Engagement: New Approaches for Connecting with Your Users
1. Kevin Cohn
Vice President of Operations
@Atypon
PSP Seminar, New York
11 October 2012
New Approaches for Connecting
with Your Users
Engagement
2. • Content delivery and monetization
solutions for publishers
• 13 million journal articles being
hosted by Literatum
About Atypon
2 Engagement: New Approaches for Connecting with Your Users
5. • Know who the user is
• Know what the user is interested in
• Use this knowledge to target content
to each user
What Does It Mean?
5 Engagement: New Approaches for Connecting with Your Users
6. A Lack of Targeting
Paid Content User Targeting
Scientific &
Scholarly
Yes No
Consumer &
Trade
No Yes
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7. Today: < 1%
7 Engagement: New Approaches for Connecting with Your Users
9. • Incentivize users to register
• Lower the registration barrier
• Keep users logged in
• Target content to users
Engagement in 4 Steps
9 Engagement: New Approaches for Connecting with Your Users
10. • Free to registered users only
• Require registration to access
enhanced content
• Metered model
Incentivize Users to Register
10 Engagement: New Approaches for Connecting with Your Users
11. 51M denials in 2011
Atypon-Hosted Publishers
11 Engagement: New Approaches for Connecting with Your Users
14. • 1Q10: Launched
The New York Times
• 2Q11: 224,000 paid digital subs
• 2Q12: 509,000 paid digital subs
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17. • Ask for less information on your
registration form
• Allow users to register using social
network accounts
Lower the Registration Barrier
17 Engagement: New Approaches for Connecting with Your Users
19. • “Remember me”
• Social network accounts are
“always on”
• “Secure key” authentication
Keep Users Logged In
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20. • You’ve created reasons to register
• You’ve made it easier to register
• Users are registering
• You’re keeping users logged in
Engagement in 4 Steps
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23. • Binary: a document is either about a
topic (100%) or it is not (0%)
• Hierarchical: a document is about a
topic and all of its parents
Taxonomies
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25. • Better related search and content-
based recommendations
• Search results clustering (“more
results like this”)
Applications
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28. • Better networking and user-based
recommendations
• Search results ordered by
relevancy to each user
Applications
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29. • “Research Intent”
• Apply different weightings to
different rolling periods
Tuning
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30. • Know who the user is and what the
user is interested in
• Use probabilistic enrichment to
target content to each user
Summary
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