Effective customer segmentation

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Efficient customer segmentation in Google Analytics (Blueffect 2013 Warsaw, Poland) - examples and best practices of accurate data analysis and advanced segmentation principles in order to improve revenues of your business.

- What makes you wrongly evaluate marketing campaigns: do you know, what is the real conversion rate of your website?
- How to prioritize content sections of an e-commerce website.
- What customer segments and cohorts are useful.

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Effective customer segmentation

  1. 1. Effective Customer Segmentation Blueffect: II Ogólnopolski Kongres Efektywności Warsaw, July 26, 2013 Pavel Jašek
  2. 2. Agenda 1. How can a customer segmentation change your usage of web analytics data 2. Why your marketing campaigns are evaluated wrong 3. Customer cohorts 4. Actionable content segmentation and prioritization
  3. 3. Why to Segment Your Customers ● Understanding the behaviour of different customer segments on your website ● Evaluating acquisition and retention campaigns properly
  4. 4. Important progress in understanding website traffic 1 2
  5. 5. Customer Segmentation Options
  6. 6. Most Important Customer Segmentations (1/3) ● Customer Type • Anonymous • Registered users • Customer with purchase history
  7. 7. Most Important Customer Segmentations (2/3) ● Customer Lifetime Status • New Customer • Frequent Customer • VIP Customer • Nonactive Customer
  8. 8. Most Important Customer Segmentations (3/3) ● Value segments for frequent customers • <1 000 złoty in last 3 months purchases • >1 000 złoty in last 3 months purchases • > 10 000 złoty in last 3 months purchases
  9. 9. 3 Ways to Gather Data for Segmentation 1. Implementing Custom Variables • _gaq.push(['_setCustomVar', 5, 'customer', 'VIP', 1]); • _gaq.push(['_setCustomVar', 4, 'ID', '123', 1]); • For GA: visit-level or visitor-level scope • Similarly in Piwik, Adobe, Webtrekk and Webtrends 2. Backward integration to customer ID • Universal Analytics: Dimension Widening 3. Without any implementation • Ad-hoc segments based on pageview /login.html
  10. 10. Recommendation #1 Start with a simple segmentation of logged-in visitors. Your view on web analytics data will change forever since than. Pavel Jašek
  11. 11. Good Sources to Read ● Google Analytics Custom Variables • https://developers.google.com/analytics/devguides/ collection/gajs/gaTrackingCustomVariables ● Ideas from Lunametrics • http://www.lunametrics.com/blog/2012/08/28/20- ways-use-custom-variables/
  12. 12. Demystifying the conversion rate
  13. 13. Demystifying the Conversion Rate ● CR = Conversions/Total Visits ● What if not all visits come to your website in order to convert?
  14. 14. 70-90 % of bank homepage visits come only to login to e-banking
  15. 15. Prospects Instead of Visits ● CRp = Conversions/Prospects ● CRp = Conversions/(Total Visits – Visits of current customers)
  16. 16. Using Visits Using Prospects • 100 total visits • 2 new registrations • CR = 2/100 = 2 % • 100 total visits • 2 new registrations • 30 visits from customers • CR = 2/(100-30) = 2,9 %
  17. 17. Your registered users also come via organic and paid traffic sources. This impacts campaign evaluation.
  18. 18. Recommendation #2 Calculate conversion rates from potentional customers only. Pavel Jašek
  19. 19. Customer Cohorts
  20. 20. Understanding customer activation and retention using cohorts based on registration date 0 100 200 300 400 500 600 700 1 8 15 22 29 Numberofvisits Days since registration Registered in April Registered in May
  21. 21. What Cohorts Are Mostly Used ● Date, month or year of acquisition ● Most recent purchase date ● Traffic source of first visit
  22. 22. Recommendation #3 Don’t limit yourself to what your web analytics tool offers. Make the tool measure, process and visualize what YOU want. Pavel Jašek
  23. 23. Good Sources for Cohort Analysis ● Cohort Analysis 101 by RJ Metrics • http://cohortanalysis.com/ ● Cohort Analysis in Google Analytics • http://cutroni.com/blog/2012/12/11/cohort- analysis-with-google-analytics/ ● Cohorts in Kissmetrics • http://www.kissmetrics.com/demo/reports/cohort/
  24. 24. Content Segmentation Matrix
  25. 25. Content Segmentation Matrix Principles ● Group your content into sections of interest ● Compare pageviews by different types of visits ● Find significant differences as insights
  26. 26. Segmenting by Desktop and Mobile Traffic Content section Desktop pageviews Mobile pageviews More on mobile? Bank branches 2,0 % 5,4 % 174 % Loan calculator 1,0 % 2,8 % 166 % ATM Locations 0,4 % 1,8 % 333 % Contacts 1,2 % 1,7 % 39 % Currency exchange rates 0,6 % 1,0 % 70 % First login 5,9 % 2,8 % -52 % Mortgage products 3,6 % 1,7 % -52 % Saving Accounts 1,5 % 0,8 % -47 %
  27. 27. What to Segment Content by ● Mobile traffic ● Traffic source (organic, PPC, affiliation, email…) ● Geolocation ● Customer segments
  28. 28. Recommendation #4 This segmentation allows you to understand e.g. if your VIP customers are visiting your new products. Pavel Jašek
  29. 29. Content-Content Matrix
  30. 30. Content-Content Matrix Principles ● Group your content into sections of interest ● Find number of visits that saw both sections from each combination ● Using cross-selling principle „those who saw section A also saw section B“ ● Compute relative frequency of visits in such combinations
  31. 31. Number of Visits in Section Combinations Outdoor Clothing Shoes Light Sale Outdoor 1 500 Clothing 540 2 500 Shoes 300 450 900 Light 655 600 477 1 450 Sale 732 777 151 633 1 780
  32. 32. Relative Visits to Site Sections ↓Outdoor ↓Clothing ↓Shoes ↓Light ↓Sale Outdoor 100 % 22 % 33 % 45 % 41 % Clothing 36 % 100 % 50 % 41 % 44 % Shoes 20 % 18 % 100 % 33 % 8 % Light 44 % 24 % 53 % 100 % 36 % Sale 49 % 31 % 17 % 44 % 100 %
  33. 33. What Page Types Are Useful for Segmentation ● Homepage ● Product categories ● Contact pages ● User login ● Support pages
  34. 34. Recommendation #5 Sections cross-views give you actionable insights about which site sections should be better linked together. Pavel Jašek
  35. 35. Conclusion
  36. 36. Conclusions 1. Customer segmentation is important for unfolding what really happens on your website 2. Evaluate campaigns only by the relevant traffic 3. Make your web analytics tool measure, process and visualize what YOU want 4. Compare what different customers want on your website 5. Segmentation gives you actionable insights
  37. 37. Action Steps 1. Start with the easiest segmentation possible 2. Make a draft output with a pencil 3. Think how would such output help you 4. Implement it 5. Analyze the data 6. Present your insights to your colleagues 7. Use those insights to improve your website
  38. 38. @paveljasek pavel.jasek@dobryweb.cz

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