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Beyond who else bought what

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Helping authors by recommending stuff to improve their content

Helping authors by recommending stuff to improve their content

Published in Technology , Design
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Transcript

  • 1. Beyond Who Else Bought What
      • Andraz Tori, CTO
      • [email_address]
      • Twitter: andraz
  • 2. Overview
    • Why recommend anything?
    • Reader / Author recommendations
    • Simple tricks
    • Advanced solutions
    • Demos & Results
    • Q & A
  • 3. Why recommend?
      • Recommendations
      • =
      • Contextual advertising
      • ->
      • Monetization
  • 4. Why recommend?
      • Recommendations
      • =
      • Navigation & steering
      • ->
      • Monetization
  • 5. Why recommend?
      • Recommendations
      • =
      • Navigation & steering
      • ->
      • Pageviews
      • ->
      • Monetization
  • 6. Why care as a publisher? Readers
    • Direct monetization
    • Steering -> pageviews -> monetization
    • Better service (example: hiding spam)
  • 7. Why care as a publisher? Writers
    • Less non-creative workload
    • Gratification -> more and better conent (especially UCG authors)
    • Steering the authors (getting trackbacks, becoming part of the community)
    • We get better metadata (more chances for distribution / repurposing)
  • 8. What if recommendation goes wrong?
  • 9. It will go wrong!
  • 10. What if recommendation goes wrong?
    • Can it do damage?
    • How much is too much?
    • Whitelists & blacklists
    • Make author act as a filter/an editor
    • And at the same time offer him value
  • 11. How is it done?
    • Based on previous behaviour of this and other users
    • Based on understanding of the data being dealt with
    • Random
    • Combination of the three
  • 12. How do I do it?
    • Simple tricks
    • Ready-made web solutions
    • Third party APIs
    • Roll your own
  • 13. Simple tricks
    • Display random photos for UCG author to start with
    • Allow for quoting shortcuts (reblog)
    • Show writer's interest feed in post compositor
  • 14. Ready-made solutions
    • Tagaroo
      • WordPress server-side plug-in
    • Zemanta
      • Server or client side (wordpress.com, blogger.com, TypePad, WP, MT, Ning, LiveJournal, MySpace, DotClear, Drupal , Tumblr)
    • Kaalga
      • Firefox extension
  • 15. APIs you can use
    • Yahoo term extractor, BOSS, Flickr
    • Calais (tags, entities)
    • Zemanta (tags, images, in-text and related links)
    • Web services, free, commercial use allowed
  • 16. So you want to be a hero?
    • Entity extraction
    • Classification
    • Use open source libraries!
    • Content access APIs (Flickr)
    • Indexing, use Lucene and Solr
    My advice: just don't
  • 17. Demos
    • Tagaroo
    • Zemanta
    • Kaalga
    • Left out: Non-serendipity solutions
  • 18. Tagaroo 1
    • Discovers interesting keywords, offers links on click
  • 19. Tagaroo 2
    • Discovers interesting keywords, offers links on click
  • 20. Tagaroo 3
    • Discovers interesting keywords, offers links on click
  • 21. Tagaroo 4
    • Discovers interesting keywords, offers links on click
  • 22. Tagaroo 4
  • 23. Zemanta
    • Live Demo
  • 24. Demo
  • 25. Kaalga
    • Discovers interesting keywords, offers links on click
  • 26. Steering authors
    • Inter-links to your own properties
    • Links to relevant sites (becoming part of communities)
    • More images are used, less worries about „google images syndrom“
    • More linking to affiliates
    • More tags, categories
  • 27. Resulting in
    • Better positioning of your authors in the community
    • More affiliate monetization
    • Some bloggers 10-15% traffic increase
  • 28. Issues
    • Tower of Babel
    • Some users are overwhelmed
    • GUI is 80%
  • 29. The next web?
    • Understanding content more and more
    • Understanding the social context
    • First the advertising world was hit
    • Now this will trickle into publishing
  • 30. What if
    • Your computer understood what you are writing about
    • Know who you know, what you know
    • Know what you don't know
  • 31. How would your text editor look like? How would your text editor look like? How would your writing assistant look like?
  • 32. The next web?
    • ... will be like a great party host , introducing us to each other and bringing us together into meaningful conversation.
                    • Marta Strickland, Organic
  • 33. Q&A
      • Andraz Tori
      • [email_address]
      • Twitter: andraz