and audit in a centralized folder for people in the business to refer back to.

You may also find as you work through this course, that there may be a lot of things that you need to update or change, and you might end up with quite a long list of tasks - which can feel overwhelming. But, having a measurement plan in place will help you evaluate and prioritize the tasks, which makes it more manageable. Fabulous.

Remember though, this is a process, please allow yourself time to get Google Analytics set up correctly. How long does it take you say? How long is a piece of string!? I have seen companies sprint through an all singing and dancing setup but the company was going for funding and needed solid numbers, so the motivation was there.

On the other side of the spectrum, I have seen companies just plod away at their list of tasks in a specific order and they completed it within a year. So, each to their own.

The marketing department needs to have this skill set under its belt, this ability to correctly collect, segment, interrogate, visualize, and interpret data in a way that supports the work that we are doing so that we can be better at our jobs.

So, instead of just tweaking your account here and there, emailing IT or development for help, or trying to talk you your boss about why you may need budget and resources to complete a task in GA, you would know what your current setup is and use this to build your measurement plan.

Every single analytics audit that we have done, and every measurement plan that we have written, have all been different, they have used the same template, but the recommendations and changes are unique to each business, and each website, because you're all kinda unique in that way.

So positive vibes, here, outwork the competition, and work smarter. Own the process, own the audit, own the plan, and kick some data ass!

Now that we are all on board with the idea that you need to audit, and then formally document the changes that you need to take action on, to get the data that you want, (Yay!), we can move on.

As mentioned in the previous lesson, you will develop a list, and that list may be very long. So how do you know which task to do first?

Your completed admin audit will help guide you when working through the individual sections of the measurement plan template. For each section, you are going to write out where you are now and any issues that you've identified with that current setup. You're going to make the case for where you need to be and therefore what you need to do to get there.

And, because you want to provide a business case to highlight and justify the need for this change in your setup, you’ll have to bring it back to the benefits for the company if these issues are addressed.

The measurement plan has the following sections for you to complete, all of which we will deep dive with individual modules, so this is a birds eye view style rundown, just to give you some context.

1.0 Admin Audit: this is where you’re going to flag any issues that you found with your admin set up across the account, property and view level.

2.0 Account Setup: based on your admin audit and how your website ecosystem is built, how is your house looking? Do you need to create additional properties and views, do you need to set up cross domain tracking?

3.0 Event Tracking: if you want to track things like people watching videos or people clicking on telephone numbers, or downloading PDFs, or submitting contact forms, you need event tracking to be set up. So, you need to see if you're using event tracking and then provide suggestions on changes to existing events or suggest new ones.

4.0 Goals: you can have 20 goals per view, so how many goals have you currently got within your current admin setup, and are they correct? What are you missing? Do you need to create funnels?

5.0 Acquisition and Campaign Tracking: is your current marketing activity being attributed correctly, are marketing channels being correctly tracked? Is the data being fractured?

6.0 Custom Dimensions, Metrics and Data Import: this is in more advanced analytics territory, but can you identify if you're currently using these advanced features?

7.0 Creating Reports and Dashboards: when you have sorted out points 1 through 6, how are you going to analyze the data? How are you going to segment this data? What dashboards do you need to create and for whom?

As you work through each section you’ll start to notice that for some tasks to be completed there will be a dependency on a previous issue, that needs to be addressed beforehand.

If you want to create reports on the users going to your website, and what pages they are looking at, but you noticed you are not using filters at all. Well, you can only create the report once you have fixed your filters. So, I would flag that task as urgent in this case.

Something that can help you prioritize the tasks at hand is to use a traffic light system. It's nice and simple but it works really well. You would use this to identify all of the key issues that you find from your audit, that are present in your measurement plan, and you will grade them in terms of what are Red, Amber, and Green. Also known as RAG reporting.

Red tasks, these will be the urgent-and-must-happen-now jobs, then moving through to Amber for the jobs that are important but not as urgent as the red ones, or for the jobs that can only move forward once the Red tasks have been completed, and then you are left with the Green tasks, which are important, but not urgent.

Who has access to the account?

It is always worth looking at who has access to your Account. Lurking in here could be past employees, past consultants, agencies, your ex husband - whomever. It’s also worth checking in to see the level of access they have as well, whilst you are at it.

There’s a section in our admin audit template for you to review who has access, and then agree if any users need to be removed (like people who don’t work for you anymore, agencies you used to work with etc). Do any users need to have their access edited? For example, if someone on your team is going to do an admin audit, then they will need to be promoted to the correct access level, especially if they are on the lowest setting.

With that in mind, here’s a recap on the permission levels so you know what to ask for, and which permissions to give.

Manage Users: You need to decide if you want people to have permission to add or delete others, or amend other users' access levels.

It may seem obvious, but you need to have more than one person in the company with Manage User access, we have seen far too many examples where we have been told that a company could not add any more users as there was only one person who had access and they don’t work for the company anymore!

Edit: Perform administrative and report related functions and see report data.

For example: Add, edit, or delete accounts, properties or views, filters, goals etc.

In addition to Collaborate, Read and Analyze data.

Collaborate: Individuals with this level of access can create personal assets and share them.

For example: Edit a dashboard or annotation, in addition to Read and Analyze.

Read and Analyze: Access the account and see reports and configuration data. They can manipulate data within the reports.

For example: Filter a table, create a segment, create a personal asset eg a private dashboard. They will not be allowed to collaborate on shared assets.

We are now going to head into the admin area of Google Analytics to see how you can view who has access to your account, and how to give access or edit access to your Google Analytics account.

Remember that if you can't see what I can see on the screen, it is possible that you don’t have edit user access and thus need to ask for it, to complete this task.

Click on the Admin icon.

Across each of the Account, Property and View columns, you will notice that there is an option called ‘User Management”.

The reason why it appears across all three columns is that you can actually decide who gets access to your entire Google Analytics account or select access for certain properties or views.

For example, let's say you have a basic website set up where you have one Account and one Property, but you have several views which are geographically specific. Now, let's say you have someone new on the team in the USA, and you would like them to access the reporting view that shows only traffic from the American market.

You can decide if you only want them to have access data for that American reporting view, and only that American reporting view, or if you're happy for them to see data across all views that are available.

The same situation applies for different properties, you might have a company that has several different unique businesses, that all live under one brand. If you have a new team member looking after one brand and its website, you can opt to only allow them to see the data for that property, or you can give them access to all brand websites under that account.

You can see now, why having a process, and auditing who has access to your account is so important. Thankfully all of the settings across Account, Properties and View - within ‘User Management’ are the same, you just need to work out what you want people to see, so you may want to have your admin audit open in the background with the details you need.

Adding a user:

I'm going to add a user to our analytics account and I'm going to let them see everything, so I'm going to add them to the Account level. I don't want them to add any other users, but I'm giving them responsibility to make changes to the admin setup and do an audit, so I'm going to give them edit access.

Select ‘User Management.’

You will then get a list of all of the users and their current permission levels.

Click on the ‘plus icon,’ which will give us the option to add a user or group.

Click add user.

And then enter the email address, which will need to be a Google email address, either Gmail, or a Google Business email address.

You have the option to tick ‘notify new users by email,’ which I always tick, because it automatically sends that person an email to say that they have been granted access, so that’s one less job for me!

Then you just need to tick the permission boxes, which will default to ‘Read and Analyze,’ the lowest access setting, and because I want to, hypothetically, for this person to do more than just read reports, I'm going to tick the box for edit and collaborate, leaving the manage users as unchecked.

Edit Permission:

If you want to edit somebody's permissions then you follow the same pattern, you can click on the ‘User management’ at Account, or View level.

Find the person's email address and name, and then navigate to the right and click on the right-hand side, where you see the three dots, you have the option to view the user's account details or remove access - should you wish.

To edit, you click on the pencil icon and then you'll be prompted with the option to select or deselect that person's permission options.

If I want to fully remove someone, I will just click remove access, and this will prompt you with a reminder to say you are removing this person from the account, you'll have the option to either cancel or confirm by clicking on the ‘Remove’. Bye bye - user.

We’re now going to create a Property in Google Analytics, and we will need edit permission in order to complete this task.

You're going to find with this demo that creating Properties and Views is not that difficult, the hard part is identifying what your account structure needs to be - which we talked about using our House Model©, earlier in the course.

When you have identified strategically why you need a particular Property and View, go for it, go create it!

Sign in to your Google Analytics account.

Click on the Admin icon.

Now, navigate over to the property column and select ‘create new property’ from the menu. You can have 50 properties per account - by the way. Probably don’t create them all right now.

You then have the option to create a Property for a website or mobile app.

We’re going to demo creating a website based Property, so we are going to select ‘website’ and then nice and simple, just add the name of the property. Note here, be specific and descriptive, ideally matching the name of the Property as identified from your measurement plan

Then add the website URL. Don’t get this wrong.

Select an industry category, which are quite broad, so just select the one that you can identify with best.

Select the reporting time zone, this is going to be used for the day boundaries in your reports, regardless of where the data originates.

You can always edit and change the time zones of your Views, and we will show you that when we go into our admin deep dive.

Once you’ve gone through all of these steps you just select ‘Get tracking ID’ and Google will give you the tracking code that you will use to collect data. High Five!

Creating a View:

Creating a View has a similar pattern thankfully, you have the option to add up to 25 Views per Property and again you are going to need ‘Edit’ permission, to create a new view.

If you haven't already done so click on the Admin icon and navigate to the Account and Property that you want to add a new View.

In your view column click ‘Create new view’.

You will then be prompted to select if this new view is for a website or app, and as our Property is for a website, we select ‘website’.

Now, we can give our View a nice specific name, so it's really easy for people with access to our Account to understand where the data that this particular reporting View is from.

You then want to select the reporting time zone, so let's say we're going to create this view for the United Kingdom, I would set the time zone to Greenwich Mean Time. (GMT)

And then click ‘Create view’.

Well done, now you know how to create a Property and View. Woohoo!

Next time, let's go into a deep dive of the Admin for Account, Properties, and Views!

Work through the steps from the last module, looking particularly at the Admin tab, as it's our focus for now.

Reflect on your current set up, do you need to change or amend anything based on your new found knowledge.

If you’ve done this, then you can come with us, into the next module on your journey!

Take this quiz to check that you've understood the Module!

We’re now going to do a bit of a walkthrough of the Account Settings, covering what’s in the box, so to speak, and highlight key areas that you may want to check when you audit your own account settings.

We recommend that you do this for your own account, and use our Admin Audit template to check what your current setup looks like and make notes on things you may wish to change. Remember you will need Edit permissions to make any changes to your Account settings.

Starting with our Admin Icon, click on this and you will see the three columns that represent our account structure. We are going to focus on the Account Settings - the leftmost column.

Firstly, click on Account Settings:

You will see your Account ID and the Name that you have given to your account, which you can edit if you wish, by changing the copy in the text box.

You are then presented with Data Sharing Settings, which allows you to control which data is shared with Google Analytics (GA).

We agree with GA’s recommendations to tick all the options provided.

Products & Services: Google products & services will help improve the data you get and to help authenticate data that is associated with a Google user account. This also helps Google tackle issues like spam detection (remember this from our filter module), some people have nothing better to do than send rubbish data to your website!

Opting into the products and services also helps things like the Enhanced Demographics and Interest reporting. This is a report in the Audience (who goes to your website) which we will cover in our reporting walkthrough, but for context, it gives you data on the types of sites your users are visiting which can be used to help refine your Google Ad strategies. Which we will cover in detail, in that course.

Benchmarking: you need to tick this box if you want to get access to the Audience> Benchmarking reports that cover channels, locations, and devices. If you throw your anonymous data into the pot, you get access to this report that helps you see how other websites (that have identified with a particular industry vertical) are doing in terms of average sessions and marketing channels e.g. Organic Search, Social, etc.

The additional two tick boxes; Technical Support and Account Specialists we always tick. Normally, you worry that someone from the Google sales department is going to give you a call, but Google isn't really like that! The reason why we tick these boxes is that we want to know if they have new features and just in case I had an issue, I’d want tech support to see the data and be able to help.

Lastly, you have the option to agree to Google’s Data Processing Amendment. This is an agreement between you and Google on how they will process and safeguard your data. It’s particularly essential for those Europeans in the audience. If you choose to accept this, and plan to protect your users data to some degree - you should click on the Manage DPA button. You’ll be asked for your legal name (the company, not you), a primary email to dispatch the required documents, the details of your data protection officer, and a representative for those users not in the EEA. Obviously, you may need to speak to your compliance team here.

Next, we have User Management, which we’ve already covered in a previous module. This is where you can see who has access to the account and what level of access they have, we can use this to edit permissions or add new people (provided you have manage user access).

Then we have the Filters end of things, which we also covered in a previous module. This is where you will see all of the filters that are on your account and which views they have been assigned to. Head back to that module if you need to recap on this.

Change History is a useful report when you are trying to work out who did something significant to your Account. Google Analytics will log the date and time, the name of a change, and who did it. By significant here, we mean something that will impact the reports, which includes things like adding Filters, creating Views, creating a Goal, editing a Channel Grouping - they will all be logged. If you’re just logging in and looking at the data, that won’t show up in this report.

Lastly, we have the good old Trash Can. If you deleted a Property or View, which used to be very easy to do, there was no getting it back, thankfully this feature was brought in so you can get your data back from the rubbish heap.

Let’s see how this works. I’m going to move over to a Test View and delete it by clicking on View Settings, then, in the top right - there is an option to ‘Move to trash can’ - which I’ll now select.

This will keep the View (for now) - but notice how there is a strikethrough in the View name. If we move back over to Trash Can, you’ll see the View we just sent to be trashed. If you wanted to restore it, you have 35 days to do so, before it’s deleted forever.

People with Edit access will also get an email alert to say ‘this view is being sent to trash’ so you can catch it, if it was indeed a mistake. Try not to give anyone a heart attack, on that point.

There are no additional Resources in this short section - you should be working on your account audit documentation from the earlier sections, at this point!

Take this quiz to check that you've understood the Module!

We are going to stay in the Admin settings, and as usual, click on the Admin icon and you will see your 3 columns for Account, Property, and Views. As previously mentioned, you will need to have Edit permission to edit anything in your Property Settings.

Depending on how many properties you have, you can use the dropdown to select the property you want to look at.

Clicking into your Property Settings, you will have a number of options to audit and review.

Let’s start with your Basic Settings. You will see your Tracking ID and the name that you have given your property, which you can edit by typing in the text box.

You also have a default URL, and you need to use the dropdown and select HTTPS:// and then type in your website domain, which should be the domain that serves as your homepage, to give you an idea, for us at The Coloring in Department, our domain is https://thecoloringindepartment.com so this is what we’ve typed into our Property settings as our default URL.

There is also a dropdown ‘Default View’ for you to select, this is the function where your integrated Google Products will push data into you Google Analytics account by default. So, if you are using say, Google Ads and you have three views, Test, Raw and Reporting (as advised), you would select your ‘Reporting’ as the default view. We will cover product linking in the next lesson.

Then you have an Industry Category which is quite a broad list, so just select the category that best fits your business.

Next up, is an Advanced Setting which is a tick box option to ‘Allow manual tagging (UTM values) to override auto-tagging (GCLID values) for Google Ads and Search Ads 360 integration’.

Simply put, if you are using the Google Ads product there would have been a setting in your Google Ad setup to auto-tag. Which you should do, because it means that any campaigns you have in Google Ads that are going to a URL on your website will automatically have the correct tagging on to make sure it goes into the Paid Search bucket when you start to look at your Acquisition reports in GA. We have a whole module on tracking and we will loop back to this point again. It’s an important one.

For now, in your admin audit, make a note if this box is ticked or not, and investigate if you are using Google Ads. Auto-tagging in Google Ads gives you extra data like the hour of the day, and keyword positions that you wouldn't get with manually tagging your campaigns, so you need to use the auto-tagging option.

An example where you would tick this box to override the auto-tagging with manual tagging is where you have Google Ads, Google Analytics and another 3rd party tool, like HubSpot, or Mixpanel - and you would need to have a hybrid solution.

This hybrid solution would use auto-tagging in Google Ads, so you still retain the extra data that comes with that option, but you tick the box to allow manual UTM tagging, which means if you have campaigns where you have put in your own manual UTM tag, Google Analytics will allow the manual tag to override the data in the auto-tag.

Next is your Property Hit Volume.

This shows how many hits your property had in the last day, 7 days, and 30 days. Why should you care about this? Well, in the free version of Google Analytics you are allowed 10 million hits a month per account. So if you have more than one Property per Account, you need to manually add these up. Annoyingly, there isn't a total per Account option, only a count at Property level.

Just to remind you of what a hit in Google Analytics is - which we covered at the start of the course. I am talking about things like a page view, or when an event fires for someone watching a video.

If you edge close to the magic 10 million, you will probably get someone from Google 360 reaching out, because for more data, you will need to pay for it, or leave your Account to go over the 10 million hits a month and get sampled and slow processed data, also known as a little bit inaccurate.

Although, when you get to THAT size of website traffic, you would need to have a serious look at your analytics plan and upgrade your tools anyway. Common sense we think.

In-Page Analytics, personally this is a little out of date now, you used to turn this toggle on, make a change to your tracking code, and you were rewarded with some cool reports in Behaviour> In-Page Analytics.

But, this report has now gone, and there is a chrome plugin where you get to see a little bubble containing internal link clicks as a %. But, that chrome plugin is no longer being supported, so, we turn the toggle on, because what’s the harm. That said, we expect this report to slowly die off soon, from what we can gather.

Search Console, we will cover in the next lesson about the joys of linking google products together, but if you have linked your Search Console account to your website Property, this is where you can click to push that data inside different views that you have associated with that Property.

And lastly, but important just the same, User Analysis, Enable User Metric in Reporting. Ok, we really think this should be a default, and you shouldn't have to click on this toggle. If you think back though, back to our basic Google Analytics model, you have users (people), these users have sessions (timeframes), and sessions fire hits (interactions). In ALL of your standard reports in GA, it will show session data, you tick this box and you will also get USER data too, all lined up nicely in your tables. Winning!

We will now go over the Tracking Information within your Property Settings. There is quite a lot of power in these settings, so let's break them down, one by one.

Tracking Info> Tracking Code

Here you will find the Tracking ID (which you can also see in your Property Settings). You also get the script (code) here, that you need to add into the <HEAD> of every webpage you wish to track.

If you are opting to use Google Tag Manager you can get support by clicking on the blue link ‘Learn how to get started with Google Tag Manager.’ More of which we will cover in the Google Tag Manager Course.

Tracking Info> Data Collection and Tracking Info> Reporting Features

This toggle is great if you are using Google Ads and you want to collect data from your website visitors in order run Remarketing campaigns. Remarketing is when, let’s say for example, you go to a website, view a dress, you don’t end up buying the dress but you end up seeing that dress on other websites as an ad.

That’s Remarketing in action. Oh, and you can also use Remarketing for Search, so the PPC ads in Google Search Results. Of course, more on this when we talk about Paid Search in another course.

For now, you need to turn this toggle on. But, by doing this you are agreeing to the policy requirements, which means you will -not- pass any personally identifiable information through Google (which you should never do anyway).

You need to update your privacy policy, that will notify users to your website that you use Google Analytics (again you should have this in place already) you are just going to update the policy to cover the advertising features with Google. If you were planning on using them.

Same goes with the Advertising Reporting Features toggle, this is a collection of features that take advantage of the Google advertising cookies so you can do things like:

1. Creating Remarketing Audiences based on specific behavior, demographic, and interest data, and share those lists with Google Ads

2. Use demographic and interest data in your Analytics reports, which you might remember from an earlier module in this course

3. Create Segments based on demographic and interest data

All of this extra data gives you more insights about your users, so you can understand them better, and improve your paid marketing strategies.

Now, you don’t have to be using Google Ads in order to take advantage of building a remarketing list. When you do want to hit GO on this paid media strategy, by creating a list ahead of time, there are people in a pot waiting to get your lovely marketing message, based on their previous interest.

Bonus for this - is that you also get the data in your Audience> Interest reports without ever launching a Paid Search Ad with Google. However, you absolutely need to make sure that you let visitors know that you use cookies to collect data, making clear which data you collect, why you collect it, and what they can do to opt out of it.

So, audit the features that you have turned on in this section and investigate if it is in fact turned on, that you have the correct information in your privacy policy. Everybody wins.

Tracking Info> Data Retention

This feature may not look like it could remove data from your account but that's exactly what this setting does. Or rather, I should rephrase, did.

It's a little bit confusing, so let me break it down for you. Just before the deadline date for GDPR which was May 25th, 2018 - this feature popped up. Everyone who was on a standard, free, Google Analytics account was automatically set to a default user and event data retention setting of 26 months. Unless you went in and manually changed it before May 25th 2018. Seems handy for sure.

However, if you actually read the copy here, within the User and Event Data Retention statement, it says that you can “change the retention period for data that is associated with cookies user identifiers or advertising identifiers these controls do not affect most standard reporting which is based on aggregated data”.

I'm going to place an emphasis on the words “most standard reporting”.

In reality, what this is saying, is for data that sits outside of the standard reports, that data will not be retained by Google Analytics. It’s going to be deleted and gone forever.

So, what sits outside the ‘most standard reporting’ and ‘aggregated data’?

Personally, it was the stuff that made Google super cool, even more so than now, things like user data, Event Data, Segments, Filters, any Custom reports that you had created. If you didn't change your settings before May 2018 then some data may be missing from your account. Which is super important to know. Especially when you are doing historical analysis, because now, some data is just not going to be there anymore. I’d be inclined to take a look.

Let me show you an example here.This website in this case had the date range set from the default 25th of May 2018, so, when I go into the acquisition reporting, because let's say my boss has asked me how many users are coming to the website through Organic Search over the last few years. If I stay within the user and event date range, you can see the nice blue lines for user data, all cool.

Until I move the date range to July 2016, as you can see with our example the data flatlines.

Same company, for another use case, looking at their Event data reports. Just so you know, we're going to talk about Events in future modules. For now though, this data was telling me how many people were logging into their account, how many people submitted a form and how many people downloaded a PDF. Again, within the date ranges of May 2018 to August 2016 the data is all there.

When I move to the months of July 2016 in this case, and try and go back any further, all of that user and event data is gone. Vanished.

So, you need to log this in your admin audit, see what your settings are, and be mindful when you are dealing with those time comparisons on how well your website is working.

Because you may find that when you are looking at that historical data, that you might just be plain missing information, and instead of scratching your head wondering what could have been the cause, you can investigate if it is down to this setting. It just might be.

For those of you that have a new website or you don't have that much data past the default 26 months, you need to decide what you want your date range to be. Making sure that your audience know, within your documentation.

Tracking Info> User ID

Think of social media sites where you can be on a desktop, mobile and tablet device at the same time - but because you are logged in, you have that seamless integration between devices. If you have a website ecosystem that has the ability for a user to be logged in you can set up this User ID feature, but it does require some development work. It isn’t always necessary though - depending on your business.

Every user and session from any device will be assigned a random Client ID from Google Analytics in the first instance, and what this User ID feature does is essentially replace the Client ID from Google Analytics with the User ID that your system has created for that user.

You'll end up with a User ID view specifically and the benefits of this are the ability to track a user across devices, provided they are logged in.

An example could be for a software as a service company that requires users to be logged in to their website to access the product, another example could be for a community website where you need to be logged in to see all of the content, vote and comment on particular articles and content.

Use your Admin Audit template here, and if you have an ecosystem where your customers can log in to your website to access something and you're not using the User ID feature, then you can seriously consider adding this to your measurement plan in the form of a recommendation to use it.

The set-up from your Property settings is quite simple, you turn on the toggles to accept the User ID policy and then you're going to need to add some extra code to your website in order for this to work.

Tracking Info> Session Settings

The next piece of the puzzle, is one you’ll definitely want to look at. By default settings for your sessions (timeframes) are set to 30 minutes. So thinking back to our Google Analytics model where you have a user, a session and hits again. If you have a visitor to your website and they have a look around, then stop, but they leave the browser tab open - which, let’s be honest, we all do.

Thankfully, this session won’t go on forever, because Google Analytics will cut it off after 30 minutes, as that is the time allocated in your Session Settings.

You can edit this and change the session timeout but you need to really think about the use case for changing the session settings, because you may accidentally inflate your session data or devalue your session data as a result. 30 minutes is the most commonly used timeout here though.

I’ll give you an example, where a company increased the session settings from 30 minutes to 60 minutes. This company was in the business-to-business space (B2B) and the entire objective of the website was to generate leads for the sales department. One of the ways that they did this was through the use of webinars and video content.

They had visitors that would come to the website, sit and watch a webinar or video that lasted about 45 minutes, and then they started to click around on the website and completed the lead gen form.

Due to the session timeout, within that 60 minute of activity, they were being counted as two sessions when in fact it was one session. They ended up with quite low conversion rates because Google Analytics is calculating conversions based on the number of sessions. Not great.

Most businesses and websites will be more than fine with the default 30 minutes but you should have a think about the way that users interact with your website, the tasks they're trying to complete, and make a decision whether or not you might increase or decrease from the default 30 minutes.

There is also another option to change the campaign time out, we will cover this again in our module focused on tracking your acquisition, all that lovely marketing you're doing, driving traffic to the website.

Fun fact: Google Analytics will look back through its data, as far as your tracking info campaign timeout settings - but will otherwise default to a campaign time out of six months.

So again you need to think about your business and how long it takes people to complete goals on your website from the 1st ever visit they make.

Again, another example from a lead generation website - where the time from a 1st visit to completing the lead gen form - “yes somebody, please call me” - was about 9 months.

Now in your acquisition reports the computer program that is Google Analytics would only look back as far as 6 months, and then give credit to the channels that brought that customer to the company, but only as far back as this. This means some of the earlier stages of marketing awareness activities would not get any credit that they needed, and deserved. So for this example, the company changed its campaign time out to 12 months. Job done.

Again, we will go into this in much more detail in the tracking module, for now, use the Admin Audit to log what your current timeout is and in the note section have a think about your business, your website, and if you need to change the campaign timeout settings - which can go up to a maximum of 24 months.

Tracking Info > Organic Search Sources

Google Analytics has a list of default search engines (https://support.google.com/analytics/answer/2795821?hl=en&utm_id=ad#searchEngine) so if you get any traffic from search engines that are featured on this list, then the visitors will show up as Organic traffic.

If you have traffic from search engines that sit outside of this list, the traffic will show up as Referral traffic. Referral traffic is Google Analytics channel grouping for websites that send you traffic - any websites.

If you find yourself getting traffic from a search engine that is not on the default list, and you want the traffic to show up as Organic, and not Referral, then you can use this feature to add a search engine - even if they are obscure.

Tracking Info> Referral Exclusion List

You want to check to see if your domain has been listed here, and if you have cross-domain tracking set up, you absolutely -must- have all the domains and subdomains included in this list.

“Exclude these domains from your referral traffic. Users arriving at your site via any of these domains will not be counted as referral traffic in your reports.”

It may not be fully clear from the note here, from Google, as to what this feature actually does though! In simpler terms (than Googles) - any domains that you have listed in this setting will not show up in your acquisition reports as referral traffic. We just mentioned referral traffic in the ‘Organic Search Sources’.

Referral traffic is defined as a website sending you traffic, so you don't want to pat yourself on the back for driving traffic to your site from your site, the official wording for this is self-referrals.

Let me explain with a few examples.

• Cross Domain Tracking

Let's start with the example of when a customer arrives on Website.com, and they check out the products on shop.website.com and then to go on to buy the products on account.website.com. When you head to your acquisition reports to see which marketing channel brought in the sale, it will say shop.website.com.

Which is not what you wanted to see - at all. You want to see the traffic sources that brought and drove the sale, before they visited any of your domains or subdomains.

By adding all the domains and subdomains that are included in your cross-domain traffic, you avoid this issue. So for your company, if you are using cross-domain (or you are going to use it) you’ll want to check this setting and ensure that all the domains, that you are in control of, are correctly listed.

1. Session Timeout & Tab Hoarders!

If you have a customer that visits your website and they, for example, look at your products, they read a review and then, just when things were getting exciting - leave their tab open with your website still running, as they get on with their day.

Thanks to the session timeout which is set at 30 minutes by default, the time on page will not go on forever, because Google Analytics will cut it off after 30 minutes.

However, if you have customers that have that tab open, and they return to that page after the session timeout of 30 minutes, start to poke around your website again and Google Analytics fires up, well, it will start a new session. The source of that new session will be, you guessed it, you! Unhelpful.

1. Stroke of Midnight

The issue of self-referral can also happen at the stroke of midnight. If you have a visitor on your website that arrives at 11:59 pm and they click through to another page at 12:00 am, this interaction triggers a new session and the source of the session becomes, you!

This is also another reason to get your house in order and make sure your view settings are set to the right timezones. Now, for this example, you can’t do much about the new session firing after midnight, but at least you would hold onto the source of traffic that the visitor came from, and if you add your domain to the referral exclusion list - you are as good as you are going to get.

1. Missing GA Code On Pages

The last example dear friends, is when you have pages on your website that for some reason are not firing the Google Analytics tracking code correctly.

If you have webpages with no tracking code implemented, any visits to those pages will show up as self-referrals. Adding your domain to the referral exclusion list will stop your own site showing up as referral traffic, however, it won’t tell you which pages are not firing the code. You would have to investigate that yourself, using a tool like Screaming Frog. Which we will talk about more on the SEO course.

Tracking Info > Search Term Exclusion List

Once upon a time, Google Analytics used to provide all the keywords from Organic visits, man that was a great time to be alive! Now, when you head over to your Acquisition reports, you still get the number of users and session. In the keywords report however, you are most likely going to get a good 90% of the traffic with the keyword = (not set) result, which is a bit disappointing for those of us that remember the days when we got all the keyword data.

This setting is for those of you who want to count some of your Organic Search traffic as Direct Traffic by telling Google, for example, to put anyone who arrives from search who typed in “your brand name’ into the Direct channel, and not the Organic channel, because they were looking for you specifically. Now we personally wouldn’t do this, but if you did want to do it, this is the part of Google that would allow you to complete said task.

Big surprise here dear student. Google loves, and we mean LOVES a Google party! It likes nothing more than putting together all the Google products in the same place so they can talk to each other and have a good time.

So, no surprise that there is a massive chunk element of product linking, which is so important, they wrote the name of this setting in all capital letters. PRODUCT LINKING.

