1. Anonymity of Clickstream data

2.  Traffic from different countries  People with different intent –Buyers –Browsers –Competitors –Visitors with no apparent reason –Students –Information seekers –Potential employees –(employees, crawlers, machine traffic) One of the reasons why senior management don’t trust the data

3. Solution? SEGMENTATION!

4. Benefits  Data that pertains to your target audience  Take action  Different strategies for different segments  Triggers for successful behavior  Market intelligence

5. Segmentation  Segment based on what? –Geography, Time, Referrer, Campaign, Content, Behavior, Success Visitors, Paid traffic, Natural SEO traffic.  What metrics to look at?  What possible actions to take?  How this is done?

6. 1. Geography

7. Metrics  Visits / Visitors  Top content  Top Products  Key phrases  Internal search phrase  Orders

8. Scenario  IT company focused on certain countries –Eliminate data from other regions All metrics would be more accurate with narrower data Less skew (example: career traffic)

9. Scenario  Services company looking at new regions –Search key phrase – know what people are looking at –Internal search phrase – know what people are looking specifically from the company –Top Downloads / Pages – Which service is relevant –Top supporting pages – What supporting information are they looking for? All this can go as market intelligence to the sales/marketing team

10. Scenario  Product company delivering in multiple countries –Traffic source pie – decide where the marketing dollars should be spent –Top Viewed services – inputs to sales –Search terms – customer intent –Top viewed supporting pages – inputs to sales / marketing –Visits to non-English sites – decide to start / sustain / shut- down. –Download data – decision on which collaterals to print

11. 2. Time / Day / Date

12. Metrics  % Visits / Visitors  Top products viewed  Top products ordered  Orders for previous year / month / day  Email: Open ratio / CTR / Conversions  Conversion ratio for messages (internal ads)

13. Scenario  E-commerce site –Message conversion ratio What offers and where –Top products viewed / ordered: Timing for running PPC ads Product display on key landing pages Stock –Email metrics: When to send and what to talk about

14. 3. Referrer

15. Metrics  Visits / visitors (share, trend)  Conversion (orders / subscriptions / leads)  Top landing pages  Top content consumed  Geography

16. Scenario  News website –Engagement: Understand which referrer is better –Content consumed: Useful to know what kind of traffic is of interest –Geography data: Relevant referrers for specific regions –Visit trend: Predict when the traffic is going to happen (cricket)

17. Scenario  B2B Website / Content Website –Region data: Useful to evaluate PR effectiveness –Engagement metrics: Identify high-value referrers and pursue relationship with them –Content consumed: links from the landing pages

18. 4. Success Visitors

19.  Success Visitors: –Ordered –Subscribed –Inquired –Looked at x number of pages –Looked at key pages –Used a particular key phrase to reach  Very powerful segment to help initiate action

20. Scenario  E-commerce Website –Product ordered-Key phrase matrix: Useful for choosing products / key phrases for PPC –Geography – product ordered: Choosing regions for PPC –Supporting pages viewed: Push pages –Campaign: Looking at where to spend money –Paid key phrases: Which terms to bid –Products ordered: Figuring out related products to push (through email, landing pages, etc) –Offers: Know what to push and where

21. Scenario  Lead generation website –Content consumed: knowing which pages influenced –Trigger page: For cross-linking –Search engine key phrases: action point for SEO –Geography: Knowing where the customer is –Search Engine date: Choosing key phrase – engine combination

22. Tools

24. To Conclude  Segmentation options for your tool  Start looking / reporting segmented data  Segmenting based on geography / referrer / success visitors – easy to start  Consider Clicktracks (for analysis and not reporting)  Explore multiple profiles and custom variables for GA

25. Questions For more on this topic, please visit www.nabler.com/blog www.nabler.com/blog If you visit, please leave a comment so that I know you had come If you have questions, please post a comment and I will try to answer them. Seby Kallarakkal