R is a popular choice of tool for analysts, offering a large variety of libraries pertaining to each and every task in data analysis. With practical projects based on various real-world domains and use-cases where web analytics can be used, this video will be your companion for implementing the various web analytics techniques using the free, open source libraries provided by R.
This video will start by understanding the basics of web analytics, and why it is used in businesses worldwide. This will be followed by an introduction to R and its libraries, and understanding why R is a great choice for performing real-time analysis of your data. Analyse your website’s traffic and understand customers’ behaviour in real time, and use this information to optimize the performance of your website. You will also learn how to use the analytical capabilities of R to fully explore your Google Analytics Data and generate meaningful visualizations of your data using libraries like ggplot2 and generate reports based on various metrics and combinations. By the end of this tutorial, you will have a solid understanding of implementing the various web analytics techniques in R, and maximize your website’s performance.
About the author
William Shin received his PhD from Columbia University in 2017 in biological sciences with specialization in computational biology. He has been an avid user of R since 2009 and has been using statistics to gain insights into large datasets since 2007. He has been a consistent contributor in digital analytics, a frequent speaker at conferences, and a wide range of regional events around the world.
What are insights I would be able to gain with Web Analytics that I would not be able to gain from traditional methods?
Why is Google Analytics the most effective way to add web analytics functionality to our site?
What is R and why should I use it along with Google Analytics?
How do I set-up R and RStudio on my system?
How do I sign-up for Google Analytics and add it to my website?
How can R be used to access data from my Google Analytics account?
What is the simplest and most effective way to generate beautiful plots in R?
Where can I learn more about GoogleAnalyticsR and ggplot2, as well as the Google API?
What are the benefits of dashboards, and how can I generate them easily in R?
How does Google track visitors and visits to our website?
How does Google track new and returning visitors to our site, and what are some caveats to understanding the metric?
How can we understand and track Visitor Loyalty?
How can our dashboard help us understand visitors, their return rates, and loyalty?
What is the difference between Exit and Bounce Rates, and why do they matter?
How can we use R to extract and plot pages along with their Exit and Bounce Rates?
How can our dashboard help us identify pages with high exit and bounce rates?
What are ways that Bounce Rates can be decreased?
What is the importance of multiple-time frame analysis and what insights can you gain from looking at multiple time-frames?
What is context, and why is it essential for interpreting metrics correctly? What will you miss if you ignore context?
How has my website been performing in the long-term?
How can our dashboard help us understand the long-term performance of our site?
What can numbers tell you? What can they not tell you?
Why is multiple time-frame analysis so important?
Are there situations where “too much” analysis can occur? What are the pitfalls of too much analysis?
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