So, if you’re using Google Ads, Adsense, Ad Exchange, BigQuery, Display & Video 360…you get the point - any of the Google Products listed, you can stitch them together with Google Analytics.

Why? Better data, so you can make better decisions across the board.

Let’s take Google Ads as an example, you can, of course, go into the Google Ads platform and look at all the data on your campaigns and see what’s working. But, if you stitch Google Ads and Google Analytics together, you will get to see the full picture, as in what do people do, beyond the click. So, you do not see the creative elements in Google Analytics however, they aren’t pulled from Ads.

That notwithstanding, wouldn't you want to know what your Google Ads traffic actually did on your website? As in what content they looked at? What products did they check out? If they end up coming back to your site again, possibly from another marketing channel?

Yeah, sure you would!

So, this is where you do it. You need to have edit access in your Google Analytics account AND have access to the other Google Products to link them together.

Obviously, you can’t link up non-GA products, like Bing PPC data, because it’s Google's party and they choose to keep it exclusive to Google. You can -track- Bing Ads, but this is another thing entirely.

Postbacks

The Postbacks configuration is for those of you who are using Google Analytics to specifically track Mobile App data. You would need to confirm that your iOS and/or Android tracking has been configured for your app. There’s more information from Google support in the transcript of this module. If you wanted to dig in more.

https://support.google.com/analytics/answer/6254369?hl=en#related-resources

What’s the benefit for configuring Postbacks? Well, when you are doing marketing campaigns across different advertising networks to either get people to install your app, or do you have a deep-link based approach?

By deep-links, we are talking about sending traffic to a specific location in your app, and the deep-link will allow users to see the content within the app, even if the app has not been installed. It gives a much better user experience for the end user - much faster.

The Postback feature will allow Analytics to track an ad network when it detects an app install or deep-link conversion from that network. So, it will help you to optimize the advertising you have across these other ad platforms and provide a feedback loop that benefits the entire mobile ads ecosystem.

For your Measurement Plan, you would need to make a note here to check if you need to enable Postbacks, investigating firstly, if your iOS and or Android campaign tracking has been configured correctly, and then letting Google Analytics know what you want to count as a conversion, as well as which mobile ad networks you are using for your marketing campaigns.

Audience Definitions

Audience Definitions is where any remarketing lists that you have created in Google Analytics would live. We’ve talked about remarketing before, this is where you can show a display advert across the Google Ad Network, or show Paid Search ads in search engine result pages, via either Google Ads or the Google Marketing Platform.

The only people that would see either the display ad, or the Search ad, would be users that have already visited your website, so it’s a really effective way to encourage people to come back to your website. A reminder, as it were.

Now even if you’re not going to launch any remarketing campaigns right now, it’s always useful to create some remarketing lists in advance. Why? Well, when you do want to hit the GO button on this marketing tactic, you will already have some people ready and waiting in a remarketing bucket of data. Good times people!

However, if you didn't have any lists building up in the background and you decided to do some remarketing, let’s say you wanted to start today, well you wouldn't be able to. Sorry...

But why though? Because you wouldn't have any data ready and waiting, and as you don’t get charged by Google to create any remarketing lists, it’s a good use of your time to have some running in the background.

We will show you how to create these in our module on segments, but to give you some ideas, you could create a list of people who visited your website, went to a particular product page, added to the basket, but didn’t convert. You want them to convert.

Dynamic Attributes are for those of you who want to level up your remarketing game. You can enhance your remarketing campaigns with dynamically created content that can improve the context of your ads. For example, let's say you are doing some marketing for a hotel company and you build remarketing lists for people who visited the website but didn't book the hotel.

With the use of dynamic attributes, you could go further and show not just our hotel brand, but the specific hotel and room that they were looking at, as well as a specific offer just for those people - to woo them back to our website and make the booking. It does need some tweaks to your Google Analytics tracking, but it is worth it.

Custom Definitions and Data Import, we will dive into this in much more detail in our Advanced Analytics module. Just so you know.

Remember at the start of the course when we walked through common terms used in Google Analytics? GA reports are built on Metrics (e.g. numbers) and Dimensions (e.g. text that gives characteristics to the numbers).

What this special section of your Property settings does to your Google Analytics account, is allow you to create your own Custom Dimensions and Custom Metrics. It is like saying, you like the standard furniture in your lounge, but you want to bring in a custom piece of artwork into the room.

You can do the same with Google Analytics, you can create your own. This is by no means the place to start though, as I’m sure you already have spotted.

Data Import is just as it sounds, you can import data into Google Analytics, a good example here is importing cost data from sources outside of Google products, remember what we said about Google loving a Google Party. Well, if you were doing Bing Search ads, and you wanted to do a better analysis of the data, you could import the costs, clicks and impressions into your Google Analytics account.

This would allow you to do a fair comparison, apples to apples, when looking at your Google Ads and Bing Search ads. Again, more on this juicy part of Google Analytics in our Advanced Analytics module.

There are no additional Resources in this short section - you should be working on your account audit documentation from the earlier sections, at this point!

Take this quiz to check that you've understood the Module!

Hey analytics people!

Now, I’m going to tell you a little secret, out of all the Google Analytics audits we have done, making changes to the configuration settings at View level can have a tremendous impact on the quality of your data. Especially when you are taking advantage of moving beyond that single default view that you get when you originally set up GA. However, as you may have found yourself, just having the default setup won’t work for you, you need to make a significant number of changes to your Account.

Use our Admin Audit template and see what your current state of play is, which we imagine you are familiar with by now. Write down any changes you want to make, which would be tried out first in your Test View. Please note here, the Test View.

We’re going to take a look inside our View level settings now, and we start, by clicking on our Admin cog and moving over to the right hand side.

Now, remember what we have said about your analytics setup, anything you do at Account level impacts everything under that roof, so all the properties and Views that sit under that Account. Anything you do to your Property, will impact all the Views that are associated with that Property. And, if you change anything at a View level, it will only impact that View. This is a very important message, if I clean a window at the front of your house, the window at the back of the house doesn't get cleaned as a result. That kinda magic ain't real people!

You can’t assume that if you make changes to one of your reporting Views that it will magically work on the other Views, it won’t, you have to repeat the process for each View you have.

Let’s make a start then, and dive into what you get out of the box so to speak, what the settings mean, and what you should be looking for when doing your own View level audit.

Starting at our View Settings, you will see the Basic Settings element.

View ID

Each View you create is given its own View ID number, which is helpful to know, as you can change the name of the View in future. The ID however, will stay the same. So, when you are doing your GA audit, make a note of the View ID. If you have a lot of Views, or you are going to create a lot of Views, I always make a point to reference the View ID as well as the View name. That way you are always on the same page, so to speak, when you are reporting to teams, agencies, or your boss.

View Name

You then have your ‘View Name’. This is a text box so you can type in the name that you want to use.

In an earlier module there was a task for you to review your Google Analytics House Setup. If you have completed that task, use the agreed name that you have decided upon. If you haven’t - go and do it now.

Tip from us: make the name user-friendly, and descriptive. If you have a reporting View that’s been created so you can see everything that happens on your website, you could call it something like ‘Master Reporting View’. If you had a View to focus on data from a specific country you could call that View something like ‘UK Reporting View’ - to see only data from the United Kingdom.

And, again, as we just flagged, you can always be specific when reporting, that you have taken data from a particular View and reference the name and the View ID. This will save future confusion.

Website URL

This pulls in the URL from your Property settings, you can change it if you have a View that is going to look at a certain domain or subdomain - so that it’s reflective.

Time Zone - Country or Territory

When you look at your analytics reports, it’ll show you how many users, sessions and hits you had in a given day, week and month. The day these numbers land on is going to be determined by your View Settings.

Why is this important to get this right? Well, in addition to getting the correct number of users and sessions in a day, there are reports in analytics where you can drill down further using a dimension called ‘Hour of Day’. This does exactly what you might expect.

You can use this to see when you had a visit from a Google Ad campaign and use those insights to adjust your bidding for when you want your Paid Search ads to show up. Or, let's say you are selling something on your website, you can see the time of day that you sell more products and adjust your activities accordingly.

Our advice here is simple. If you have a specific geographic market then set the timezone to match. We have a reporting View for the UK, so we have set the timezone to the United Kingdom. However, our master reporting View, which we use to see everything, we have set this to match our Google Ads account, which is set to match the east coast of the United States.

Default page

The default page is another optional setting, and will most likely need to be left blank.

If you hover over the question mark symbol next to ‘Default page’ you will get this message.

“Enter the default page for your domain so that multiple URLs that point to the same page are treated as the same entry in your reports. For example, if example.com and example.com/index.html both open the same page, you can enter index.html in this field”

Now, if my mind reading capabilities are working, when I was reading out that copy that Google Analytics gives for the Default page setting, you were most likely thinking “What the fudge Jill? What does that even mean?”

Ok, stay with me on this one, as it bent my mind a little when I was originally getting my head around it.

What people sometimes do, is they read that statement and add /index.html or /default.aspx in the text box.

I have been there, done that, and made a mess of my data by doing this.

Let’s explain the ins and outs of this.

If you have a website homepage that has a URL that looks like this www.website.com/ but your homepage could also show up as www.website.com/index.html or www.website.com/default.aspx etc. depending on how your site is built - then you need to think about this function.

When you get a visitor to your homepage that arrives on a URL which is either, for example

• www.website.com/ or

• www.website.com/index.html

BUT the homepage stays the same, the visitors get the same experience of your homepage regardless of which homepage URL they arrived from.

If this is something that happens on your website, then your content reports, which are found in the Behaviour section of Google Analytics will definitely have fragmented data. That’s because your homepage has shown up twice, as if they were different pages, even though it’s the same page.

So what people do, which is wrong, is they add, say /index.html into the default settings.

However, this is where a twist in Google Analytics will frazzle your data. And it is down to the surprising fact that this Default page setting will apply whatever you have typed into the text box onto every URL that ends in a forward slash.

So if you have a page called www.website.com/blog/ where all your blog content sits, and that is the only single URL, it will now show up in your content reports as www.website.com/blog/index.html even though that page doesn't exist.

Normally, a website will redirect a homepage with www.website.com/index.html to a more user-friendly www.website.com/. If you find yourself with a website that does not do this, then you need to leave this box empty, my friend.

The fix for this is not in this Default page setting. The fix is in a Search and Replace Filter.

We talked about Search and Replace filters in Module 3, and for this example, you can create a Filter to tell Google Analytics to change any URL with /index.html and replace it with a forward slash /. Job done!

Exclude URL Query Parameters

This is another optional setting, and is only going to need investigating if you have a website with query parameters in your URLs.

Query parameters are where you have a URL for your website, but there are additional values that are assigned to that URL, things like terms, search query keywords, numbers etc.

We’ve mentioned a few times now that Google Analytics will record the exact URL during a visitors session on your website. What you need to work out is what kind of impact these parameters have on your reports. Do they fragment your data making it hard to analyse? Or are they useful in helping you understand how people are using your website?

Because this setting doesn’t exclude parameters in the way you may think, they do take parameters out, but they do this by stripping the URL down, consolidating the URLs into one.

Let's walk through an example for using the Exclude URL Query Parameters setting.

If you had a password reset on your website, for people like me who forget their login details, for instance. I enter my email address and get sent a link with a code to allow me to rest my password. Happy days.

The URL may look something like this:

www.website.com/resetpassword?code=12345

Now, let's imagine my sister forgets her password, and she goes through the same process and gets a new dynamic URL for her, which may look like this www.website.com/resetpassword?code=67889 because obviously, she’s a different user.

Annnnnnd repeat.

Every time someone forgets their password and requests to reset it so they can log in, they get a new URL.

Now, the page people are taken to reset their password is the same for everyone. In fact, it’s www.website.com/resetpassword - however, the query parameters for the resetting of passwords here would fracture my data.

So in this example, I would type into the Exclude URL Query Parameters the word ‘code’. My content reports would still count total page Views, but the rows (and rows) of data for each URL wouldn't be expanded to make analysis a nightmare! You’d have successfully cleaned up your reports, making your own life easier.

Now, for an example where you may be tempted to use this feature, but by doing so, would mess up your data. Scary.

Imagine a website that sells stationery, because who doesn't love getting new stationery. However, this website has tons of categories for its products. To help its visitors find what they are looking for they have a feature to select which products they want to look at. Also known as shopping.

Hypothetically, I landed on this website, and I want to look at pens, but this website sells ballpoint pens, gel pens, marker pens, and fountain pens.

I just want to see the fountain pens. So, I use their handy user-friendly search box, and tick the category ‘fountain pens’ which gives me a URL like this

www.website.com/pens/category?id=123

When I go back to my product page to look at paper, I get a URL like this - because you guessed it - different product.

www.website.com/pens/category?id=456

Now, if I were to add the term ‘category ID’ to my Exclude URL Query Parameters, based on the same logic as the password example earlier, I will be stripping out an element and losing data.

Because, unlike the password reset option, where I don't want to see duplicates in my content reports with dynamic URLs, I do want to analyze how many people are looking at this content.

In this example, the query parameter actually helps me understand what page and type of content my visitors are looking at. Admittedly, it’s not that user-friendly. Imagine having multiple products and category ID’s! Well, this is where you would use a filter to help improve the readability of your reports. You would use a Search and Replace filter so that each time the URL has ID=123 you could replace it with something more useful like Fountain Pens. Problem solved!

Sadly, there’s also another way that query parameters nudge into your URLs and fragment your content reports, and that is search queries from a website with a site search function.

Now, although the setting does not follow exactly under the Exclude URL Query Parameters We're just going to jump into this, as it’s in line with this theme. Data destruction.

Site Search Settings

If you have a website with a Site Search facility, and by this, we mean having a little search bar so that users can search on your website for things like products, contact numbers, blog posts etc. It’s basically like Google, but for your website.

Site Search setup in your analytics is a little gold mine, it tells you exactly what people are looking for. If you don’t have the information people are searching for on your website, write about it! Create a landing page or blog post. Or if you thought it was obvious to people where to find something but they are getting stuck, improve the user experience to help people get what they need faster. You can also use the search terms, and mis-spellings in your Paid Search campaigns.

There is a -however- here though.

When a user types a keyword into your search bar, it will produce a URL with results for your website. This URL will have a site search query parameter and the keywords the visitor typed in. The URL that could look something like this:

www.website.com/?s=keyword

Similar to our password reset example, every time a visitor uses your site search function, a URL is created for that session. That URL will include the search parameter plus the keyword the visitors' type added to it. This can result is many, many, many rows of data when you look at your All Pages report. Not great.

But, you don’t want to have to manually sort through this information in your content reports.

In order to get the Site Search data and make sure you keep your sanity when looking at your All Pages reports, you need to do the following:

Step 1: Turn the toggle for Site Search Tracking ON.

Step 2: You then need to tell Google Analytics what your query parameter is. You can find this by looking at the URL when you use your search facility. Or, check in with your website or development team if you are not sure. Typically, the parameters are either the letter s or q, and sometimes it’s simply the word ‘search’.

Let's imagine in our example the parameter is s. You would type the letter s into the text box.

Step 3: You then need to tick the little box with ‘strip query parameter out of URL’

There’s also the option to turn on Site Search Categories. This is only used if you have an option in your search function to allow users to refine searches by category. So if you have a Site Search category parameter in addition to the site search query parameter you turn the toggle on. You then need to let Google Analytics know what your category parameters are and decide if you want to exclude them from the URLs as well.

