Google Analytics Data Mining with R
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This document summarizes a webinar about analyzing Google Analytics data with R. The webinar covered an introduction to R, why use R for Google Analytics data, getting started with R and the Google Analytics API, and provided three examples of real-life applications including predicting product revenue, assessing marketing campaign value over time, and creating visualizations with ggplot2. Speakers included Kushan Shah from Tatvic and Andy Granowitz from Google Analytics.
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Google Analytics Data Mining with R
- 1. #tatvicwebinar A GACP and GTMCP company 1/28/2015 1 #tatvicwebinar1/28/2015 1 #tatvicwebinar Google Analytics Data Mining with R (includes 3 Real Applications) Jan 28th, 2015 FREE Webinar by
- 2. #tatvicwebinar A GACP and GTMCP company 1/28/2015 2 #tatvicwebinar1/28/2015 2 #tatvicwebinar Our Speakers Kushan Shah Maintainer of RGoogleAnalytics Library & Web Analyst at Tatvic @ kushan_s Andy Granowitz Developer Advocate, Google Analytics (Google) @ agrano
- 3. #tatvicwebinar A GACP and GTMCP company 1/28/2015 3 #tatvicwebinar Outline An Introduction to R Why analyze Google Analytics data with R Getting started with R & Google Analytics Questions & Answers 3 Real Life Applications & Use Cases
- 4. #tatvicwebinar A GACP and GTMCP company 1/28/2015 4 #tatvicwebinar An Introduction to R • Open source statistical computing language, widely used by organizations to solve business problems
- 5. #tatvicwebinar A GACP and GTMCP company 1/28/2015 5 #tatvicwebinar An Introduction to R • Open source statistical computing language, widely used by organizations to solve business problems Data Analysis Statistical Tests Data Visualization Predictive Models Forecasting R
- 6. #tatvicwebinar A GACP and GTMCP company 1/28/2015 6 #tatvicwebinar Why Use R Easy to integrate with various data sources Data Frame – Analogous to Excel Spreadsheet or MySQL Table 6000 Pre developed packages for various applications No software licensing costs Enables reproducible analysis
- 7. #tatvicwebinar A GACP and GTMCP company 1/28/2015 7 #tatvicwebinar Outline of this Webinar An Introduction to R Why analyze Google Analytics data with R Getting started with R & Google Analytics Questions & Answers 3 Real Life Applications & Use Cases
- 8. #tatvicwebinar A GACP and GTMCP company 1/28/2015 8 #tatvicwebinar Why analyze Google Analytics data with R ● Google Analytics API allows data extraction for custom reports • Reports with up to 7 Dimensions and 10 Metrics • API is well suited for batch data extraction • API has techniques for handling large queries (10K - 1M records and beyond) ● RGoogleAnalytics = R Wrapper over the Google Analytics API • Provides functions to easily interact with the Google Analytics API • Takes care of the low level plumbing ● Google Analytics Premium User and data exported to Big Query • Use the bigrquery package by Prof. Hadley Wickham
- 9. #tatvicwebinar A GACP and GTMCP company 1/28/2015 9 #tatvicwebinar Outline of this Webinar An Introduction to R Why analyze Google Analytics data with R Getting started with R & Google Analytics Questions & Answers 3 Real Life Applications & Use Cases
- 10. #tatvicwebinar A GACP and GTMCP company 1/28/2015 10 #tatvicwebinar Getting Started with R and Google Analytics ● Install R - http://www.r-project.org/ ● Install RStudio - GUI for R (Optional) ● Install RGoogleAnalytics Check out the blogpost for a step by step walkthrough - bit.ly/18oJjqA
- 11. #tatvicwebinar A GACP and GTMCP company 1/28/2015 11 #tatvicwebinar Getting Started with R and Google Analytics One Time Setup ● Create a Project in the Google Dev Console ● Activate the Google Analytics API for your project ● Get your Project’s Client ID and Client Secret https://developers.google.com/analytics/devguides/reporting/core/v3/gdataAuthorization
- 12. #tatvicwebinar A GACP and GTMCP company 1/28/2015 12 #tatvicwebinar Outline of this Webinar An Introduction to R Why analyze Google Analytics data with R Getting started with R & Google Analytics Questions & Answers 3 Real Life Applications & Use Cases
- 13. #tatvicwebinar A GACP and GTMCP company 1/28/2015 13 #tatvicwebinar Examples ● Example 1: Forecast Product Revenue for an eCommerce Store ● Example 2: Assess the long term value of your Marketing Campaigns ● Example 3: Web Analytics Visualization with ggplot2
- 14. #tatvicwebinar A GACP and GTMCP company 1/28/2015 14 #tatvicwebinar Example 1: Predict Product Revenue with R ● Get Product Revenue as Time Series (historical data) ● Forecast Product Revenue for the next quarter Check out the blogpost for a complete walkthrough - http://bit.ly/1y3dmtI
- 15. #tatvicwebinar A GACP and GTMCP company 1/28/2015 15 #tatvicwebinar Example 1: Predict Product Revenue with R Time Series Components
- 16. #tatvicwebinar A GACP and GTMCP company 1/28/2015 16 #tatvicwebinar Example 2: Long Term Value of Your Marketing Campaigns Check out the blogpost for a complete walkthrough - http://bit.ly/1zpjbYA
- 17. #tatvicwebinar A GACP and GTMCP company 1/28/2015 17 #tatvicwebinar Example 2: Long Term Value of Your Marketing Campaigns
- 18. #tatvicwebinar A GACP and GTMCP company 1/28/2015 18 #tatvicwebinar Query New Customers Acquired via a Given Campaign query.list <- Init(start.date = "2014-11-01", end.date = "2014-12-20", dimensions = "ga:date", metrics = "ga:transactions,ga:transactionRevenue", segment = "users::sequence:: ^ga:userType==New Visitor; dateOfSession<>2014-11-01_2014-11-07; ga:campaign==Campaign A; ->>perSession::ga:transactions>0", sort = "ga:date", table.id = tableId) Example 2: Long Term Value of Your Marketing Campaigns
- 19. #tatvicwebinar A GACP and GTMCP company 1/28/2015 19 #tatvicwebinar Example 2: Long Term Value of Your Marketing Campaigns Segments Explained • The segment selects users:: in order to include not only the sessions that match the conditions, but all sessions among users who match the conditions. • The sequence:: prefix selects a set of users that completed a specified set of steps • Step #1 - Visit from a given campaign in a given set of time • Step #2 - Make a purchase • The ^ prefix in front of ga:userType==New Visitor;dateOfSession<>2014-11-01_2014- 11-07;ga:campaign==Campaign A ensures that the Date of Session, Campaign, and User Type conditions are true for the first hit of the first session in the given date range. • ->>perSession::ga:transactions > 0 specifies the second step of making a purchase at some point.
