The document discusses using session replay technology and mouse cursor tracking as an alternative to eye tracking to infer user intent and behavior on websites. It provides examples of how session replay data could be used to segment users based on factors like task completion, satisfaction ratings, and problems encountered. The document argues this emerging technique of analyzing cursor movements and replay data has the potential to provide useful insights for web analytics and usability testing.

1. The future of web analytics: Inferring User Intent from Session Replays Dustin Chambers & Dick Horst UserWorks inc.

3. First source of web use data 86.42.132.114 - - [31/Oct/2005:18:15:16 -0500] "GET /styles/style.css HTTP/1.1" 200 5194 "http://www.example.com/links/links.php?cat=css" "Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.12) Gecko/20050915 Firefox/1.0.7"

4. Early attempts to visualize data

5. Dashboard

6. Page tagging

7. Google Analytics -Google Analytics

8. Heat Maps

9. Page Overlay -CrazyEgg

10. Hover Map

11. Session replay e.g.

12. Providers? Cost? RobotReplay – Free www.robotreplay.com ClickTale – Free - $99/month www.clicktale.com TeaLeaf - $20,000+ www.tealeaf.com

13. How is this any better? How do we use it?

14. Alternative to eye-tracking? “ The data suggest that there is a very strong relationship between gaze position and cursor position.” “ This implies that we can use an inexpensive and extremely popular tool as an alternative of eye-tracking systems, especially in web usability systems.” -Carnegie Mellon, 2001

15. Information Foraging Theory “ What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” -Herb Simon (Nobel Prize Winner)

16. Consider the anecdotal evidence “ Just by looking at the way a mouse moves, I can tell whether you are reading a webpage or not.” “I can tell because when you read a webpage, you do one of two things. You either shove the mouse off to the right so it is out of the way, or you will walk down the page with your mouse.” Dr. Ted Selker, MIT Media Lab

17. Ambiguity “ Slow and arched trajectories as users move their mouse would indicate an ambiguous state of mind.” -MIT Media Lab

18. Are you experienced? “ People are extremely good at remembering graphic design. So when you act like you know where you are going on a place where you have no reason to know, then we know you have been there before.” Dr. Ted Selker, MIT Media Lab

19. Web Analytics 2.0 -Avinash Kaushik

20. Web Analytics 2.0 Apply Context Segment Triangulate/Validate

21. Examples Inferring user intent using the latest web analytic technology with the latest theory

22. What’s next? Bleeding-edge technology Future Implications…

23. Integrated Triangulation Surveys Why are you here? Where you able to complete? Why not? How satisfied? Unmoderated remote usability testing

24. Enhanced Segmentation Filter by: Task completion Satisfaction rating User intent Problem encountered Time on task Search term

25. Thanks for listening! Dustin Chambers [email_address] Dr. Dick Horst dhorst@userworks.com