What do you get?

Turning this setting on gives you a whole report just for Search Terms. Head over to Behaviour> Site Search and you can drill down to Search Terms.

By ticking the box to strip out query parameters, your Behaviour> All Pages reports will be clean.

If you want, you can add a Filter to force all search terms that visitors type to lower case if that makes it easier to consolidate the data and read the data.

What you absolutely should not do, is put the query parameters into the Exclude URL Query Parameter function, if you do that you will lose all your search data. And, like all things in analytics, this feature will only start to collect and process data the day you set this up. Do this in your Test View first and then rinse and repeat on the reporting Views that you’d like to have Site Search data included in.

Currency Displayed As

This setting will default to US Dollar (USD $). You should change this to the currency you want in the reporting View used in your E-Commerce and Goal value reports. So if you have the UK reporting View, you could change the currency to British Pound, or if you had an Australian reporting View, amend to AUD $.

Bot Filtering

This will not be ticked by default. This setting can be useful in bringing your traffic numbers down. Why is that a good thing? Some visits may not be from actual people. It could be from bots and spiders (the little darlings that crawl the web). If you tick this box it will tell Google Analytics to remove any data generated by bots and spiders that have been compiled into a list managed by the IAB and ABC International Spiders and Bots List.

We covered User Management in detail within a previous module, but to recap, remember that you can assign access to your Google Analytics by Account level, Property level, and View level.

This means that if you have a team member, or group of people who only need to access a particular reporting View then you can assign that access by heading to View> User Management.

This can work well if you have a View for particular regions and you only want the people responsible for that particular region to see their data. Or, if you had a View that was set up to see a particular subfolder or subdomain.

What we would suggest you do, if you haven't done so already, use our Admin Audit Template to review who has access to your Google Analytics Account. Then make a decision as to which part of GA you want people to have access to, and at what level.

Worth a recap, remember that…

Manage users: You need to decide if you want people to have permission to add or delete others, or amend other users' access levels

Edit: Perform administratively and report related functions and see report data

Collaborate: Individuals with this level of access can create personal assets and share them

Read and analyze: Access Account and see reports and configuration data. They can manipulate data within the reports

Bottom line, all websites should have Google Analytics set up with Goals - but are often without. It’s been more than common for us at The Coloring in Department to see GA Accounts with either no Goals, Goals set up incorrectly, or just a few Goals set up.

You can have a whopping 20 Goals per View! Yes, 20! Which may seem like a lot, but trust us, there are so many that you could be using for your website.

Why should you be setting up Goals then?

Well at some point, you are going to have to look beyond visits and actually start to see how your marketing, content and campaigns are working in regards to making people convert. And by convert, we mean, doing the thing you need them to do so you are still in a business.

There is a whole module coming up that is dedicated to Goals, which will cover things like:

• What your business model is and what your business objectives are

• How you can identify what your Goals should be

• The types of Goals and how to create them

As well as lots of other exciting things.

For now, at this stage at least, you want to understand if you have any Goals set up and log them in your Admin Audit.

Click on your Admin cog, and select the Views you wish to audit and click on Goals.

There are four types of Goals you can have in Google Analytics, the more commonly used goal types are based on a destination, so you have to reach a particular URL, say - a thank you page, in order to complete the goal.

Event Goals follow the same rules as your Event Tracking, because Google uses the Event Tracking data to create and verify an Event goal. We have a whole module for you on Event Tracking too, so don’t worry if this sounds alien to you right now.

After Destination and Event Goals you have two more options, which to be honest are not as helpful.

Page/Screens per session, are for creating Goals around users that have a specific number of pageviews. Or Duration, which is for sessions that last a specific amount of time.

We think these last two options are not that helpful as Goals go. Why? Well, you can use them if you wanted to get data on page views and time on your website, but would I use these as definitive information to inform conversions to show the board of directors? Probably not.

So, in short, if you have any Goals they’ll be listed here in Account> View> Goals.

Make a note of how many Goals you have, if they are active, which you can check by looking at the toggle on the right-hand side, to see if it is turned on or off.

You also want to check if they are working or not. By working, we mean, have they had any conversions in the past 7 days? You can find this data in the row called ‘Past 7-day conversions’. This is essentially a snapshot.

Depending on your business though, you may only have one big conversion a month. In which case, dive into your Reporting interface and head to Conversions> Goals> Overview to be sure that the goal is working or not. Little bit of extra work

I always find it useful to log the Goal Name, Goal ID, Goal Type and then notes on the setup as part of my audit.

It’s not uncommon to find Goals that are created but are not working correctly. Or duplicate Goals, so having two Goals created but they are tracking the same thing.

Repeat this for every View you have on the Property and you will get a good idea of how well your Goals have been set up.

Let’s set the scene.

It is a sunny day, you are logged into Google Analytics and pumped full of excitement to see how well your content is doing. Especially for those of you who have tidied up your reports with some fancy filters, to clean up previously fragmented data. Go you!

You head over to Behaviour> Site Content> All Pages report and that smile on your face suddenly turns into a frown, you poor marketing soul. Because you notice on the bottom right that you have oodles of pages, indeed tons of pages, to work through.

All you wanted is to shuffle through the report and see what your top pages are, which is really easy to do. But, how can you work out how many blog pages are being viewed? Or product pages? Or if you have multiple brands, which are getting the lions share of page Views? Could you find this out without having to manually count, or worse, export and try some complex excel workaround?

Well, my lovely coloring in students, there is an option that will make your life a little easier, and make you smile a little more. Content Groupings!

What are they, you say?

Well, imagine all your website pages are printed pieces of paper and they are just strewn all around your office. Now, imagine if you could organize the pages into nice, neat and tidy filing cabinets?

Wouldn’t that be smashingly good?

Well, you can do this with Content Groupings, and you can have five of these per View.

Let me show you an example in action.

Here’s the Google Demo Account. If we navigate to Behaviour> Site Content> All Pages. Above the table where you can see the Dimensions and Metrics for Page, Pageviews, etc. Just at the top, you can see some blue text with ‘Content Grouping:’ and then ‘none’ with a dropdown icon. When you see ‘none,’ this just means that there is no content grouping currently assigned to this View to add to the report. If your Account has no Content Groupings created yet, then you won’t see anything in this report.

As the Google Demo Account has created them, we can see an example in action. If you click on ‘none’ you will get to see that there are three content groupings out of a possible five.

If you select one of them, let's look at Product Categories, you will see something like this:

It’s the filing cabinet equivalent for your content report. It makes it so much easier to see your content in groups, and you get to decide what goes in each of the groups.

It works at the View level, so you have to create these for every reporting View that you have, and it works by setting up rules, like anything else. As you can imagine, as its Google Analytics here, they work the day you create them.

What should you create?

Start by thinking about what it is you want to achieve. We always like to use one of our five to group a companies website structure. That way, you can look at the All Pages report and use the Content Grouping to see how many page views are going to your homepage, product pages, blog pages, campaign pages, contact pages, etc. After your website structure, you should think about other use cases.

The Google Demo Account has three content groupings, as we’ve just seen. One to look at brands (Google, Youtube, Android). One to focus on Product (Apparel, Bags, Electronics etc). The last one used to define clothing by Gender (Mens, Womens).

How do you create them?

You need to have Edit access in order to create Content Groupings. Head over to Account> View> Content Grouping and make a note if you have any Content Groupings for each of the Views assigned to your Property. You would, as always, create these in your Test View first, and they will only start to work from the day you create them. They won’t be applied to your historical data. There are three ways you can create them.

• Rule Set

• Content via Extraction

• Tracking Code

Let’s look at all three in turn.

Rule Set

The Rule Set option is the quickest and easiest of the three options to create a content grouping. All you really need to know is what the page URL, Page Title or Screen Name is. The other routes require some development work, but this one is surprisingly easy to create, the hard part is working out what goes into each group.

Let’s walk through an example for The Coloring in Department. Start by clicking on the button “+NEW CONTENT GROUPING” and give your content group a name. I’m going to call this ‘Website Structure’ as that’s usually where we start.

As we're doing a demo using the rules option we need to open the rules editor, click “create a rule set.”

For each rule I need to do the following:

• Enter the name you want to use for the Content Group

• I will start with the homepage, so I can name this ‘Homepage’

• Under Define rules, select either Page URL, Page Title, or Screen Name

• I am going to use the Page (so the URL) but remember you have the option to select the page title, or screen name

• Select a matching option and enter a value to match

• So I will use Page> exactly matches> /

• When you have defined all the conditions you want to use, click Done.

(After you finish all your configuration for the group, click Save.)

Next, I want to add the next section to my website structure, our course pages. So, I will pop in the name I want to use for the Content Group. So I will call this ‘CID courses’

• Under Define rules, select either Page URL, Page Title, or Screen Name

• I am going to use the Page (so the URL) and I will select a matching option and enter a value to match

• This time I will use Page> starts with > /online-digital-marketing-courses/

• This will pick up any pageviews for /online-digital-marketing-courses/ and anything that follows eg https://thecoloringindepartment.com/online-digital-marketing-courses/google-analytics/

• When you have defined all the conditions you want to use, click Done

Now, for an example using this same website structure Content Grouping, to show you how to use the ‘and/or’ option.

• Enter the name you want to use for the Content Group

• I will call this one ‘About Us’

• Under Define rules, select either Page URL, Page Title, or Screen Name

• I am going to use the Page (so the URL)

• Select a matching option and enter a value to match.

• I will use Page> exactly matches> /contact/

• And as for our website the way we have structured the website I will select ‘or’

• Page> starts with> /digital-marketing-trainers/

• As that will also pick up the page /digital-marketing-trainers/aiden-carroll-and-jill-quick/

• When you have defined all the conditions you want to use, click Done.

Keep clicking save as you work through this. I have created a whole rule set and then hit the back button and lost my work. Sad times. You are working in a browser, which is live, so save away.

Assign content via extraction

We are going to need to do some Regex work here, remember that thing we talked about in filters. Regex is needed here my friends, if you have a larger site, with a slightly more complex URL structure.

You would follow a similar pattern from our Rule Set, but select Add Extraction as your option, give the content rule a name, and then select either Page URL, Page Title or Screen Name once again. Notice how there is ‘no page contains something that is equal to’ option here. You would have to write the regex capture for the content instead

Here is an example used by the Google Demo Account.

• Page > /Men/(.*)/

  • Creates a Content Group for each subdirectory of /Men/, and adds the pages in each subdirectory to the corresponding Content Group

• Page Title > (.*shirts).*

  • Creates Content Groups for pages that contain the word shirts
    
    For example, if your site has the following directories with shirts pages:

    • /men/m_dress_shirts.html

    • /men/m_tshirts.html

    • /boys/b_dress_shirts.html

    • /boys/b_tshirts.htm.

Assign Content via the Tracking Code

In this option, you will need to work with your developers, as they are going to need to modify your tracking code. You would select Enable Tracking Code, keep the toggle turned ‘on,’ and then select the index number and modify your javascript tracking code to include one of the following snippets. You need to make this code modification to each page you want to include in a Content Group. A little bit like the original tracking mechanism we talked through at the beginning of the course.

Thinking back to your audit, review what you have and what you think you may need.

Brainstorm what would be useful for you, and how you want to group your content together. Then map it all out in your measurement plan.

Some Things to Remember.

You can drag and drop the Content Group rules so they match the order you want. Google Analytics processes the tracking code first, then the regex, and then the rules. As soon as it finds a match, the processing ends, and your content is grouped according to that first match. This is a bit like with the Filters function, where the output of one filter is the next filters input. So, please think about how you create your rules and how this computer program is going to work through them.

Bonus round.

Not only do they help you when looking at your content reports, but you can also use these groupings in Segments and in other reports as secondary dimensions. We will walk you through these examples in our module around the reporting interface.

This is really just a repeated message from our Filter module. In your audit, go through each of your reporting Views and make a note of the Filters that have been assigned to the View.

Very important, have a look at the View order.

For any of the Filters you have on the View, remember that this is just showing the Filters on this View, and if you click on one of the filters you will notice that there is no option here to see where else the Filter is applied, you can only do that in the Account ‘All Filters’ report.

If you edit a filter at View level, it will impact any other View that filter has been assigned to.

And in case you forgot, or skipped the module on Filters here’s a quick recap:

• Filters take about 24 hours to work on your Account, so when you put them on your test View, you should ideally check in a day later, and I would like to have at least 7 days worth of data to look over and check. You may need more time to check how they are working, depending on what your normal traffic looks like

• One Filter input is the output of the next Filter, so your Filter order can make a big difference to your data

• Filters are assigned to your View, but if you edit a Filter at View level, it will impact any other View that has that filter added to it. This is because Filters sit in a big bulk at the Account level. Remembering our House Model©, anything you do to your roof is going to impact the floor and all windows associated with it

• Google Analytics is not case sensitive, so even if you think “I don’t think I need any Filters” that’s probably not true, if you have, say, for example , that you have a few URLs that are a mix of lower case and upper case, they will show up in your reports as different pages, and therefore you have fragmented your data, which is not ideal

The Default Channel Grouping (which you can find in your Admin> View settings) is what powers your gorgeous Acquisition > Channels report. You know, the one you use to see how your marketing is working for you.

This is part of the Admin area that we will spend quite a bit of time on when we talk about tracking your acquisition traffic.

All I would like you to do for your View audit, is click on Channel Settings> Channel Grouping and make a note to see if there’s anything new in there.

You have ‘System Defined’ channels, which are channels and rules that Google have defined. You can also create your own, which are called ‘User Defined,’ because you, the user, can define them. Sounds simple, but there is way more to this story.

It’s such a good story, it has its own module!

If you have a website where you are selling stuff. As in, I would have the ability to go to your website, add to cart, give you my credit card details and pay you for the order. Then you need to set up ECommerce Tracking.

You may think that this has something to do with Goals, and it kinda does. It’s quite conversion orientated, to show that your website traffic equals dollar-dollar bills. If you have a thank you page for your orders (as in a page you get to which only happens if you complete the sale (e.g. /thanks-for-shopping) which is highly probable, then you will of course want to create a goal to show that people converted. Which is obviously very useful in itself.

But, if you sell lots of things, like a clothes shop, or a software as a service with bespoke product options, you’ll need more than just a ding-ding of the bell to say you made a sale. You need, and dare I say it, you should want to know more.

You want to record and report on the transaction total (so how much cash did you make on that sale). You want to know which products you sold. If there was any tax added to the sale. You would want to know the name of the product. So, yeah. More than you get from just the thank-you-page-we-have-your-money destination goal.

Hopefully you’re sold on the idea that you should be getting this extra information inside your analytics.

Spoiler.

You are going to need to work with your developers to make the magic happen. Which is going to require some work.

First things first, let’s understand the concepts and the process to make it happen.

There are two types of E-Commerce tracking that you can use.

1- Basic Tracking

Basic Tracking works by adding additional code to your thank-you pages that confirm a sale. There will be code on that page that will push data into your Google Analytics Account. There are two types of data types that are used, which are:

‘Transaction Data’, which is as it sounds, the revenue, shipping, tax data. And ‘Item Data’, which is data about the items you are selling, be it services or products. So, think about the name and price of the items you are selling, the SKU code (that means stock keeping unit, which is used in managing inventory). Then you have things like the item category for examples Dresses, Shoes, the quantity (how many you sold) and the transaction ID. All useful information, as a start, we think.

