The document discusses the importance of measuring customers rather than devices or cookies in web analytics. It emphasizes that customers are not homogeneous and should be analyzed and treated according to different segments like fans, regulars, and occasional visitors. Tracking unique customer IDs across channels allows companies to better understand customer lifecycles, attribute marketing ROI, and identify cross-channel opportunities. Mobile analytics presents new challenges to connect app usage to revenue that can be addressed through a holistic cross-channel view linking customer-level data.

1. Analytics 2.0 SAScon Tom Betts, Head of Web Analytics, FT.com 20 May 2011

2. Our business model: combined subscription and advertising revenue FT digital circulation increased 50% last year "the information and intelligence gained from readers from a subscription model is a powerful asset“ – John Ridding, CEO, Financial Times Context

3. <soapbox> Always ask – ‘so what?’ Remember: great analytics are only as great as their usage </soapbox> Before we begin..

4. Metrics? There’s no magic bullet You’re smart – and experts in your field Topics for today: Customers are not all made equal Measure customers, not devices or browsers Dealing with emerging channels

5. Customers are not all made equal Customers are not all made equal

6. Customers are not all made equal No one size fits all People use your sites in different ways ...so think about them differently Don’t think in aggregate, think in segments Fan Regular Occasional Fly-by

7. Customers are not all made equal Multichannel: Measure customers not cookies

8. We almost always deal in cookies But cookies are: unique to a device and browser deleted! blocked! unreliable! ComScore: 2.4x cookies per user per site in 1 month Now your customer acquisition campaign ROI doesn’t look so attractive… Measure customers not cookies

9. Consider: using a (persistent) customer ID instead Provides context (e.g. purchase history, geodemographics, account descriptors) Combine with behavioural information compare new customers with repeat.. Descriptive attributes endlessly segmentable data Knowing your customer endlessly actionable data Know Your Customer Web analytics + customer ID Get data into data warehouse Turbocharge

10. And know their lifecycle too.. Unaware Interested Customer Repeat customer

11. The value of linked data Enables eCRM ‘ Who ’ dimension improves ‘ what if ’ analysis Segmented, personalised, trigger-based marketing communications Measure marketing ROI accurately

12. Customers are not all made equal Multi-platform: mobile analytics

13. Customers are not all made equal “ My mobile app is highly profitable” Really?

14. We used to have multiple PCs / browsers - now we have multiple devices too.. Is my new channel making me more money? Some metrics: % of customers that are new? channel incremental revenue? Joining the dots is hard

15. Use a single platform for cross-channel analytics Do what we did before: measure people not cookies* – join the data by customer ID Web analytics rock star moment: Use channel(s) to segment your analysis? * Because apps don’t necessarily even support cookies! So what do we do?

16. Clear line of sight from app usage to revenue via customer Holistic picture of channel consumption Figure out how to invest in mobile Identify new channel marketing opportunities And the benefit?

17. Summary Goodbye global averages – segment, segment, segment! Turbocharge your analytics by measuring customers, not cookies Next most important thing you do: figure out your channel mix

18. Thanks! [email_address] / @tomp2 (PS we’re hiring)