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How To Get The Most Out Of The Google Analytics API For Non Developers

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30 slides with examples of how to use Excel plugins to download data from Google Analytics and Google Search Console and turn it into actionable data

Published in: Data & Analytics
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How To Get The Most Out Of The Google Analytics API For Non Developers

  1. 1. Twitter: @charlesmeadencharles@digitalnation.co.uk Getting The Most Out The Google Analytics API If You’re Not A Developer Charles Meaden Digital Nation
  2. 2. Twitter: @charlesmeadencharles@digitalnation.co.uk Introduction • Involved in analytics for 22 years • Started off analysing log files, now concentrate mainly on Google Analytics • One of the reasons why we are based in Swansea #Nofilters
  3. 3. Twitter: @charlesmeadencharles@digitalnation.co.uk Who Is This Talk Aimed At? • Anyone who wants to – speed up their reporting – Extract actionable data • Who looks at this… {"reportRequests":[{"viewId":"96284643","dateRanges":[{"startDate":"2018-08- 21","endDate":"2018-09- 19"}],"segments":[],"metrics":[],"dimensions":[],"orderBys":[],"samplingLevel":"L ARGE"}]} • And thinks – what this all mean
  4. 4. Twitter: @charlesmeadencharles@digitalnation.co.uk Why Do We Use the API Save Time Be detectives
  5. 5. Twitter: @charlesmeadencharles@digitalnation.co.uk Quick and Easy Ways to Extract Data API • Google Sheets – free • Supermetrics – paid • Next Analytics - paid • Analytics Edge – paid • This talk uses Analytics Edge, but the principles remain the same
  6. 6. Twitter: @charlesmeadencharles@digitalnation.co.uk Why Analytics Edge • Allows us to pull in data from multiple sources
  7. 7. Twitter: @charlesmeadencharles@digitalnation.co.uk Why Analytics Edge • Allows us to pull in data from multiple sources • Append / compare and combine from multiple sources
  8. 8. Twitter: @charlesmeadencharles@digitalnation.co.uk Why Analytics Edge • Allows us to pull in data from multiple sources • Append / compare and combine from multiple sources • Transform and manipulated the data
  9. 9. Twitter: @charlesmeadencharles@digitalnation.co.uk Two more reasons • The core application, plus the Google Analytics and Google Search Console connectors cost us just £139 per year • The developer Mike Sullivan is outstanding in fixing the very few bugs that have appeared • His Misunderstood Metrics series is well worth checking out – Look on the right hand menu of his web page for the links to all 12 articles
  10. 10. Twitter: @charlesmeadencharles@digitalnation.co.uk Get Data Down Quicker and Faster… • How often do you run the same report time and time again? • How often do you need to wait for this?
  11. 11. Twitter: @charlesmeadencharles@digitalnation.co.uk Landing Page by Medium / Source in Google Analytics • It takes the following 10 steps plus ‘loading time’ to extract data 1. Log in 2. Select property 3. Select Acquisition 4. Select All Traffic 5. Select Source / Medium 6. Select Secondary Dimensions 7. Select the Landing Page dimension 8. Set date range 9. Change show rows 10. Export as CSV • If more than 5000 rows, then select the next page and wait for it to load….
  12. 12. Twitter: @charlesmeadencharles@digitalnation.co.uk In Analytics Edge
  13. 13. Twitter: @charlesmeadencharles@digitalnation.co.uk In Analytics Edge
  14. 14. Twitter: @charlesmeadencharles@digitalnation.co.uk In Analytics Edge
  15. 15. Twitter: @charlesmeadencharles@digitalnation.co.uk As it’s in Excel • Store key variables in cells and call them from the application • Store all the setting in one Excel file • Makes it really easy to change and adapt • Can use all of the Excel formatting and functions • Lot of people still like reports in Excel…
  16. 16. Twitter: @charlesmeadencharles@digitalnation.co.uk You’re Limited Only By Your Imagination • Rather than be constrained by looking at what data the API can pull out • Look at the ideal type of actionable reports you want to build Data Ideal
  17. 17. Twitter: @charlesmeadencharles@digitalnation.co.uk Get Around Sampling
  18. 18. Twitter: @charlesmeadencharles@digitalnation.co.uk Download Over A Million Rows • Had a well known UK retailer with a bounce rate of less than 3% on the home page • That just feels wrong…. • Added Simo Ahava Key Custom Dimensions to capture – Client ID – Session ID – Timestamp • Left it running for a week to collect data • Exported the results as a CSV file
  19. 19. Twitter: @charlesmeadencharles@digitalnation.co.uk Only Grab Certain Results • Find any instance of Personally Identifiable Information • Find all query strings
  20. 20. Twitter: @charlesmeadencharles@digitalnation.co.uk Create Missing Google Analytics Reports • We create a most navigated to pages report • Using Analytics Edge we extract – The page name – Entrances – Page views • Analytics Edge allows you to create a set of macros to step through and transform the data
  21. 21. Twitter: @charlesmeadencharles@digitalnation.co.uk Create Missing Google Analytics Reports • We create a most navigated to pages report • Using Analytics Edge we extract – The page name – Entrances – Page views • Analytics Edge allows you to create a set of macros to step through and transform the data