2- Enhanced ECommerce

Enhanced ECommerce needs a bit more work from you, so that you get the lovely data into your Google Analytics Account. As a side note, depending on what you sell and how much money you make, you may decide to start out with Basic ECommerce. As you build and expand your business, move up a level to Enhanced ECommerce. It all depends on your business model, marketing strategy and budget.

Ok, so back to Enhanced ECommerce. Unlike the Basic tracking, which happens on the thank-you page, for a completed order - here, there’s additional code that needs to go on other pages of your website, like the product pages and checkout steps.

Enhanced ECommerce gives you more than you get from Basic, unsurprisingly, and it has five data types which as you will see can overlap between each other.

‘Impression Data’ gives you insights regarding how the product was Viewed on your website. Things like the brand that is associated with the product, variants of the product, for example black dress, white dress, the position the product was in if it was in a list or collection.

‘Product Data’ gives information on individual products. So, things like the brand name associated with the product, and if say a coupon code was used for the product purchase.

‘Promotion Data’ passes information about any promotions you have that were viewed by customers. Things like the creative, did they see a promotional banner and click to the product page.

‘Action Data’ is the bottom line stuff, all the ECommerce action data = money data stuff. This is where you can send the revenue data to Google Analytics, if any tax was associated with the transaction, or shipping costs. It also has the ability to track the specific steps in the checkout process, which is very handy when you want to see if you have a leaky bucket. Do people get to the last page and just leave? This would give you at least, a starting point to investigate what’s going on with your checkout flow and ideas on how to fix it, so you make more money. Yaeh!

‘Product and Promotion Actions’ this helps you to interpret product and promotional data that you send to GA. Like people adding products to shopping carts, or removing them, if they initiate the checkout process, that kind of thing.

All sounds wonderful doesn't?

Now, how do you get the goods into Google Analytics?

Setting up E-Commerce for Google Analytics

Short answer - ask your developers. This also happens to be the lazy, kind of useless answer.

Real answer, working with your developers. You need to map out a clear plan, which will vary depending on how your website is built. We're after all our own individual and special snowflakes, so the implementation can vary from one ECommerce setup to the next. It really should, if we are honest.

The first thing to check in your Google Analytics Admin audit, is to check your Conversions> ECommerce reports. Is there anything there?

If you don’t find anything in the reports but you think you had the ECommerce data added to your website by a developer, the next check is to go to your View settings and for each View you have, check if the ECommerce toggle is turned on. Is it?

This may seem really bloody obvious, but I have done many audits that HAD the data on the website, but nobody knew to go to View>Settings and turn this toggle ‘Enable E-Commerce’ to ‘On’. So they both had they data, and did not have the data. Fun times.

And as you know all too well now dear analytics student. Google Analytics will not go back in time and re-process your data. I had a client that missed out on two whole years of data because someone didn't turn this toggle on. And, I’ve seen an Account where one View had Basic turned on, and the other reporting View had both Basic and Enhanced ECommerce turned on. It happens.

For some of you, you either have it set up (thank the analytics gods) and you just need to check if you have or need the Enhanced option.

Some of you, just need to turn on the toggle to receive this information in your Account.

For the rest of you.

You need to get this specced up, and briefed in, with your technical dev-people.

There are a few ways to do this. How it’s done for you will depend on your ecommerce platform, your shopping system as it were.

If you are using something like Shopify, or WooCommerce, they have plug-ins to help setup ECommerce within Google Analytics. So, go check out what types of integrations you have with your shopping system provider and how they might work with Google Analytics.

After that, you can either manually do it, as in manually tag your site. Admittedly, almost no one really does now because it ain’t 2005 anymore. Instead the common, the go to option, is to use Google Tag Manager (hello again GTM).

Google Tag Manager will help you populate the data layer with ECommerce transaction and product variables (those data types we just chatted about) that one would have on their thanks-we-have-your-order page.

Or, if you are going into the Enhanced ECommerce route, populate the data layer with data for the product and checkout pages on your website.

A few things may be going through your head right now, as they went through mine, when I first learned about ECommerce tracking.

One thought was, why can’t I just pop the code from the Google developer help pages onto each page, like adding the Google Analytics tracking code? Well, each sale is unique to the user, so the data is dynamic, as in, it is unique to the user. Plus, your business is unique too, so you need to tell our lovely GA computer program which data types it should be looking for, for example, what your brand names are for a product, because, how would it know?

The next thought, for me anyway, was “what is a data layer?”

Good question.

So, let's just chat about the Data Layer.

If you Google ‘Data Layer’ you get an answer like this “A data layer is a JavaScript object that is used to pass information from your website to your Tag Manager container.”

So, think of the data layer like an intermediary. You pop your data into the data layer, and it keeps it nice and safe, to then pass on to your website, which has other things linking to it, like your Google Analytics javascript.

Provided you have sent your data to the intermediary, and that data is written in the language of the platform it's passing the information onto, it works. Oh, and don’t forget about turning the toggle ON to receive the ECommerce data.

So your plan is, as mentioned, to check if you have ECommerce data in your Conversion reports first.

Then head to your View settings, and make sure you have turned on the toggle to receive the data. If you have more than one View, check each View to make sure.

• Sign in to Google Analytics

• Click Admin, and navigate to the View you want

• In the View column, click E-Commerce Settings

• Set Enable ECommerce to ON

• Click Next step

• Click Submit

Check your Ecommerce platform to see if there are any plug-ins that will help with the heavy lifting.

If your shopping system has no plugin, or you have a bespoke shopping system on your website, you need to brief your development team.

You will need to get the ECommerce Plugin setup on your site, which is referenced in the Google Analytics Developer Guide. This is not the same as, say a shopify plug-in. This is a Google thing, and in their words:

To reduce the size of the analytics.js library, ECommerce tracking is not provided in the default library. Instead, it is provided as a plugin module that must be loaded before being used.

To load the E-Commerce plugin, use the following command:

ga('require', 'E-Commerce');

This command must occur after you create your tracker object and before you use any of the E-Commerce specific functionality.

Once loaded, a couple of new commands specific to E-Commerce tracking will be added to the default tracker.”

There are two types of ECommerce Plug-ins for you to use, one for Basic ECommerce tracking and another for Enhanced Tracking. If you are bumping yourself up from Basic ECommerce to Enhanced you need to get your dev team to migrate your plugin from the Basic plugin to the Enhanced plugin, as they can’t work together.

Basic ECommerce Tracking

For Basic ECommerce to work on your site, you need to populate the data layer with the following data variables, and they need to be triggered on your “thank-you-confirmation” page.

The data variables that are required in order for it to work are:

• transactionID

• transactionTotal

Optional data variables are:

• transactionShipping

• transactionTax

• transactionProducts

Although it’s optional, most ECommerce sites would add the transactionProducts to the list, as it gives you richer information. Using transationProducts means you have to use these variables:

• Name

• SKU

• Price

• Quantity

There is an additional optional data type too:

• Category

This one is used a little bit less often.

These transaction tags will then show up in your Conversions reports. See this example from an Account that is just using Basic ECommerce. We can drill into the product performance to see out of all the products we sell, which ones have been sold on the website in a given period of time. How many were sold, and our product revenue.

Sales Performance is a report that shows how much you made in a given day. And remember here guys, it is going to pull in data as per your time zone for that View.

The Transaction report will populate all the Transaction IDs which will link up to your shopping system. Time to purchase, shows the number of days between a user purchase and the campaign referral. We’ll go into this in more detail when we go through the Reporting interface modules.

But, as you can see with just this quick show and tell. This is very valuable information.

Enhanced ECommerce Tracking

If you want to level up from there, this is going to take a lot more work from your developers. All five data types we have mentioned work together to give you so much more information, and a totally different report in Conversions> E-Commerce.

Now, I am not going to read out all the data types in detail, as that would probably send you to sleep. What I will say, is that there are a set number of requirements that I would have as my go-to ECommerce enhancements.

• Clicks on a product link

• Viewing product details

• Impressions and clicks of internal promotions

• Adding / removing a product from a shopping cart

• Initiating the checkout process for a product

• Purchases and refunds

In addition, I would want to have my ECommerce funnel mapped out so I can drill down into the ECommerce data further, by looking at the Shopping and Checkout Behaviour reports. Now, just to note, this is turned on at View level, where you type in the name of the steps into your funnel set up.

These have to match the name you have given in your enhanced ECommerce settings. So please, please, sit down with your dev team and agree on user-friendly, idiot proof names, as they are going to show up in your Account.

This example from the Google Demo Account is a good example of clean, user friendly labelling.

Billing and Shipping

Payment

Review

Things to Keep in Mind

I have done a lot of GA audits and when it came to E-Commerce companies, they always asked why there was a data discrepancy. Now, as we have gone through in our Admin deep dives. Having staging sites not filtered out, having the wrong timezone, not having the correct Account structure can all make the data murky. If you have ECommerce set up correctly, there will always be some gaps.

Why? Well Google Analytics was created to track what your website visitors are doing on your website. It was not designed as a customer relationship management database or a shopping accounts system. Let’s be fair.

Which means, it will tell you how many people bought a particular product, the transaction ID, all that glorious stuff. However, it will not tell you if someone who bought the clothes then decided to send them back to you in the post because they didn't quite look right on them. Or if they buy the hotel room, and then cancel the order. All that refund data, yeah, that will not appear in the Account.

Although, there are some workarounds to fix this which we will cover in our Advanced Analytics module. It is possible to link up CRM and Sales systems to push data back into Google Analytics so you get a better picture. More on that little gem later!

https://ga-dev-tools.appspot.com/enhanced-E-Commerce/

https://developers.google.com/analytics/devguides/collection/analyticsjs/E-Commerce

https://developers.google.com/analytics/devguides/collection/analyticsjs/enhanced-E-Commerce

Calculated Metrics give you the option to personalize your reporting by combining two existing metrics together to provide insights relevant to your business. Which is quite nice.

Every report in Google Analytics is made up of standard metrics, things like, your users, sessions, page views. You cannot create Calculated Metrics using Dimensions, because the Dimensions are definitely not Metrics, basically.

To have the option of creating a Calculated Metric will help you when you have previously had to take two numbers and separately do some maths to get another related number. Or, you could create a custom metric that will do the math for you and show it in your Google Analytics reports.

You can be as creative as you like, but what you don’t want to do is create metrics for the sake of it, you need to be in the mindset of whether or not it’s a worthwhile use of time.

Only create a metric that is going to tell you something, give you some insights, or that you can take some action from. Otherwise, you are just adding another metric to a report for the sake. Don’t do that.

Equally, you only have five per View, so make them count.

They require some knowledge of regex, and this course isn’t about “coding” - but there are however, plenty of blog posts where the analytics community has shared their use cases.

But what should you create? My advice is to go back to your business Goals think about which questions you are looking to answer, and go from there.

When you create them you need to give them a name. Here again, try and be descriptive, so they make sense to everyone who has access to your Account. So think more ‘Revenue Per User’ and less ‘Not Set’ or ‘CalMet1’

Then you need to give it an External Name, this field will be populated when you enter a Name for your metric. You cannot change this after you have created it, so think carefully otherwise you will have to delete and start over again. Which would suck.

Formatting Type is another thing, you can have integer (which is a fancy word for number). Currency, e.g. $195, time - which is set like a 24-hour clock, e.g. 00:17:10 or percent, e.g. 30% ROI.

Then you have your Formula, this is where it may be handy to work out which metrics you want to work with, as you can type it in the box, or use the dropdown if your metric is available already.

Google provides two use cases in its description of Calculated Metrics, so let's follow these two examples.

Revenue per user: Good to find out the revenue of your website users

• Name: Revenue Per User

• External Name: (automatically populated)

• Formatting Type: Currency (Decimal)

• Formula: {‌{Revenue}} / {‌{Users}}

Currency Conversions: Good too if you have a number of regions, you can apply this calculated metric to the countries View

• Name: Revenue from GBP to EUR

• External Name: (automatically populated)

• Formatting Type: Currency (Decimal)

• Formula: {‌{Revenue}} * 1.27

And that, as they say, is that - for now. Well done on getting through this module - we know it’s a toughy!

If you are selling things on your website and you want to know the difference between basic and enhanced ecommerce?

You should download this resource.

If you want to know what types of data you could have with basic and enhanced ecommerce?

Yeah, you should totally have a look at this resource.

And, if you want to check what the steps are to get your ecommerce data inside your reports?

You got it, it's yours.

These are of course optional - but they add a different take, even more depth, or just a fascinating look at how the other half live

Take this quiz to check that you've understood the Module!

This last section of your analytics Admin, so called Personal Tools & Assets, isn’t needed for your main analytics audit, but it does link up to your measurement plan when it comes to using Annotations and Custom Alerts. So it’s worth familiarizing yourself with it.

Let’s say you created a segment (which we will cover later in the course) then they will be listed here under ‘Segments’. And as they are your assets, you will find any segments that you have ever created that were done so using the email address that you use to access the Google Analytics account.

I have had access to hundreds of Google Analytics accounts for my work email, understandably my Segments list is quite long, as it includes any segments I have created across all accounts.

The same thinking applies here if you created an attribution model or a custom channel grouping. All of your work would live here, as they are your assets.

However, that doesn’t mean that everything you create here under this seemingly personal umbrella, remains private. For the most part, others would see your work. Here are some examples (and we will loop back to these assets in future modules).

• If I create a segment and decide NOT to share, then no one else can see it. So this list is private to me

• If I create a public annotation, everyone who has access to the reporting view will see it. So it is public

• If I created a custom alert and sent it to someone on my team, they would by default, see it

The key parts that you want to focus on for your audit and measurement plan, is to investigate whether or not you have any annotations or custom alerts set up on your account. Which we will cover in the next lesson.

I love them because my tired human brain forgets things.

If I were to ask you now “What were you doing 6 months ago today for work?” chances are you would struggle to remember what it was you were exactly doing.

Because we are busy humans, juggling a million things, managing people, managing yourself. You know, just keeping your head above water.

As we live in a busy marketing world, it’s not uncommon to look at your analytics reports, and see a spike in traffic. You know those moments where there is a jump in the sparkline and you look and think, “I wonder what happened there?”

I’ve done many audits where I’ve asked the client about a jump or decline in their reports and they shrug their shoulders and say “can’t remember, dunno”. They are tired too.

This is where annotations come in.

There’s an option to add little sticky-post-it-notes onto your analytics reports to help you understand what those blue sparklines are doing.

Anyone can create them, and you can apply them to historical data. They are very simple to use, the hard part is to just get into the habit of using them. A habit worth forming though!

To create an annotation, you just click on the little triangle under a report and select +Create New Annotation which is on the right hand side. It’s quite small, almost like no one wants you to use this little gem.

You can then amend the date and use the calendar to select the date you want to make a note on.

Then you have a text box, but you only have 160 characters, so no big long essays people, just a nice, user-friendly note.

You also notice that there’s an option to make them private (only you see them) or public (anyone who has access to the account can see them). Also worth noting, as they are assigned to a reporting view specifically, you may need to repeat the task if you want the annotation on other views.

Once you have finished, click done, and that is it.

Then, when you are looking at reports within the date range of your annotation you will see a little speech bubble on the report which is your annotation. Or you can look at your Admin > Personal Tools and Assets > Annotation to see a chronological list of annotation on that reporting view.

