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.
34. Addi0onal Measures ‐ Engaged Visits
Engage &
Attract Commit Convert
Persuade
engaged
Engaged Visits = # site visits that move N* pages into the site
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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
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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
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37. Addi0onal Measures ‐ Persuasion Index
Engage &
Attract Commit Convert
Persuade
persuaded
Persuasion Index* = Commieed visits / Visits to PageX
*This is a page level measure
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41. What are we measuring?
Engage &
Attract Commit Convert
Persuade
Persuasion Usability Conversion
Engagement
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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
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)
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?
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