  22. 22. Twitter: @charlesmeadencharles@digitalnation.co.uk Most Navigated To Reports • Editable 3 step macro to extract, transform and write the data
  23. 23. Twitter: @charlesmeadencharles@digitalnation.co.uk Most Navigated To Reports • Not good that the second most navigated page is a zero search results page!
  24. 24. Twitter: @charlesmeadencharles@digitalnation.co.uk Get Data from Hundreds of Segments • The API supports dynamic segments • Allows you to build segments on the fly • Easy to use taxonomy – sessions::condition:: – sessions::condition::ga:deviceCategory=~desktop; – sessions::condition::ga:deviceCategory=~desktop;ga:medium=~organic; – sessions::condition::ga:deviceCategory=~desktop;ga:medium=~organic;ga:landingPagePath=~/sport swear • Supports regex and a ‘not’ condition – Very handy for trying to deal with horribly complicated URL’s
  25. 25. Twitter: @charlesmeadencharles@digitalnation.co.uk User Funnels • If you’re not blessed with 360, easily create user funnels – users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/categorypage/ – users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/productpage/ – users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/basket/ – users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~/checkout/ – users::conditions::ga:deviceCategory=~desktop;ga:pagePath=~^thankyou$
  26. 26. Twitter: @charlesmeadencharles@digitalnation.co.uk Dashboards • This one has 253 queries • For each site area we grab • Last week, previous week and last year • Sessions, Revenue, Bounce and Ecommerce Conversion Rate • For each device category
  27. 27. Twitter: @charlesmeadencharles@digitalnation.co.uk Merchandising Reports • Two examples of reports that we built to help merchandisers • Simple – Allow the user to select the category page from a drop down list – Extract all the searches carried out on that page – Extract and summarise all the events fired for the faceted and filtered search • Advanced – Extract product and category level Enhanced Ecommerce information – Calculate the average ‘buy to detail’ and ‘cart to detail’ – Place categories and products into 4 categories • Little Seen – Little Bought • Little Seen – Often Bought • Often Seen – Little Bought • Often Seen – Often Bought
  28. 28. Twitter: @charlesmeadencharles@digitalnation.co.uk Boston Matrix Often Seen / Little Purchased Often Seen / Often Purchased Little Seen / Little Purchased Little Seen / Often Purchased Often Seen Little Seen Often Purchased Little Purchased
  29. 29. Twitter: @charlesmeadencharles@digitalnation.co.uk Google Search Console API • Analytics Edge can extract data out of the Google Search Console API • Combine it with Google Analytics to add search queries to the landing page data • We use to – Grab as many queries as possible – Classify queries into intent groups – Really understand brand vs non brand traffic
  30. 30. Twitter: @charlesmeadencharles@digitalnation.co.uk Extract All The Queries From Google Search Console • Analytics Edge contains a repeat macro • Use this to grab all the queries containing a,b,c etc – We run 89 queries including common parts of words such as er,at • With some clients, we are getting 100,000+ keywords • For a well known retailer, we extracted 468,463 phrases used to show their site in the Google SERPS over a 16 month period
  31. 31. Twitter: @charlesmeadencharles@digitalnation.co.uk Classify Queries Into Intent Groups • Analytics Edge allows to make multiple passes over the data • We build macros to extract the most popular used 2,3 and 4 word combinations used in the search queries – For the phrase ‘red tennis shoes’, ‘green tennis shoes’ , ‘cheap tennis shoes’ we would extract tennis shoes • These are ‘eyeballed’ to determine content groups • Filters in Analytics Edge support regex, which allows us to build out capture groups – The example here uses the regex b word boundary to capture any search query that contains a question • The repeat macro facility takes the first query and extract any phrase to a new worksheet. It then then works through the list, deduping as it goes
  32. 32. Twitter: @charlesmeadencharles@digitalnation.co.uk Brand vs Non Brand Traffic • People searching for a brand don’t always land on the home page and sitelinks make it harder to track • Google Search Console data will always be less accurate than Google Analytics • Using the Google Analytics and Google Search Console API, we do the following 1. Download all search queries and landing pages 2. Divide them between brand and non brand search queries (including misspellings) 3. For each landing page calculate the number of clicks that came from brand and non brand terms 4. Using the click split, calculate the percentage of traffic for each landing page that came from brand and non brand 5. Extract all organic landing page traffic from Google Analytics for the same period 6. Use the percentage split to calculate how much traffic is brand related • You may find brand traffic is far higher than you thought
  33. 33. Twitter: @charlesmeadencharles@digitalnation.co.uk Thank You… • Any questions or feeback, please • Email me at Charles@digitalnation.co.uk • Follow me on Twitter @charlesmeaden • Connect with me on LinkedIn

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