How should you use them?

Start with you.

As a starting point, focus on you and your own work, and decide if you need the notes to be private or public. So when you launch a new campaign on social media, or you sent out an email campaign. When you get mentioned in the press, or an influencer posted about your company.

Company-wide marketing initiatives

Make notes on the work you are doing as a marketing department or business department. All these should be public annotations. Things like launching a big campaign, changing your website design. Launching a new SEO strategy.

Business initiatives

For your business and the products or services you sell, make notes about updates and changes. Things like updating your software for your customers, launching a new product. Opening a new shop, or starting a community.

Marketing world

Make notes on significant shifts in the marketing space. Google announced they have updated an algorithm. Annotate that. New laws for opting into email lists. Annotate that. New social media platform announced. Annotate that.

The world

This is for anything outside of the marketing bubble that can impact your business. Things like new legislation, political shifts, change in taxation. That kind of thing.

What you will be left with is a nice list of notes that can help you identify causal factors that can impact your reporting. Essentially, a list of “things that might have had an impact.”

So, think about how you can use annotations and get your team, agencies, everyone really, to start to use them. It is such a simple thing to do, but can turn out to be so useful in understanding your data.

This is another very useful tool that allows you to create alerts if certain things happen to the traffic on your website.

When I say alert, I mean, Google Analytics will send you an email, or a text message when you want to know if something went up or down on average. This is an early warning system of sorts.

Just think about that for a second. What would it be worth to you, to get an email or a text message to say that your website traffic is down and you are not converting? That kind of alert can save your bacon as you can go off and investigate if your website has a problem that you need to fix immediately. Flip that idea, and get alerts for something going up, like press traffic, or organic traffic growing like crazy. High fives all round.

Our recommendation, you need to get a balance as to what is important to you: you don’t want to get lots of alerts that you won’t act on, that’s pointless. Also, if you are assigning alerts (either by email or text) then notify that person so they know what you are doing and why they are getting that alert.

Set up alerts for anything that would positively or negatively affect your site, things like.

• Traffic changes

• Technical e.g. site speed

• Key goals changing in conversion rate

• Products out of stock

Let me show you how you can set up an alert based on a decrease in revenue.

Head to your Admin area and navigate to Personal Tools and Assets > Custom Alerts

Select +NEW ALERT

Give the alert a name (make it user-friendly and descriptive). So for this example, I will call this “Decease in Revenue Alert”.

Then you can select which View you want to assign this alert to, which is super handy. Although the User Interface will pull up every report you have access to, which can be confusing at times. Make sure you select the correct reporting view to avoid this.

Decide which time period you’d like to apply this to, you have the option for Day, Week and Month. I’m going to select Week for this example.

Next, do you want an email, or text, and do you want to add anyone else to the list? Again make sure you let that person know ahead of time!

Then we pop in the Alert Conditions. This is where it’s helpful to know which dimensions and metrics you want to look for, and why brainstorming ahead of time is critical.

For this example, I am going to keep the alert applied to data from “All Traffic” and then change the Metric to “Revenue”. The condition is a dropdown selection.

You can select less than or greater than, and you then add your Value. You will need to know what your average and baseline numbers are so you can correctly set this up. For example, if you know your revenue is around $1000 per week, you could then select greater than $1200 as a reasonable option.

You can also set this up to flag decreases or increases by more than a specific value. Then decide on the time period again, which is the previous day, same day in the previous week or same day in a previous year. This is really handy if you know you have a cyclical cycle.

The last option is the same as our previous example, but with a % value instead of a metric. For example, sessions decrease by a % and not by, say, 50,000 as a numerical value. When you are happy with your Alert, hit Save Alert and you are good to go.

We will close this module by revisiting the Admin Audit Template and show you an example of what a completed audit would look like, and with that, what your next steps are for your measurement plan.

We have gone through a lot in our last few modules, but you can now see that getting your admin house in order is just, so, super important. Without it, the data you are reporting on can be dangerously wrong.

There is still more to learn, but at this stage of the course, work through the Admin Audit Template and start by making notes across the Account, Property and View settings.

Here is one from an account we looked at a while ago. As you can see, it’s as simple as it looks, the impact is knowing what all the settings actually mean and how it impacts your data. Every single audit we have done looks different. I can’t stress that enough. Every website is different, it has a different history, business model, resources, but the process remains the same.

Most companies have no analytics process in place, and as you can see with our example, just listing the View audit you can see that some reports are not getting all the e-commerce data, and are on the wrong timezone. This is a major problem.

A top tip from us at this stage, is to use, if you can, a document where you can add notes and comments. Google docs or Dropbox are a good starting point. If you don’t have that, good old fashioned pen and paper will do. Highlight key issues that you know are causing a problem as they will be written out in more detail in your measurement plan.

Well done for getting to this stage of the course, you are halfway there. Next up. Tracking your marketing campaigns like a champ. See you on the other side.

You should be finishing up your account review right around now - because in the next section, we have some top notch surprises for you!

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Hello my friends, and well done for getting through the previous modules. Seriously, high fives all around. The ‘how does the admin area work?’ is a lot to take in. But, is really important, as I’m sure you now know.

Now that you have a good idea of what you need to do to get nice clean data, you want to move your attention into thinking about why it mattered in the first place. Think about those visitors who arrive at your website, those marketing channels you are spending so much time and money on.

We hope you’ll agree that tracking your campaigns is absolutely critical, not only to your marketing department but to the overall performance of your business. Tracking your campaigns helps you to understand what’s working and which tactics are a big fat flop. But, it’s also important to use the data from your analytics to back up your budget and resources for all your super smashing marketing wizardry.

However, what if I was to tell you that you may be doing your tracking all wrong? Would you feel nervous? A pang of panic? Have you made the right decisions when sacking that agency for not delivering, or put money on a channel that was actually, well, wrong…?

As a marketer (or anyone whose job it is to get people to your website) you have to really understand how Google Analytics works. How it defines your website traffic, how it may be bucketing your wonderful work, which could be, for all your best intentions and tagging efforts - being thrown into the wrong rep[orting bucket. Leaving you wiping tears from your keyboard.

How UTM Tracking Works

Let’s start by breaking down what UTM tracking codes are and how they work.

If you’ve never heard of the term ‘UTM’ before, you have at least clicked on a UTM link. They are special links that you create to help Google Analytics understand where your marketing traffic is coming from. They are to be used on your external marketing campaigns. You do not, I repeat do not use these codes on your own website. If you do you’ll mess up your data. Seriously.

They are to be used on marketing campaigns, like your email, or social media traffic.

UTM stands for Urchin Tracking Module. Why Urchin? Google bought Urchin, which was a company who created the analytics platform you are using today, and I guess the name just stuck.

In any case, they look like this when they are done.

thecoloringindepartment.com#utm_source=onboarding-analytics&utm_medium=email&utm_campaign=AUG-18-cohort&utm_term=&utm_content=CTA

The visitor will still get to the URL you want them to go to, but it helps our lovely Google Analytics computer program to understand exactly where the traffic came from. Which is super important, but surprisingly super easy to get wrong. Let’s start by breaking down what each of the bits in a UTM code actually mean.

URL

First up, you need to have a URL that you want the traffic to go to, this sounds uber obvious, but you want to check that you have the correct URL, check it works, no one wants an error page (or 404) when they click on that link. Check that it’s currently valid e.g. your HTTPS version, not the HTTP, that will redirect.

Medium

These are the big broad buckets for your marketing channels, Organic is a Medium, Email is a Medium, Social is a Medium.

Source

This tells us where the link lives, so if Organic is the Medium, the Source would be Bing or Google, if Email is the medium it will be the name of the data set e.g. newsletter database, or customer database. If it was Social the source would be Facebook.com or Twitter.com for instance.

Campaign Name

You can choose to give the link a campaign name, so if you were doing a marketing campaign for a promotion that included a bit of Paid Search, Social Media and Email you can name all your traffic involved in said promotion under one campaign name e.g. “AUG-18-cohort.” This, you can then dig into within the Analytics platform, which is a massive timesaver, to see how the collective channels are working for a campaign overall.

Content

Love using this element - even though it’s optional. It gives you the option to further slice and dice your data. If you had an email campaign, you would set the Medium = email, Source = newsletter-database, Campaign = BlackFridaySale and if you had, say a call to action (CTA) that has multiple links to the same URL, you could create two UTM codes. The only difference between the two, would be to vary the Content tag, one would say Content = CTA the other Content = Image. This would give you some insight into your email creative and whether it’s working at driving traffic and conversions.

The Tracking Triangle

How we remember how UTM codes work, is with our Tracking Triangle. Looks a bit like this:

URL - The Where: As in the destination that we are sending traffic to

Medium - The How: More detail on the channel, as in a specific breakdown of the channel

Source - The What: Where does that link live within the Medium (and therefore channel)

Campaign Name - The Why: Used to tie together your marketing campaigns, especially those that sit across multiple sources and mediums.

Let’s do an example for Email:

URL- The Where: for example thecoloringindepartment.com

Medium - The How: email

Source - The What: newsletter-database

Campaign Name - The Why: Oct-19-CourseLaunch

And our link would look like this:

https://thecoloringindepartment.com/?utm_source=newsletter-database&utm_medium=email&utm_campaign=Oct-19-CourseLaunch

This means, if we sent out a newsletter via email, as part of a campaign in October 2019, to let our subscribers know we have launched a new course, the Google bouncer will put the traffic into the Email bucket.

Here’s another example, this time for Social Media:

URL - The Where: thecoloringindepartment.com

Medium - The How: social

Source - The What: twitter

Campaign Name - The Why: Oct-19-CourseLaunch

And that link would look something like this:

https://thecoloringindepartment.com/?utm_source=twitter&utm_medium=social&utm_campaign=Oct-19-CourseLaunch

This means, if we posted say, a tweet, with a nice picture, to let people who follow our account know, as part of a campaign in October 2019 that we have a new course, the Google bouncer will put the traffic into the Social bucket.

The idea of a UTM code is simple. What could go wrong? Well, a lot. You really do need to help Google Analytics understand where your inbound links are coming from, to help it attribute your work correctly. It is, after all, a computer program!

So, you really need to know how Google Analytics processes that information. I know you guys don’t lay awake at night thinking ‘I wonder how the Google Analytics core reporting API defines the Default Channel Attribution model for my Acquisition reports”.

Lucky for you, we have (true story), so here we go!

The Default Channel Grouping (which you can find in your Admin> View Settings) is what powers your gorgeous Acquisition > Channels report. You know, the one you use to see how your marketing is working out for you. We touched on it ever so slightly when we did our Admin deep dive module that focused on View Settings particularly.

Think of the Default Channel Grouping as a bouncer, they are at the door of your website, asking people where they have come from, and checking through their little list to see if your traffic matches the rules that they have been given.

This list, is -really- important. Let me explain how Google defines it, and show you some common errors (that you may be doing, and will need to fix).

This is the actual list of rules for the Default Channel Groupings, this is the little list the bouncer is checking your traffic against, and it all -has- to match exactly what is here, case sensitive, no room for error.

Now, something important to add at this stage in learning about tracking traffic like a champ is this. All the tags, all the Mediums, Sources etc, they all feed into the Acquisition Reports, and that report has a Dimension called Default Channel Grouping. Not the Default Medium Grouping. Fun!

Google Analytics, and its bouncer at the door, will group the Mediums and Sources, and group them as your Channels. That’s why you can have different Medium definitions that can get grouped under the same Channel name. This happens a lot.

A good example that demonstrates this - is Paid Search. Any traffic you are buying from search engines. If the medium exactly matches either cpc, ppc or paidsearch, then GA will put in under Paid Search in your Acquisition reports. So, straight away, three different Mediums are now the Paid Search Channel in your reports.

Let’s walk through this beefy list, shall we?

Organic Search

You don’t need to do ANYTHING for Organic. Google Analytics is really good at knowing if the traffic is from search engines - mostly anyway. If the bouncer sees traffic from a known search engine, then it goes into the Organic Channel category. Remember, if you have traffic from a Search Engine that Google doesn’t have in its list, you can add it by going to Property> Tracking Info > Organic Search Sources.

Paid Search

As you are spending money on this traffic, trust me when I say that the people you are buying the traffic from (hi Google Ads, hi Bing Ads) - know what they are doing. These guys know how to tag all the links so that the bouncer knows it is paid traffic. Makes sense, they want to show you what your money is buying, so it will auto-tag the medium as any one of those many mediums; cpc, ppc, paid search.

Referral

This channel is used for the traffic you get from other websites. It works exactly how it sounds, someone is referring your website to someone, they are giving you a thumbs up. So, let’s imagine a blogger writes something about your company, and they add a little link onto their blog. If their reader clicks on that link, and they land on your website, the bouncer will pop that visitor in the Referral bucket. Easy peasy.

Social

A slight wrench in the works, that causes some confusion, is traffic from social media channels. You see, technically speaking, Twitter.com is a website, Facebook.com is a website. So, if you get traffic from say Twitter - Google Analytics, and its Default Channel Grouping bouncer, will put it in the Referral bucket. Not so easy peasy.

As you can see here, in this example Acquisition report, within the Default Channel Grouping the Medium is ‘referral’ but the Channel is Social.

The bouncer is trying to be helpful by splitting up traffic from websites that send you traffic, like our blogger example, and social media sites (which are technically websites) that also send you traffic.

This is a good example highlighting that we are not just talking about a Medium. We are also talking about the Default Channel Grouping. AKA the Acquisition reports. Social media traffic can show up in your Acquisition reports as Social, since that’s the name of the Default Channel Grouping. The Medium can be both referral or social, social-network, social-media etc.

Little tip here, when you look at your Acquisition> All Traffic> Channels report. It will split out the Referral Medium to two Channel Groupings, one for Social, and one for Referral. If you head over to Acquisition> All Traffic> Referrals they are NOT split out, they are added together. This has caught us out before when reporting on our total traffic numbers. Keep an eye on it.

Email

Ah, email, who doesn’t love a thoughtful email? They can be used for all sorts of marketing strategies. Acquisition, retention, activation, referral, just keeping in touch with customers about what’s going on with your business.

However, if you don’t take the time to tag any of the links inside your email campaigns specifically with medium=email and remember it has to be exactly ‘email’, you are not going to get accurate numbers.

Note, not “Email” with a capital E, or “Email Marketing,” it has to be lowercase, “email.” You may think Google Analytics will just sort it out, and when the visitor lands on the website it ‘just knows’ it will be from email. It doesn’t.

Sorry to burst the bubble, but untagged email links will end up with the traffic going into Referral or Direct. It will end up as Referral if the person who clicks on the link, did it when they were in a web browser looking at their inbox, like when you are using Gmail. If it’s opened on a desktop system, different rule applies, thinking of those office workers or home computers that are set up with Outlook, that kind of thing.

If your visitor arrives from an email that was from there, well there will be no parameters. And when that happens the traffic goes into the Direct bucket. It’s definitely not Direct traffic.

Which moves me nicely on to Direct traffic.

Direct

Anything that Google Analytics can’t identify, meaning that the bouncer has gone through its list to see if it came from Organic, or Social, or a website, if it can’t find anything - it will just pop it into Direct. Direct can be a bit of a catch all as a result.

