Personalization Best Practices for Engaging Online Experiences


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Slides from an American Marketing Association (AMA) webinar re: how to implement online personalization techniques - pitfalls, opportunities, best practices.

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Personalization Best Practices for Engaging Online Experiences

  1. 1. Personalization Best Practices for Delivering an Engaging Online Customer Experience Carlos Carvajal, Sr. Director of Marketing, Baynote April 28th, 2010
  2. 2. Agenda • Personalization 101 • Common Pitfalls • Always Right Personalization • Real-World Use Cases & Results
  3. 3. What is Personalization? Personalization is a strategy for delivering a customer experience that is always personal, relevant and convenient EXPLICIT IMPLICIT • Profile-based • Behavioral-based • Segment-based • Context-driven • Rules-driven • Collaborative Filtering
  4. 4. Many Ways to Personalize… Implicit Product Recommendations Content Recommendations
  5. 5. Many Ways to Personalize… Explicit Customization Role-based
  6. 6. Many Ways to Personalize… Channels & Content
  7. 7. Personalization Benefits Increase: • Conversions • Engagement • Revenue • Customer Insights • Customer Lifetime Value
  8. 8. Common Personalization Pitfalls
  9. 9. Four Common Personalization Pitfalls 1.Must Build a Comprehensive Customer Profile First 2.Create Rules to Target Content Based on Customer Preferences 3.“Ultimate Personalization!” 4.Personalization is Really Hard to Get Right
  10. 10. Pitfall #1: Must Build A Comprehensive Profile First… Brother Uncle Husband Engineer CEO Father What to recommend???
  11. 11. Pitfall #2: Create Rules to Target Content…
  12. 12. Pitfall #3: “Ultimate Personalization!”
  13. 13. Pitfall #4: Personalization is Really Hard to Get Right Approval & Deployment BI, Analytics & MV Testing • New issues with priority • Too much noisy data • Missed deadlines • Rear-view mirror • Out-of-sync with market • Guess work Re-design Re-launch Re-platform Annually Quarterly Monthly Development & QA Tuning, Merchandizing & Editing • Too many projects • Manual & costly • Conflicting priorities • Top 5% most popular only • Expensive • Expert bias Too Slow, Too Expensive
  14. 14. Personalization in 2001 – Learn From the Past Source: ‘Web site personalization’, IBM 2001
  15. 15. Always Right Personalization
  16. 16. Always Right Personalization
  17. 17. Always Right Personalization “By understanding who you are and your shopping history… I can accurately predict which products you are currently interested in.” VS. “What are you looking for?” “Many customers who came before you liked this beginner snowboard…”
  18. 18. Collective Intelligence Powers Always Right Personalization Combination of Social and Cognitive Science Sell 1 of many Crowds are free Invisible Crowds Niche segments Crowds > Expert Actions > Words Micro projects Crowds reduces cost Whole > Sum of parts Real-time trends 7 deadly biases Real-time feedback But how? Aligned incentives?
  19. 19. Respond to Changing Customer Needs in Real-Time Approval & Deployment BI, Analytics & Observes Automatically MV Testing • New issues with priority • Too much noisy data Emergent Patterns • Missed deadlines Automatic Adjustments Real-time • Rear-view mirror • Out-of-sync with market • Guess work Re-design Re-launch Re-platform Annually Quarterly Monthly Use Collective Intelligence Development Little IT Involvement & QA Tuning & Merchandizing • Too many projects • Manual & costly • Conflicting priorities • Top 5% most popular only • Expensive • Expert bias
  20. 20. Three Principles for Achieving Always Right Personalization 1.Focus on Context First 2.Understand Customer Intent Through Engagement 3.Like-Minded Peers Know What They Like Best
  21. 21. Principle #1: Focus on Context First Brother Uncle Husband Engineer CEO Father What to recommend CONTEXT DRIVES RELEVANCE ?
  22. 22. Principle #2: Understand Intent Through Engagement
  23. 23. Principle #3: Like-Minded Peers Know What They Like Best
  24. 24. Putting it All Together… …page refers, links, entry trails, queries, page sizes, mouse movement, negative experience, virtual bookmarks, time spent, exit trails…
  25. 25. Real-World Use Cases & Results
  26. 26. Use Case: Personalized Landing Pages Known context Unknown context
  27. 27. Use Case: Personalized Search The crowd knows “insight” is really the LG Incite phone.
  28. 28. Use Case: Dynamic Navigation • Real-time as trends emerge • Based on aggregated visitor behavior • Brings content to the navigation level Popular content in category
  29. 29. Use Case: E-Mail Personalization Transactional Email Promotional Email 4x Conversion Rate
  30. 30. Use Case: Video Recommendations 21% Increase in Video Starts
  31. 31. Use Case: Recommendations Across Content Types Most Popular, Related, Content  Video, Email…
  32. 32. Use Case: Social Personalization Items shared by friends drive recommendations based on your preferences What I‟m cooking You Might Like today
  33. 33. Use Case: Identify Customer Trends Identify Trends Before They Happen Find Gaps and Optimize Product Mix
  34. 34. Use Case: Merchandising & Targeting Controls Select Action Select Product Select where product should be shown
  35. 35. Personal Profiles Serve as Filters and Constraints Personalized store
  36. 36. Personalization Best Practices Known Contextual Recommendations Personalized Contextual Recommendations Context Unknown Most Popular Products Personal Recommendations Unknown Profile Known
  37. 37. Real World Results: Bluefly Results: 300% lift in sales in Q4 „09 Profile • $84M High fashion discount eTailer • 50K SKUS, 350 brands Challenges • Low inventory per item • Constant turnover of product • Needed real-time solution “By making recommendations more relevant from a time perspective, we knew we would get a lift, but we had no idea it would be this much" – Marty Keane, SVP ecommerce
  38. 38. Real World Results: TurboTax Results: • 35% increase in site search conversion rates within weeks Profile • 73% increase within a year • 14M taxpayers • Award-winning support site Challenges • Taxpayers unable to find answers • Manually hard-coding content recommendations in results • Rapidly changing content & seasonality “The results were so overwhelmingly positive that it became a no-brainer.” Chris Jones, Web Analytics Manager
  39. 39. Baynote in a Nutshell Company • Pioneered real-time recommendations using collective intelligence in 2005 • 200+ web sites use Baynote today Technology • Collective intelligence foundation • Breakthrough UseRank® patents Solutions • Real-time personalization, targeting and recommendations • SEO and SEM – peer-driven • Search optimization – re-ranking by engagement • Email & video recommendations • Insights - Merchandising, Testing, Reporting
  40. 40. Key Takeaways 1. Avoid Common Pitfalls • Build a comprehensive customer profile first • Create rules to target content… • Personalization is really hard to get right 2. Best Practices for Success • Understand customer intent thru engagement • Use Collective Intelligence to respond to changing customer needs in real-time • Personal profiles serve as filters & constraints 3. Start Simple… • Identify high-value personalization use case: landing page, e-mail, product detail page • Define clear success metrics and plan for results within 8-12 weeks • Use customer insights, run tests, adapt
  41. 41. Thank You for Your Participation! Contact Information • E-mail: • Twitter: @Baynote To Learn More About Baynote • • Continue the Conversation on Twitter: #AMABaynote