1. The document discusses effective customer segmentation for understanding website traffic and properly evaluating marketing campaigns.
2. It recommends starting with a simple segmentation of logged-in visitors to change one's view of web analytics data. Calculating conversion rates from potential customers only is also recommended.
3. Customer cohorts based on acquisition date can provide insights about customer activation and retention. The document recommends not limiting oneself to what web analytics tools offer and making tools analyze customized segments.
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. Why to Segment Your Customers
● Understanding the behaviour of different
customer segments on your website
● Evaluating acquisition and retention campaigns
properly
6. Most Important Customer Segmentations (1/3)
● Customer Type
• Anonymous
• Registered users
• Customer with purchase history
7. Most Important Customer Segmentations (2/3)
● Customer Lifetime Status
• New Customer
• Frequent Customer
• VIP Customer
• Nonactive Customer
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. 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. 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. 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/
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. What Cohorts Are Mostly Used
● Date, month or year of acquisition
● Most recent purchase date
● Traffic source of first visit
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. 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/
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. 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. What to Segment Content by
● Mobile traffic
● Traffic source (organic, PPC, affiliation, email…)
● Geolocation
● Customer segments
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. 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
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. 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