Most people think that Direct traffic is for those visitors who just type your website into a browser, or have you saved as a bookmark. You’re not wrong.

However, it also means that any visitors that Google Analytics can’t attribute an origin to, like our email traffic opened from a desktop app, will end up in Direct.

If your website is still on Http and you get traffic from an Https website then it will end up as Direct.

Or, traffic from a mobile or social app, if you don’t tag it to a known Medium or Source it will end up in Direct.

Let’s say you send out a lot of PDF documents with links inside of them, yep all that gets put into Direct too.

Links in your staff email signatures? The same example as our email example, depending on where that traffic came from, will end up in either Direct or Referral.

After Direct you have another channel called (Other)

(Other)

Unlike traffic that gets lumped into Direct, if you have any traffic tagged where the medium is cpv, cpa, cpp, or content-text then it goes into a channel called ‘Other’.

If you get your Sources and Mediums mixed up, which is a really easy mistake to make, then there are going to be issues. For example, if you create a tag where the medium = newsletter_database and the source=email, then the traffic gets put in ‘Other’.

Equally, if you create a UTM tag with a Medium that the Default Grouping has never heard off, then that also gets put into ‘Other’.

Given the examples, that we’ve gone through, and the Default Channel Grouping list that our bouncer works through. Some of you may have noticed that there is no Channel Grouping for PDF, or Staff Email Signatures, or Paid Social (like Facebook Ads).

Well, some good news!

There’s a way to create your own channels, and we will cover that in the next lesson.

So, you want to create your own channels, do you?

You don’t want your traffic going into (Other) and having to pull and pick at data to find your Mediums. Yep, we feel you.

When you have marketing channels that don’t sit in the Default Channel Grouping list, you can create your own channels. A good example of this is for Paid Social campaigns. If you were running advertising on Twitter, and you tag it as cpc (cost per click), then that traffic will be put in the channel ‘Paid Search’ - which is where all the traffic from your Google Ads or Bing Ads will live.

Technically it is a cost per click activity, but boosting your social posts is a very different tactic than those involved in your search marketing and your AdWords campaigns.

Therefore, it should, in our opinion at least, have its own defined channel. We have seen people log in to Analytics, go to the Acquisition>Channels, and they take this report at face value, then fire their agency managing paid social as the numbers don’t stack up in Analytics. The Paid Search agency, at the same time, gets a pat on the back.

We’ll now show you how to edit your Default Channel Grouping. Let’s go back to our thinking about the core reporting API as being a bouncer, checking visitors on a list.

Editing the Default Channel Grouping is you taking that list, and writing a new set of rules for the bouncer to look at, in addition to what they already had.

We head into our Admin> View> Channel Settings >Channel Grouping and select Default Channel Grouping.

VERY IMPORTANT: What you are going to do here is changing the way that Google crunches your data, and it does this from the day that you create the changes. If you make a mistake you can flatline your data. So, it is very VERY important that you do this in your Test View first. When you are happy with the data coming in, create the same changes in your Reporting View.

• Click on the blue text - Default Channel Grouping.

• Click on define a new channel.

• We need to give it a name, so we will call this ‘Paid Social’

• Next, we define the rules. Let’s select from the dropdown ‘medium’ exactly matches, and then type in your rule. For this example, we will put in ‘paid-social’

• Hit done.

Now, on top of this, the bouncer is a bit lazy, and will allocate visitors based on the first rule they see. That’s top down, from the list. You may then want to change the order, and you can do that by dragging and dropping the channels.

When you are happy with your list, scroll to the bottom and hit save.

Always scroll down and hit save. You are working in a browser and if you don’t do this, all your work will be gone. Rinse and repeat for all your new channels.

Remember to put the channels in order. You’ll want to put your more specific channels at the top and your more generic channels at the bottom.

Job done!

Now, you have a good understanding of how the core reporting API works. And how it actually groups your visitors together, based on the marketing channels they arrived from. You are also now armed with information to edit and create your own Channels should you wish.

So, how do you create a UTM code?

This bit is super super easy - from a process perspective. The hard part is deciding which words to put into which box, and making sure you are using the correct Medium and Source, in the right order.

You can use the Google URL tool. If you do decide to use it, remember that it won’t record all of the links that you create. This annoyed me a while back, I created a ton of links, didn’t record them, and then forgot what I had typed in - only human after all. Even if you put the UTM codes into a word doc, or excel spreadsheet, you are winning.

Let me walk you through an example of creating a UTM link, for an email campaign, using the Google URL Builder tool.

• You put in the URL you want the traffic to go to first, if you remember, so I will put in “https://thecoloringindepartment.com”

• Next, we have the campaign Source, which is where the link is going to live, this example is for email, so I will call this “newsletter-database.”

• Medium, well this can only be lower case “email.”

• Next up the Campaign Name, personally I like to add dates and any geographical information, so I will pop in “Oct-19-CourseLaunch.”

• I can leave Campaign Term blank as that is for paid search keywords.

• Lastly, I have the option to add Content. Now let's pretend I have two calls to action in my email, both going to my homepage. One is a banner, so I could put in ‘banner’ here. The other is a text link, so for that one, I could type in ‘textlink’.

Then at the bottom, you can see the URL generated for you, and you can copy and paste this into your desired UTM home.

We have a Channel Planning Template to help you, that can also be used to create and record your UTM codes, which we will cover in our channel planning lesson at the end of this module.

Right, so you have a good understanding of the Default Channel Grouping and how it defines your marketing channels. Check.

You know how a UTM code works and how to correctly create them. Check.

You also know how to create new channels with User Defined and System Defined Channels. Check.

But, there’s always a but, isn’t there!

If you have created User Defined Channel Groupings, there’s another step you need to complete. You see, as well as a bouncer on the door checking people, you have another reporting API that sits in the Conversion reports under Multi-Channel Funnels.

Now we have a whole module on Multi-Channel Funnel and Assisted Conversions, so, for now, this is just a gentle easing into it.

The reason we are talking about this now, is down to attribution.

What’s attribution then?

Short answer, it’s a fancy way of saying ‘who gets the credit’.

There are seven attribution models in Google Analytics and the default model is the Last Non-Direct model. This means that the last non-direct channel that scored your conversion gets 100% of the credit. Which is a bit rubbish when you think that you have many marketing touchpoints in your customer journey.

So, to help balance the credit out a little bit more, there’s a report in Conversions> Multi-Channel Funnels> Assisted Conversions.

When we check out which channels are assisting in conversions, that lives in our Acquisition>Channels Report, the last non-direct click still wins here. BUT, the reports in the Multi-Channel Reports run on the MCF Channel Grouping. Which is different from the Default Channel Grouping. So, how do you see if your new Paid Social Channel, that we just created in the Default Channel Grouping, is assisting in conversion?

There’s a very quick way to do this.

In your Conversions> Multi-Channel Funnels> Assisted Conversion Report click on the drop down and select “copy MCF channel grouping” to clone the MCF settings.

Now rinse and repeat the same process that you’ve just done for your User Defined channels.

For example, you put in the same medium rule as you did in your Default Channel Grouping, mirror matched, case sensitive. If you put in medium = paid-social well you put ‘paid-social’’.

Unlike the Default Channel Grouping, this MCF Grouping is part of your Personal Tools and Assets, and is only changing the way your current, and future data, is being displayed.

That means when you create this, you need to share this asset with other people in your team - should you wish to get them on board.

Happily, this is as simple as sharing a link.

Head over to your Admin> Personal Tools and Assets> Custom Channel Grouping and select the name of the MCF Channel Grouping you just created. On the right hand side there’s a dropdown called ‘Actions’. Click on this and select ‘Share’. This will generate a URL for your new MCF Channel Grouping and you can share this with others in your organization.

We will cover this topic in more detail in our module around Multi-Channel Funnels and Attribution.

The key point here is that any ‘new’ channels you create will be attributed correctly in all the reports within Google Analytics.

Clearly, this is a good thing!

The concept of tracking your campaigns and using UTM codes is simple. However, as you probably have now come to realize, it is very, very easy to end up with an Acquisition report filled with data that is a jumble of errors and confusion.

Sources and Mediums mixed up, teams not tagging things, people making up Mediums - all of these things happen. The result is an Acquisition report that can quickly end up with your website visitors being attributed to the wrong channels.

The result of lousy tagging? Well, you have incorrect data, to back up your budget and marketing resources. In short, you’d be making the wrong choices.

So what can you do about it?

You need to be strategic and make a big fuss to anyone responsible for marketing campaigns, so that they fully understand how important tracking is, and of course, doing it the right way.

A strategic channel planning process will make sure your marketing effort is allotted correctly. Everybody wins, tell them so.

Start with getting everyone in the company up to speed on the importance of UTM tracking and how it works. Bring anyone who is responsible for deploying your marketing campaigns into the conversation and process. Your staff, any agencies, freelancers, consultants, everyone.

• For your internal staff, make it clear that this is a core competency, and how important this skill is

• For your external support, agencies and freelancers, consider baking this into a service level agreement so they are also on the same page and held to account if they move outside your agreed channel planning process

Get a feel for how you are currently tracking your campaigns. You’ll likely have a gut feeling about how things are going already.

Or, you have questions about how well certain Channels are doing in terms of generating visits and sales. For example, you may have spent money on paid social campaigns, but you don’t know if it’s working for you or not.

Well, if it was never tagged properly, it would be squashed up with your standard social traffic. You may never know.

Another example, you have spent time and money on a new email campaign, and again if those links are not tagged then your email channel looks like it is not doing its job as the data went to direct or referral.

To dig into this a little bit more, investigate your own analytics state of play by heading over to your Acquisition report and add a Secondary Dimension.

Type in source/medium. You will then get a table with the Channel Grouping and alongside it, the Source (where the link lives) and the Medium (big broad buckets for your channels). This may show some gremlins in your tagging!

Once you have an idea of where you are in terms of your tagging, and who needs to be involved, work through your channel planning process.

Start by listing ALL the marketing channels that you are currently using in your company.

From this list, which channels are included in the Default Channel Grouping.

Next, make a note of anything in that list that is NOT included in the Default Channel Grouping. They may make good additions to your User Defined Grouping.

Agree and work out your Mediums, and Sources. You don’t want to fragment your data, so agree company wide what you are going to call your Sources. Pay particular attention to your email Sources, and social media Sources.

If, through this process, you need to create your own User Defined Channels, agree on the name of the channel and the Medium rules for them.

Use the Channel Planning Templates provided with this module and formally write down what you have agreed. Hold people to it.

Reminder here, create Channel Groupings in test view, then when you are happy with it, create in the reporting views

Create a Multi-Channel Funnel (MCF) Grouping so you can see the assisted conversions.

Keep a record e.g. spread-sheet, of any UTM tags you create. Our Template can help you do just that. In fact, let me quickly show you how this Template works.

It’s a nice simple document, but you can use it to base your channel planning process on. Once, of course, you have agreed on your tagging structure and written up your recommendations in your Measurement Plan (tab labeled Channel Planning).

There is another tab called ‘Menu Options’. This is where you will list all the agreed naming conventions for both Sources and Mediums, remember to put in the exact names, case sensitive!

This has personally really helped me, as I am dyslexic, and spelling is not a strength of mine. Also, people can just have days where their brains are tired and they make a tiny error, or they forgot what you agreed to call something. By listing it all in this tab, it feeds the dropdown options in the third tab - named ‘Campaign Code Creator.’

As you can see here, the dropdown function reduces errors in fragmenting data, and it keeps a record of everything. You can, of course, use the Google URL builder, but remember that it doesn't record your UTM codes, or hold the rules that you define. You would need to copy and paste the UTM code into a recorded document of your choice. Or just use ours.

Now you know how to track your marketing channels like a champ, we will move on to the next module focused on tracking just what your users are doing on your website. See you there.

Investigate your current Acquisition tracking process for your company.

Work through the Channel Planning Process using our template

Write up any formal recommendations in your Measurement Plan.

These are of course optional - but they add a different take, even more depth, or just a fascinating look at how the other half live

Take this quiz to check that you've understood the Module!

Let’s quickly recap what you get with Google Analytics, and while we are at it, refresh your mind on our previous modules.

Audience: Who goes to your website?

Your analytics house is set up and you have turned on all the toggles to max out the insights you can get in your reports. User metrics turned on, demographics and interest reports should be pulled in, and filters are keeping your numbers where they should be.

Acquisition: How did they get there?

From our previous module, you know how to get your campaign tracking in order. Every marketing channel and campaign is tagged and bagged so it is correctly attributed.

Behavior: What did they do when they are on your website?

You are using content groupings to get a better view of which sections of your website are getting some reading love. Those of you with a site search function have set this up and you’re getting all that lovely information in your reports. Not forgetting the joy of using filters to make your reports readable and avoiding fragmenting your page data.

Conversion: Does your business model work? Are you still in a job?

We will deep dive on this in the next module, but we touched on it in our View setting deep dive. Do you have goals set up? Are you looking healthy?

Well people, there could be more to your behavior reports. If you so wished.

Now you could just leave your GA setup as it is. You can report on who goes to your site, how they got there, if they converted and which pages they looked at.

Whilst it's great to understand which pages people are looking at on your website, you really want to know what people are doing on your website, and for that, you need to set up Event Tracking.

Let’s take an a-typical webpage. Without Event Tracking, you wouldn't know a number of things - like:

• Who scrolled down to the bottom of the page? To what extent?

• Who shared content? And which platform was most popular to share that content?

• Who started to fill out the form? But, maybe didn’t complete it?

• Did anyone submit the form?

• Did anyone click on the phone number, when on a mobile device?

• Did anyone check out your social media profiles?

• Who clicked through the image carousel?

• Does anyone click on the mailto: email@?

• Who clicked through your tabbed content?

• Did anyone play the video?

When you have Event Tracking setup on your GA account, it will live in the Behavior>Events report.

As part of your Audit and Measurement Plan, you want to investigate if you have Event Tracking in place. Just so you can kick this process off.

Obviously, if you head over to the Event reports and there’s nothing there, well you don’t have it set up. Even if you do have something in this report, don’t assume that it’s correct or that you’re tracking everything that you should be tracking.

So, you're probably thinking that this all sounds great, how do you get this data into your Google Analytics account? Well dear student, let’s look at that in the next lesson!

You want that data, don’t you? Yep, we don’t blame you, we will convince you by the end of this module that it is not a ‘nice to have’. For a lot of you, getting Event Tracking inside your account is going to be quite vital.

You need to use Google Tag Manager to fire event data into your Google Analytics Property. We have mentioned this product before. But a little bit more on it now.

Google Tag Manager allows you to send ‘tags’. Think of them as like name tags, they carry information. Useful information.

Tags are sent based on ‘triggers’ that you define. An example of a trigger could be when a video is played, or a form is submitted (without a thankyou/confirmation page).

You used to have to manually tag each page with event data. Having been through the process of doing it the ‘old way’ you should thank your stars that GTM was created. Instead of tagging each individual page with tags and triggers, you can set up events in GTM that can work sitewide. So you set it up once, and watch the data roll in so to speak.

A little bit like our Tracking module where you have a hierarchy, Default Channel Groupings> Mediums> Sources. You have a similar pattern with Event Tracking by way of; Category, Action, and Label.

Let’s work through each - so they are clear in your head.

