Beyond who else bought what

Beyond Who Else Bought What
Andraz Tori, CTO
[email_address]
Twitter: andraz

Overview
Why recommend anything?
Reader / Author recommendations
Simple tricks
Advanced solutions
Demos & Results
Q & A

Why recommend?
Recommendations
=
Contextual advertising
->
Monetization

Why recommend?
Recommendations
=
Navigation & steering
->
Monetization

Why recommend?
Recommendations
=
Navigation & steering
->
Pageviews
->
Monetization

Why care as a publisher? Readers
Direct monetization
Steering -> pageviews -> monetization
Better service (example: hiding spam)

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)

What if recommendation goes wrong?

It will go wrong!

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

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

How do I do it?
Simple tricks
Ready-made web solutions
Third party APIs
Roll your own

Simple tricks
Display random photos for UCG author to start with
Allow for quoting shortcuts (reblog)
Show writer's interest feed in post compositor

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

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

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

Demos
Tagaroo
Zemanta
Kaalga
Left out: Non-serendipity solutions

Tagaroo 1
Discovers interesting keywords, offers links on click

Tagaroo 2

Tagaroo 3

Tagaroo 4

Zemanta
Live Demo

Kaalga

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

Resulting in
Better positioning of your authors in the community
More affiliate monetization
Some bloggers 10-15% traffic increase

Issues
Tower of Babel
Some users are overwhelmed
GUI is 80%

The next web?
Understanding content more and more
Understanding the social context
First the advertising world was hit
Now this will trickle into publishing

What if
Your computer understood what you are writing about
Know who you know, what you know
Know what you don't know

How would your text editor look like? How would your text editor look like? How would your writing assistant look like?

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

Q&A
Andraz Tori
[email_address]
Twitter: andraz

http://en.oreilly.com	316
http://www.web2expo.com	88
http://www.open.ac.uk	10
http://flowr	9
http://blog.slideshare.net	5
http://www.centrestage.de	3
http://mayank.name	1
http://berlinblase.de	1
http://www.elsua.net	1

Beyond who else bought what

by Andraz Tori on Oct 21, 2008

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Beyond who else bought what — Presentation Transcript