Usability <> Web Metrics ; Advancing analytics through the lessons of usability ...and improving user experience along the way
•
24 likes•963 views
Traditional Web analytics are designed to capture how easily and how often users “convert” by buying stuff or taking desired actions on Web sites. While Web analytics and other data-oriented measures work well for commercial sites, they often fail to capture the user-friendliness or effectiveness of government and other information-oriented sites. Within this talk, we will: * Outline the complementary objectives of usability and Web analytics measures * Review usability testing methods designed to measure users’ comprehension * Discuss how the business concept of “conversion” can be applied to sites that provide government information * Discuss the benefits of integrating the Web analytics and usability data streams * Describe performance measures that map user experience metrics or measures to NIH Web site business goals Throughout the talk, they will explore the characteristics of the different data streams. They will also explain how–when intertwined—the data streams may provide even more clearly actionable guidance for Web site improvement.
Recommended
Recommended
More Related Content
Viewers also liked
Viewers also liked (19)
Similar to Usability <> Web Metrics ; Advancing analytics through the lessons of usability ...and improving user experience along the way
Similar to Usability <> Web Metrics ; Advancing analytics through the lessons of usability ...and improving user experience along the way (20)
More from Kath Straub
More from Kath Straub (13)
Recently uploaded
Recently uploaded (20)
Usability <> Web Metrics ; Advancing analytics through the lessons of usability ...and improving user experience along the way
- 3. 4
- 4. NIH types know a lot about how to handle data.
- 6. What we’ve learned doing usability may help analy0cs move faster
- 7. Analy0cs is also be about what can happen.
- 10. Measurable Business Objec0ves Usability Web Tes0ng Analy0cs Best Prac0ces Review 29
- 12. UX <> AX
- 19. Ins0tu0onaliza0on of Usability • Grassroots/Piecemeal effort • Tactical response • Train wreck • Notice of the champion • Organizational commitment • Recognized as skill • Common Method • Tools & Training 29
- 22. Define the question(s) Ask: Who cares? Pick the data Collect and track Present just enough Present to drive action
- 25. Analy0cs and usability ‐ similari0es ‐ Planning hEp://ins2tute.nih.gov/index hEp://ins2tute.nih.gov/grants hEp://ins2tute.nih.gov/grants/deadlines Institute home Health Grants Research Health Pg 1 Deadlines Research Pg 1a Health Pg 2 Grants Pg 2 Research Pg 2 Grants Pg 3 Research Pg 3 Grants Pg 4 Research Pg 4 29
- 26. Pain points ... URL naming conven0on hEp://SiteHomepage/default.asp hEp://SiteHomepage/Default.asp hEp://SiteHomepage/default.aspx Institute home Health Grants Research Health Pg 1 Grants Pg 1 Research Pg 1a Health Pg 2 Grants Pg 2 Research Pg 2 Grants Pg 3 Research Pg 3 Grants Pg 4 Research Pg 4 29
- 28. Visit cycle Engage & Attract Commit Convert Persuade Unengaged Unconverted Unpersuaded (Bounce) 28
- 30. “Typical” Measures Engage & Attract Commit Convert Persuade captured Visits = # site entries 30
- 31. “Typical” Measures Engage & Attract Commit Convert Persuade Bounce 31
- 32. “Typical” Measures Engage & Attract Commit Convert Persuade captured converted Tradi0onal Conversion = Converted / Captured 32
- 34. Addi0onal Measures ‐ Engaged Visits Engage & Attract Commit Convert Persuade engaged Engaged Visits = # site visits that move N* pages into the site 34
- 35. Addi0onal Measures ‐ Engagement Index Engage & Attract Commit Convert Persuade engaged Engagement Index = Engaged visits* / Site entries *Engaged visits are site visits that move [1 to N] clicks into the site 35
- 36. Addi0onal Measures ‐ Persuaded Visits Engage & Attract Commit Convert Persuade persuaded Persuaded Visits* = # site visits that enter a conversion funnel *Can be computed for individual funnels or summed over funnels 36
- 37. Addi0onal Measures ‐ Persuasion Index Engage & Attract Commit Convert Persuade persuaded Persuasion Index* = Commieed visits / Visits to PageX *This is a page level measure 37
- 38. Addi0onal Measures ‐ Engaged conversions Engage & Attract Commit Convert Persuade engaged converted Engaged Conversions = Converted / Engaged visits 38
- 39. Addi0onal Measures ‐ Commieed Conversion Engage & Attract Commit Convert Persuade persuaded converted Persuaded Conversion* = Converted / Conversion commitments *This is a page (sequence) measure 39
- 40. Types of conversion Engage & Attract Commit Convert Persuade Persuaded Conversion Engaged Conversion Tradi0onal Conversion 40
- 41. What are we measuring? Engage & Attract Commit Convert Persuade Persuasion Usability Conversion Engagement 41
- 42. How does this reflect site performance? Name awareness & SEO Effectiveness 25000 Content match Good labels Meaningful 20000 Content 15000 Usability 10000 5000 0 Visits Engaged Persuaded Converted
- 43. Performance ques0ons & measures Ques2on Measure Evaluates Brand How many visits to the site? Visits Awareness, SEO Engaged Visits, Right content, How many visits move past the first page? Engagement Index right labels How many visits move into a “Conversion” Persuaded Visits, Persuasion sequence? Persuasion Index What propor2on of engaged visitors Engaged Persuasion + convert? Conversions Usability What propor2on of commiEed visitors Persuaded Usability convert? Conversions 1st Impression content + What propor2on of visits convert? Conversions Persuasion + Usability
- 45. Contribu0on Index – Across key tasks 1 +1 +1 +1 +1 17
- 46. Contribu0on Index – Across key tasks 1 +1 18
- 47. Contribu0on Index – Across key tasks 1 +1 +1 +1 +1 x2 +1 +1 +1 +1 +1 Same page 19
- 48. Contribu0on Index – Across tasks =1 +1 +1 +1 = 4 1 x2 Same page 20
- 49. Contribu0on Index Which page / pages contribute most to the • success of the site? Iden2fy key “final” pages • Where people off • • Key informa2on pages (Submission dates; Workshop desc2p2ons; Ac2ve Mechanisms) Look at common paths to those pages (possibly • the culminate in drop off)
- 50. Behavioral Segmenta0on 24
- 51. Behavioral Segmenta0on Grant seeker • Funded work • Mechanism • Deadlines • Funding Strategy • Reviewers • Portfolio contact 24
- 52. Behavioral Segmenta0on Which clusters of pages do people tend to visit? • Do the clusters match • up with personas? Which addi2onal pages • should people be seeing to accomplish the persona tasks?
- 54. Using Analy0cs to Validate User Research Membership benefits Auto Car maintenance Insurance tools & tips Extended Research car warranty Auto Loan
- 55. Using Analy0cs to conduct User Research A | B [|C] Tes0ng Which link makes sense to Rudy? Ruth L. Kirschstein Na0onal Research Service Award NRSA Predoctoral Grant
- 56. Performance ques0ons & measures Ques0on Measure Evaluates Which pages are most cri2cal to site Contribu2on Central content success? Seduc2ve Are visitors seeing the right clusters of Behavioral placement of things? Segmenta2on associated content Which labels / images engage best? A|B Testing Labeling
- 58. Measurable Business Objec0ves Usability Web Tes0ng Analy0cs Best Prac0ces Review 29