- 20. #tatvicwebinar A GACP and GTMCP company 1/28/2015 20 #tatvicwebinar Example 2: Long Term Value of Your Marketing Campaigns • head(campaign_a_df) • cumulativeTransactions <- cumsum(campaign_a_df$transactions)
- 21. #tatvicwebinar A GACP and GTMCP company 1/28/2015 21 #tatvicwebinar Example 2: Long Term Value of Your Marketing Campaigns Use the data to Generate a Cumulative Transactions Plot
- 22. #tatvicwebinar A GACP and GTMCP company 1/28/2015 22 #tatvicwebinar Example 3: Web Analytics visualization with ggplot2 Background • gg – Grammar of Graphics (Wilkinson, 2005) • R Implementation by Prof. Hadley Wickham • Sophisticated graphs in a *few lines of R code * Learning Curve
- 23. #tatvicwebinar A GACP and GTMCP company 1/28/2015 23 #tatvicwebinar Example 3: Web Analytics visualization with ggplot2 ggplot(data = ga.data) + geom_line(aes(x = date, y = itemRevenue) Check out the blogpost for a complete walkthrough - http://bit.ly/15Iaaf7
- 24. #tatvicwebinar A GACP and GTMCP company 1/28/2015 24 #tatvicwebinar Example 3: Web Analytics visualization with ggplot2 Decomposing the syntax • Create the ggplot object and populate it with data • ggplot(ga.data) • Add Layers(s) • geom_line(aes(x=date, y=itemRevenue)) • Other geoms – bar, point, line, histogram • Aesthetics describe how variables are mapped to visual properties of geoms • Additional Plotting Options -> Plot title, Axis Titles, Axis Text Formatting, Legends
- 25. #tatvicwebinar A GACP and GTMCP company 1/28/2015 25 #tatvicwebinar Best Practices • Become familiar with the Google Analytics API Naming Conventions – Dimension/Metric names are in camelCase • Know the permissible Dimension Metric Combinations – https://developers.google.com/analytics/devguides/reporting/core/dims mets • Use the Query Feed Explorer to test queries before running them in R – https://ga-dev-tools.appspot.com/explorer/ • Post issues at https://github.com/Tatvic/RGoogleAnalytics/issues • Questions at Google Analytics Reporting API Forum
- 26. #tatvicwebinar A GACP and GTMCP company 1/28/2015 26 #tatvicwebinar Further Resources • http://bit.ly/r-googleanalytics-resources • Watch the full R Google Analytics Webinar - http://bit.ly/1KrHXtH
- 27. #tatvicwebinar A GACP and GTMCP company 1/28/2015 27 #tatvicwebinar Outline of this Webinar An Introduction to R Why analyze Google Analytics data with R Getting started with R & Google Analytics Questions & Answers 3 Real Life Applications & Use Cases
- 28. #tatvicwebinar A GACP and GTMCP company 1/28/2015 28 #tatvicwebinar Next Webinar Webinar: Everything You Need to Know about GTM V2 When: Feb 18th 10:00 AM PDT Guest Speaker Phil Pearce (Web Analyst/ PPC/ SEO Expert) You will learn: • How to Upgrade to GTM V2 • Mistakes to Avoid while Upgrading • A Quick Checklist for Upgrading to GTM V2 And much more… Register Here - http://bit.ly/gtm-v2-webinar
- 29. #tatvicwebinar A GACP and GTMCP company 1/28/2015 29 #tatvicwebinar Kushan Shah Twitter: @kushan_s Thank You! Andy Granowitz Twitter: @agrano
Editor's Notes
- Very often we analyze how campaigns perform directly for us. Someone visits via a campaign, and makes a purchase. This is good analysis, but often leaves money on the table. What happens to these visitors the subsequent times they visit? Especially if they are first time visitors - customer acquisitions. Perhaps some campaigns are slower to convert, or lead to more loyal customers over time.
- What we want is a cumulative graph of the campaign’s performance over time, so we can see the total value generated by the campaign. Let’s dig into how to do this.