A complete journey to web analytics using R tool

Name: A complete journey to web analytics using R tool
Rating: 3.8 (22 reviews)

Analyze your website behavior using R tool

Created byElementary Learners

Last updated 1/2019

English

What you'll learn

understand performance indicators for business functions
Understand what kind of reports and analysis can be done and how can you interpret the business outcomes

Course content

10 sections • 61 lectures • 3h 58m total length

1.1 Web analytics Introduction4:13
Explore web analytics with R and Google Analytics to understand, evaluate, and improve your site and marketing. Learn how quantitative internet data and qualitative insights reveal visitor behavior and value.
1.2 What you should know1:12
1.3 Who should go for this course1:03
1.4 Intro to Tool that is to be used1:36
1.5 How this course will help3:50

2.1 Why Web Analytics3:56
2.2 What is pre, post and onsite visitors3:22
2.3 Questions to consider4:26
2.4 Some insights that we can get from Web Analytics3:00
Identify web analytics insights by analyzing traffic sources and visitor intent (awareness, comparison, purchase) to reveal who visits, what they seek, and how to improve the site.
2.5 Why is it useful for businesses3:47
2.6 Who uses Web Analytics3:00
2.7 Metrics for Web Analytics Report3:50
2.8 Why invest in Web Analytics1:53
2.9 Setup a web analytics tracking system1:45
2.10 Discussion on E-commerce and Non-Ecommerce data3:21
Explore the use of web analytics for both e-commerce and content-driven sites, measuring visits, engagement, and content interaction to bridge visitor expectations and improve performance.

3.1 How data collection works4:41
3.2 How you can start with your account4:18
Create a five-page site on WordPress or Blogger, sign up for Google Analytics with your Gmail ID, and insert the tracking ID on all pages to start analytics.
3.3 Understanding data reporting2:48
Understand how web analytics reporting uses dimensions and metrics to describe site visits, with predefined or custom templates organizing mediums and key metrics.
3.4 Understanding Web analytics framework and KPIs14:02
3.5 Choosing a right web analytics tool5:11
3.6 Web Analytics and Business Organizations0:54
3.7 Stakeholders and Expectations2:22
Contrast the brand manager's marketing perspective with analytics to align stakeholders' expectations with business goals. Bridge analytics to business indicators by visualizing website engagement and campaign metrics toward targets.
3.8 Reporting to stakeholder's need4:43
Identify brand engagement using organic and direct website visits, compute a brand engagement index, and report KPI trends to stakeholders across four quarterly periods.
3.9 Understnding Business Strategy4:15

4.1 Understanding origin of R and Rstudio3:28
4.2 Advantages of using R in Web Analytics5:38
4.3 Introduction to R Interface5:16
Explore the commander interface, the console and prompt, and learn the assignment operator, variable assignment, script creation, and package installation.
4.4 Introduction to Rstudio Interface3:10
Explore the RStudio interface as an integrated development environment with a console, editor, plotting, history, and workspace management, and learn to run scripts across its four divisions.
4.5 Installation Process of R and Rstudio tool2:43
Learn to install the R language and the RStudio IDE on Windows by following the step-by-step download and installation prompts, enabling you to start web analytics with R.

5.1 Understanding Vectors and variables15:15
5.2 Understanding Dataframe5:44
Create a data frame in R by combining kids and ages, inspect structure with str, and access columns by index, name, or $, showing 3 observations and 2 variables.
5.3 Factors,Subsetting and Summarizing methods8:36
5.4 R help Feature5:31
Discover how to access R's built-in and online help using help(), the question mark, and the double question mark. See examples with example() and explore the sequence function documentation.
5.5 Importing data in r studio3:35

6.1 Intro to R google analytics2:25
6.2 Understanding Dev tools and Github1:28
6.3 Authentication to Google API4:41
6.5 Extracting Data4:01
Authenticate with Google Analytics in R Studio, initialize parameters, and extract website data by building queries with init and get report. Use dimensions and metrics and cap results at 10000.
6.6 Google trends Data Extraction1:58
6.7 Interpreting the results for Decision making1:47

7.1. Understanding & Differentiating new users and7:40
7.2. Hierarchy of visits, visitors and page views3:06
Explore how Google Analytics defines visitors, visits, and page views, including unique visitors, 30-minute sessions, and cookie-based metrics, to analyze site engagement, loyalty, and campaign effects.
7.3. Sorting data by Browser capabilities6:22
7.4. Analyzing data from mobile browsers6:20
7.5. Optimizing Traffic by time of day3:14
Learn to optimize traffic by time of day using Google Analytics data in studio, analyzing sessions, page views, bounce rate, and peak hours to inform ad budgeting and timing.
7.6. Tracking your Marketing6:49
7.7. Understanding Internal Site search behavior5:11
7.8. Measuring Return on Investment (ROI)1:56

9.1 What is Time Series1:08
9.2 How do we use Time Series Data2:15
9.3 Components of Time Series2:24
9.4 Flavors of Time Series3:32
9.5 Steps of Time Series Forecasting in R5:41
9.6 Forecasting using Exponential Smoothing2:17
Explore forecasting with exponential smoothing for time series with trend and no seasonality, including data import, converting to a time series, and using automatic forecast functions.

Requirements

Students should be comfortable with opening a browser, visiting a website and internet usage.
Should have idea about Google Analytics and Google AdWords
Basic knowledge of R would be advantage
If you have knowledge about graphs and charts previously, it would be an added advantage for you

Description

The course "A complete journey to web analytics using R tool" starts with a basic understanding of web analytics moving to the tool used for the same which is The R Studio.It covers all the basic commands used in the R studio starting from variables and vectors and ranging to importing data in R. Further the course details about Google analytics covering topics like authentication to google API,validation and extracting data. Moving ahead it covers the most important concepts of website data analysis which involves website visitor analysis, Tracking of marketing and measuring return on investment. The closing topics include visualization of information and map plotting.

Who this course is for:

everyone including students who want to choose Analytics as their career option, employees of organization, CEOs, Managers, SEOs, Business Analyst, Digital Analyst, Web Analyst, everybody who wants to optimize website performance and gain profits from it.

A complete journey to web analytics using R tool

What you'll learn

Explore related topics

Course content

Introduction to the course5 lectures • 12min

Why Web Analytics10 lectures • 32min

The Web Analytics Framework9 lectures • 43min

Introduction to R Studio5 lectures • 20min

R Studio Basics5 lectures • 39min

Introduction to Google Analytics in R6 lectures • 16min

Analyzing website behavior8 lectures • 41min

Visualization in R5 lectures • 15min

Introduction to Time Series6 lectures • 17min

Further Resources and links2 lectures • 3min

Requirements

Description

Who this course is for: