What to Feed Your Search Engine: The Evolution of Search Analytics at HBS

860 views

Published on

Overview of three iterations of search analytics tools and actions taken to improve search UX based on analytics.

0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
860
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

What to Feed Your Search Engine: The Evolution of Search Analytics at HBS

  1. 1. What to Feed Your Search Engine:The Evolution of Search Analytics at HBSRavi MynampatyCopyright © President & Fellows of Harvard College
  2. 2. Our Organization• Harvard University • Many schools (HMS, HLS, HKS, …)  Harvard Business School (HBS)  ITG, DRFD, MBA, Exec Ed, M&C, …  Knowledge & Library Services (KLS)  Information Management Group  Metadata/Taxonomy  Information Lifecycle Management  Analytics  Search & Findability (== Ravi) @ravimynampaty 2
  3. 3. Agenda• Background• Three generations of analytics tools • Query Log Reports • JeffTrends • Hosted solution• Using analytics @ravimynampaty 3
  4. 4. Background• In the beginning… • OOTB search engine • No optimization, no customization • Fraction of HBS content indexed / searchable• Proliferation of different search tools• User sentiment  “Search sucks”  “Why can‟t we just get Google?” @ravimynampaty 4
  5. 5. @ravimynampaty 5
  6. 6. Query refinement options Query resubmit options @ravimynampaty 6
  7. 7. Analytics Needed…• Provide insight into:  Impact of UI changes  Behavior of search users  needs, wants, give a „face‟ to visitors• Reflective, not predictive @ravimynampaty 7
  8. 8. Common Metrics to Track• Visitor Segmentation• Visits• Top Entry/Exit Pages• Task Completion Rates• Visitor Primary Purpose• Query Analysis @ravimynampaty 8
  9. 9. Top search terms• Do they have good results?• Any with no-hits?• What‟s the click-thru rate ?• What are the referrer pages ? @ravimynampaty 9
  10. 10. Analytics: Implementation• Query Log Reports • Record additional data as needed • Refinement usage • Best bets click-thru • Originating site • Generate reports from logs• JeffTrends • Collect data with JavaScript • Record to web server log • Generate reports from logs @ravimynampaty 10
  11. 11. Query Log Reports @ravimynampaty 11
  12. 12. Query Log Reports @ravimynampaty 12
  13. 13. Query Log Reports @ravimynampaty 13
  14. 14. JeffTrends @ravimynampaty 14
  15. 15. JeffTrends @ravimynampaty 15
  16. 16. Top Queries by Referrer @ravimynampaty 16
  17. 17. Top HBS Queries by Role and Profile @ravimynampaty 17
  18. 18. Path from www @ravimynampaty 18
  19. 19. Using Analytics: The Process• Collect Data• Record data (reports)• Test improvement strategies• Implement improvement• Measure results• Repeat process @ravimynampaty 19
  20. 20. Using Search Analytics• Add/remove refinement options• Add synonym-like functionality • 5-2423  (617) 495-2423• Date sorts• Taxonomy development• Feed Best Bets @ravimynampaty 20
  21. 21. Create Best BetsTop 10 QueriesOct – Dec @ravimynampaty 21
  22. 22. Conclusion• Getting the most out of your search engine• Search is only as good as content• Content gaps/content development/design• Answer “What if …?” questions @ravimynampaty 22
  23. 23. Thank You• Questions? searchguy@hbs.edu @ravimynampaty 23

×