Web analytics

1. Web analytics Beyondwebsiteoptimization

2. Introduction Most of us are already familiar with web analytics as a marketing tool, to optimize transactions and realize maximum ROI from campaigns. But web analytics data can be used throughout your company to make data-driven decisions.

3. Who am I?

4. About Me • Angie Brown, Web Analytics Manager at Elsevier Health Sciences • 90+ web sites implemented with Unica’s NetInsight • Lead analyst for flagship MD Consult product • 8+ years web analytics experience • Vendor (IBM SurfAid, Coremetrics) • Practitioner (Elsevier) • Co-chair of Web Analytics Association (WAA) Standards Committee

5. About Elsevier

6. About Elsevier • World’s leading publisher of science and health information • Elsevier Science & Technology, HQ Amsterdam • Elsevier Health Sciences, HQ Philadelphia • Headquarters: Amsterdam, The Netherlands • > 7000 employees in 24 countries • Publisher of 2,000 journals and 19,000 books • 2,000 new books each year

7. Some Health Sciences Products

8. My web analytic toolbox • Analytics tools • Web analytics tool: Unica’sNetInsight • Continuous surveys: ForeSee Results • Multivariate testing: Optimost • Other tools • Excel • Firefox • Access to other data in my company • Back-office databases (reports, SQL access) • Customer management • Subscribers / transactions • Financial reports • Raw server logs

9. Who uses web analytics data?

10. Who uses web analytics?

11. Web analytics users… Company Executives / Strategy Group

12. Executives / Strategy Group Use web analytics to… Support good decision making on a corporate or business unit level

13. Two ways to view data • Key performance indicators (KPIs) • Historical • Bottom line • Performance-driven • Proactive analysis • Show how/where visitor behavior supports executive strategy (or not) • Identify new opportunities that support corporate goals

14. Segmentation is key • Marketers – both online and direct – are accustomed to segmenting customers into strategic groups • New customers, low/high value customers, at risk customers, etc. • Web analysts use additional segmentation for executive-level insight • Product or product line • Business unit • Customer segments • Along financial reporting segments

15. Strategic reporting: cross-product KPIs Allows for benchmarking across many different websites Informs decisions about investment in different websites or online products

16. Strategic reporting: product-level KPIs Revenue Growth Sessions Growth Shows how a specific website contributes to the company’s strategic priorities.

17. Strategic analytics example* • Subscription site with the following types of content • Journals • Books • Drug Info • Practice Guidelines • Sells to the following customer types • Medical Students • Doctors • Students are strong users of the book content • Usage is increasing rapidly in Europe • Executives want to increase focus on selling books to European students • Is this wise? * Segments and numbers are made up for this example

18. Strategic analytics example • Web analytics can be used to support this decision-making process • Metrics • Relative usage of different content areas • Relevant segments • By customer type (student/professional) • By geography • By type + geography together

19. Strategic analytics example • Do findings support the strategy? • Students are indeed heavy users of books • However, European growth has been driven by journal interest, and European students are interested in book and journal content equally • Conclusion: • Targeting books to European students could be a mistake; dive into their usage more to understand their true needs • Bonus: Non-European professionals are relatively interested in Guideline content: could be a hidden opportunity Other geographic areas were left off the example; would include all relevant geographic areas in a real situation

20. Web analytics users Product Managers

21. Product managers • “CEO of the product,” business owner responsible for success of product throughout its lifecycle • Product strategy • Product branding, positioning, marketing • Development priorities • Improvements / enhancements / problem detection • Financial health • In Elsevier, “products” and “websites” are often the same • Many are subscription-based content sites • For other types of sites, the business owner of the website has many of the same responsibilities

22. Product managers Use web analytics to… • Show how their website contributes to corporate goals • Understand how their customers interact with the site • Find barriers to customer success, in order to improve the experience