Category: Think of these as big broad buckets for you to organize your events into. For example Category= Chicken Bucket

Action: This describes the ‘doing’, so what is the action that we are tracking associated with the Category. For example, Action = Eating Fried Chicken

Label: Is used to further describe the doing, and the extent to which your users are doing something, in relation to the Action. For example. Label = Chicken Thigh with Hot Sauce. It’s essentially a name.

Value: There is an optional parameter too, it’s called Value. This could be set to either a time, or monetary value. For example, we could use the Value parameter to set the cost for our chicken thigh. Value = $1.50. Or set the Value based on how long it took someone to eat it e.g. Value = 60 seconds.

Now for an example that doesn’t involve food.

How far do people scroll down on your website pages, and to what extent? You could have a Category called Scroll Reach, the Action is the doing of said Category, so ‘scrolled page’ would work. And the Label which further describes the doing, 25%, 50%, 75%, 100%. The extent to which the action is happening.

Now, imagine you have lots of videos on your website, and you want to know which ones are being played, which one is the most popular, how far do people watch the video, that sort of thing.

You would create a Category called Video. The Action, for this Category, and remember this is the doing, so it would be something like, played video 25%, played video 50%. And the Label is to describe the doing, so you would label the name of the video for example ‘Company Showreel’ or ‘How to eat chicken’.

Getting your Category Action and Label naming convention is really important. This is our job, as marketers. Do not expect a development team or agency to know how you would like to name your Events. We are the ones that need to work out what we want, what it should be called, and when the data should fire.

Here is an example I have seen more than once, for an e-commerce company, who told me that their Event Tracking had been ‘done’ and it is working correctly.

They had ONE category. Which, in their defense, was helpfully called ‘Ecommerce’.

The Action for the Category was Interaction or Non-interaction. Ok... so click on the labels for the interactions.

‘Not-Set’- yep, that's correct. Every time a user watched a video of the products, added to the basket, signed up to the newsletter, clicked through the images, all of that data was ALL labeled as ‘not-set’. Not so helpful.

How can this happen? In truth, for similar reasons that we’ve talked about before. There was zero documentation in terms of briefing in what they wanted. Development didn't know what marketing wanted to call things, so they just left it to not-set.

Another issue that could have been solved by having documentation for your Events, is good old agreement. Using the same name for a different action, and/or just changing it from lower case to upper case.

For example, this company had two actions with the same name. One called ‘click’ and the other called ‘Click’ with a big C. Big Mistake.

The action for our ‘Click’ with a big Capital C was assigned to 10 different Categories.

Which meant it caused confusion when they were using the Event Data - they could’nt tell which name meant what, or why, and what to do. Which brings me nicely to our next lesson, what you can do with all this information!

Event data is cool, and for a lot of you, absolutely vital. That is down to the use cases for Event Tracking.

Let’s start with the big ones.

Goals.

As in conversions. As in, lines-in-the-sand-did-I-make-any-money and what marketing and content actually helped land the sale?

Some of the Goal types, which we touched on in our View Admin deep dive are:

Destination - A specific page loads

Duration - Spent a specific amount of time

Pages/Screens - visited a specific number of pages

And, drumroll please... Event Goals.

Event Goals are where an action as an event is triggered - and fed into your goal reports, because it was a particularly important Event.

Now, this is why it is vital to have the data inside your account and worth the resources to get it set up in the first place.

Google Analytics is a computer program. A program, that based on your configuration, which includes firing Tags and Triggers via Google Tag Manager to your property, will process your data.

Which you can then report on, and with that, build Goals.

Let’s say you have a contact form on your website, but the way your website is built means there is no ‘thank-you-page’. Users just fill in their details, hit the ‘submit’ button and the pages pretty much stay the same. But, you may add a little note to let the user know the form has indeed been sent.

If it’s important for you to track this as a conversion, then you can only create the Event Goal if the data is inside your Google Analytics Behavior Reports.

Now, you can go over to your little email service provider (ESP) or whatever system you have that receives the contact form information. And you can report to your boss and say ‘Hey, 10 people filled out the contact form this week’.

However you will have, no idea, zero, nothing, blanks all round - as to which marketing campaigns can actually take credit for those filled forms, and even less the conversions that might follow.

Segments.

Imagine your data as an Orange. You can segment your data, which is like taking a segment of your orange. However, each segment is different from the next, as you decide which data you want to zoom in on, which segment you want to eat. Women in South Africa, Men who use iPhones - that kind of thing.

Say you have invested in loads of videos on your website. You know they help drive conversions, and you have to justify your budget on the videos, so you can have more money for the next marketing cycle.

Now, you have all watched those TV programmes where startups ask rich people for money, for their business. You will also know that they love to know the details and facts, no warm fuzzy feelings. If you tried to report to the board, your boss, whomever and said “I would like some more money for videos because I think they help convert but I have no proof’ is a hard ask. Actually, I’ll answer that - it’s a no.

Now, imagine you have Event Tracking set up for your videos. You could create a segment where you only see people who have played a video. You could dive into that juicy data pot and see if people who watch the video spend more money than those who don't? Or you could see which video was the most popular. Or which demographics preferred the videos, and use that to tinker with your audience based marketing tactics.

Remarketing Lists

If you have linked your Google Ads account to your Property, and ticked the correct toggles, if you can create a segment, you can create remarketing lists.

Imagine building a segment for people who visited your website, who then scrolled down to the bottom of the page.

Tabbed through the content, watched the product video, added to the basket but didn't convert. You could create a segment and turn that audience into a Remarketing list to nudge people who very nearly converted back to your website. More on how to do this in the Segment module coming up.

Custom Dashboard

Lastly, you can add this extra data into your dashboard to show how users flow through your website, in terms of the actions, that form their customer journey. Or, to dive into specifics of a particular Category. For example, we have a specific data studio report on our content that you can download.

So, you get the idea that Event tracking is cool, and you actually really need it in your account to do things like, create Goals, Segments and report on what people are actually doing on your website.

But, what should you have on your website?

Good question. Now, it will vary from business to business, and website to website, but thankfully there’s a process that we have used for all of our Google Analytics audits and measurement plans in the past, which we are going to share.

Event State of Play

Firstly, have a look at your Events> Behavior report. What’s in there? Anything at all? Or has someone done some event tracking in the past?

Work through the Category> Action> Label and check if you have any mistakes e.g. naming conventions that got muddled up? Remember our (not-set) example? And the Click/click example?

It may be handy to export what you have by using the Export feature and look at the data in Google Sheets, Excel or CSV file.

Make a note of anything that is out of sorts and needs editing. Documentation is your friend.

Work Through Key Pages

To identify the types of Events you want to track, you need to work through your Homepage and then your “Money Pages”.

Money pages being the key pages of your website, that are pertinent to you being successful. For an eCommerce site, that could be the pages with the product on them, and then check out page. For lead gen, the pages where people access content and fill out forms that build your database of marketing qualified leads.

Now, sit in a room, on your own, or with your team members and work through the homepage and money pages listing all the things Google Analytics will not track by default. As a reminder, GA will fire data that a web page was viewed, how many users, sessions, and how well it converts. But beyond that, you don’t get anything else really.

Let’s work through a hypothetical example for a website. Starting with the homepage. What could our users be interacting with on this webpage that Google Analytics will not track by default?

• There is an image carousel that can be tabbed through by a user

• A video that can be played

• A form to submit (but there is no thank you page)

• Tabbed content

• How many people scroll down the page?

• A telephone number that could be clicked, on a mobile device

• A social media icon that goes to the business social presence

Then moving to one of the ‘money pages’, and again, what could our users be interacting with that Google Analytics will not track by default?

• There’s an option to click through the product images

• A link to read reviews (on a 3rd party website which GA won’t track)

• An option to select the type of product from a dropdown

• Add addition items with radio buttons

• Add to basket

• A live chat box that users can interact with and talk to the company

Arrange your findings into your Categories, Actions, and Labels

When we do this activity, we like to use post-it notes, as you may end up editing and changing the names as you gradually add to the list and further define your Category, Action and Label names. Pulling some examples from our list.

• A telephone number that could be clicked on a mobile device

You may start with:

Category = Telephone Number

Action = Clicked Telephone Number

Label = 012 345 67 89

But, if you dig around on your site when you do this activity, and find that you also have email addresses that people can click on, and a contact form.

So, you may find that you need to edit and change the Category to include more Actions, that still fit into that theme of Categories. So it may look like this.

Category = Contact Us

Action = Telephone Number Clicked

Action = mailto@ Clicked

Action = Form Submitted

Label = 012 345 67 89

Label = info@companyname.com

Label = General Enquiry Form

This is why post-it notes are your friend, when you do this activity, they are flexible enough that you can flex collaboratively without commitment. Pro tip, we have found it useful to use one color for Category, one for Action and a different one for Labels. Mapping it out this way also stops you from giving the same name to another event. For example, not using an Action name that has been given to a different category. It’s a little bit like card sorting in User Experience Design.

Arrange To The Funnel

Once you have brainstormed and mapped out what you could track, and gave everything a name. Arrange all of your Events to match your funnel. We like to do this by thinking about what the typical customer journey may look like.

For example...

Category

• Scroll: to track people who dared to move the mouse or thumb down your page

• CTA: to track specific call to actions dotted on the page

• Social Share: do people care enough to share our page with their social network

• Newsletter Sign Up: do they signup to our newsletter?

• Product Pages: Did they start to check out our goods?

• Shopping Bag: How far do they get on that shopping cart page?

List It All In A Centralized Document

We like putting our final events into an Excel doc, but you can use whatever you feel comfortable with. If you want to put this in a text doc, go for it. Whatever makes you happy.

Now, you may find that you have a rather long list - which can be a bit daunting. Just to help you manage expectations for this task. When I have done this myself, for a standard website, it would take me around up to 8 hours to complete this whole mapping process. Once it is done, and those Events are firing into your account, you only need to revisit this document when you update your website, as you may need to edit or add new Events to your account.

The last point here, highlight any of the Events that you believe will be so important as to be promoted to Goals for your website, or key actions that are needed to report on the success of your business model, aka your key performance indicators.

Don’t email dev, or your agency and say ‘Hi, I would like event tracking please’. You need a clear brief. As with pretty much everything else in life - you get what you ask for.

In your measurement plan you are going to write up your current state of play. What is your current Event Tracking setup at the moment?

You either have nothing, so obviously you want to have it, or, there are some events but they need some tweaking to make them more useful, like changing the names, or adding new events to the list.

A good start, is to highlight the benefit to the company and website. This is where you state that the resources needed will give you data to build goals, create segments, and remarketing lists. You will be able to dive deeper into the behavior of your website. Flag any UX issues with the design, and create bespoke reports. Maybe even making more money in the process.

Then, you reference your Event Tracking Briefing document. Which is the final, typed up document you put together based on working through your Homepage and Money Pages. We recommend, as we said before, mapping them out to the funnel so you can reflect the customer journey, so to speak. Stakeholders more easily relate to this - and it’s definitely the smart approach.

Now, you may end up with quite a long list. For this module we have provided you with two templates. These templates are a sample of the types of Events for an a-typical ecommerce, and lead gen site - which you can use to help guide your own plan.

Our advice, in addition to providing a long list of Categories, Actions and Labels, is to also add some extra columns to describe them - so it’s crystal clear to any who might look.

Start with ‘notes’ - this is where you write in plain english, what you are looking for. Adding in any notes that will help the person who is going to tag all of this for you from an implementation perspective. For example. Video plays, you can write ‘please fire an event when the video is played by a user’ and then make a note of a specific video. Or, for Social Media links ‘please fire when someone clicks on our Facebook page link which is {x}’. Make it foolproof.

RAG

Traffic light which events you want the team to start with. Do you want them to just start from the top and work down? Or, do you need them to start with Contact forms first, because you need that to build goals. So colour code your Event doc in relation to degrees of urgency.

Red= Really, really, need these implement 1st - as a priority

Amber= Can you build these next, they are important

Green= These need to be done, but are not as urgent as the others

Non-Interaction - True or False

OK, that seems straightforward, but there is also a super confusing (but very useful) part of Event Tracking.

I’ll start with explaining the concept of the Bounce rate as this is where the Non-Interaction element, set to True or False, can impact the metric - as well as the session data.

What is a bounce? A bounce is where a visitor has visited your website, whatever page they landed on, and they didn’t go to any other page on your website. Or, if they clicked on a 3rd party link, like your social media pages, or a booking platform, that kind of thing. When this happens, Google Analytics will create the metric for bounce.

So. you could have a page where a user reads some kick ass copy, and completes a form, or signs up for something, or goes off to another platform to buy. Now you could end up with say, a bounce rate of 90%, some people will look at this and pull their hair out, shout at you and say the page is rubbish. It’s not.

Context matters here people. If a user has completed their desired task, then all is well with the world.

So, you could have a user looking for an answer, and they find your blog post. They read it, all the way to the bottom (because you have scroll reach setup as an Event). You can now balance the reports with more context.

However, if you want, you can use an Event to tell Google Analytics to treat it as if they went to another page on your site, and therefore it will impact your bounce rate. Usually it will go down.

But you don’t want to do this to all of your Events, otherwise you will have a bounce rate of 0% and inflated sessions. That would be a bit useless.

If you set the Event to False you are saying “hey Google, I want you to consider this as an interactive hit, I know they didn’t go to another page, but treat it as if they did.”

For example. You could set up Events that represent a few things; submitting a form, buying something, or making a payment - setting them as Non-Interaction = False.

You are literally saying that the statement ‘Non-Interaction’ is wrong, it is false, you want it to be treated as an interaction.

Events that are set as Non-Interaction = True are for things like scrolling your page, or auto play videos, actually all of your events (excluding maybe the important ones that you want to be counted as an interaction).

You are agreeing with the statement, it is correct, it is true, these are non-interactions. You record the data, but you are saying to analytics ‘Nothing to see here, move along’. This stops misleading data and errors in session counts.

We saw an account that had the Scroll category set to False, which meant that as soon as the code tag and trigger fired, Google counted it as if it was another website page, so their bounce rate went down to 0% and their session data was inflated. So yeah, it can be important to get this right.

As a general rule of thumb. The events that are set as Non-Interaction = False are the big conversion goals you want to create. Like form completion, or payment made.

If in doubt, talk to your development team about your options.

Implemented

Lastly, have some way of communicating when the Events have been done. Either by ticking that part of the document to say,”yes we have implemented this set of Events” or link it all up with your own internal project management systems. Please treat it as important.

And the last point, Event Tracking does need some resource, which could be time from your dev team, budget to hire a consultant or agency to build them - whatever. Depending on the size of your website, you could be looking at a day's work, or a good solid week!

Make the most of this feature by working through our process, have a centralized document and written recommendations in your measurement plan. Making sure you update this document when you make significant updates to your website is really pivotal.

Lastly, highlighting the benefit to the business. Which is, without Event Tracking, you cannot build goals and get conversion rates, you can’t segment your data further, you don’t know what people are actually doing on your website.

You are not a mindreader!

Audit your current Event Tracking state of play. Navigate to behavior> Events and investigate what you are tracking, and what the current label system is for your website. Export as excel, csv, or Google doc if needed.

For any new Events, work through your Homepage and Money pages and log anything that GA will not track by default. Group these interactions into themes and build your Category, Action, Label hierarchy.

Use our templates as a guide to help map to the funnel, and brief the development team.

These are of course optional - but they add a different take, even more depth, or just a fascinating look at how the other half live

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