23. Two ways to view data • Key performance indicators (KPIs) • Same as KPIs rolled up to executives, plus • Other metrics that show the “health” of the site in more detail • Sections/features utilized • Customer satisfaction • Usage of up-sell offerings • Percent visits encountering errors • “Engagement” (time on site, content to navigation ratio, print previews, downloads, etc.) • Marketing metrics (campaign performance, transactions, conversion rates, etc.) • Ad hoc analysis • Often exploratory in nature • Who is using the site? How? • Look for deeper customer understanding • Seek out problems before customers find them • Gage effectiveness of development efforts • Prioritize projects

24. Segmentation is key • Segment in the same manner as rolled up to executives, plus… • Segment by content type • Compare/contrast groups of pages that represent similar content or functionality • Exploratory analysis can require segmenting on anything/everything available • Used for troubleshooting, or exploring new opportunities • Which segments behave significantly different than others?

25. PM example: content groups

26. PM example: content groups by segment • Informs decisions about: • Up-sell opportunities • Product expansion • Branding / messaging among different customer types Why is this content so appealing to students, and no one else? Visitors from larger firms are more focused. What are people saying about these features? Is it bad or good?

27. PM Example: content groups by entry location • Informs decisions about: • Cross-linking between different areas of the site • Cross-promotion • Similar analysis can be used by program managers (for promotional programs at a bank): shows how efforts at cross-sell/up-sell are doing

28. PM Example: local search troubleshooting • “Zero results” searches higher than anticipated • Site contains well over 10 million pages of content • Requires subscription: unlikely someone would reach it by mistake • Site measures high in customer satisfaction • Customers who use search are generally more satisfied than those who do not • Lots of specific feedback for “bad” searches, but no obvious patterns • Track % zero results search visits as KPI: try to lower

29. PM Example: local search troubleshooting • No clear pattern of issues emerged with available data: zero-results search terms, site feedback, user testing • Exploratory analysis: Do any customer segments have higher-than-average zero-results searches? • Segment by country, entry page, customer type, referrer, etc. Search issues, relatively few users affected Who gets a lot of no-results? No problem No problem Who uses search a lot?

30. PM Example: local search issues Latin American countries! Analysis led to very specific recommendations for improving search, and better customer understanding. Few not-founds Many not-founds Use search a little Use search a lot

31. Web analytics users Sales teams / Account Managers

32. Sales / Account Managers Use web analytics to… • Identify at-risk customers • Look for up-sell opportunities • Assist with pricing / discounting decisions

33. Sales / acct mgmt example • Informs decisions about: • Priority attention from account team • Price increases or discounts • Retention marketing

34. Web analytics users Content Providers

35. Content providers • Authors • Editors • Publishers • Consultants • Subject matter experts • Direct marketers creating content for campaigns • Anybody who writes or sources the content that is on your site

36. Content Providers Use web analytics to… • Find out what resonates with customers • Inform decisions about adding, modifying, or removing content, both online and offline

37. Can use online data to inform offline decisions • When content is offered in multiple channels, use online data to help inform offline decisions • Print books • Areas to focus on for next edition • Where to cut, if necessary • Newspapers • Which stories are most interesting to readers online? • Can position better in print • Corporate brochures / handouts / white papers / other printed documentation • What information are your customers after the most? • Test out marketing messages online before committing to print

38. Content provider example – top articles

39. Content provider example • View ageing of content overall • Determine where to cull if necessary • Investigate old articles are being viewed • Redirect to new content? • Revise? • Update links? • “Classic” content that stands the test of time?

40. Content provider example • View ageing of specific titles • Lag between publish date and usage? • Is content used to keep current with latest news? Or is it used as a reference?

41. Content example: online data informing offline decisions • Print version of Cecil Textbook of Medicine • “The granddaddy of general internal medicine texts” (JAMA) • 3120 pages • 11.2 pounds • 467 chapters in 28 sections • Online • Full text online in two different products • Broken into1574 “pages” • Chapters, sections same as print

42. Cecil Medicine online usage

43. Wrap-up

44. Conclusion “Boundarylessness” Increased customer focus, and better business decisions