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Discovery is the new cocaine Going beyond engagement By: Ming Yeow Ng, Yu-shan Fung (Discoverio) Note: Section on “ Flow ” was derived from  “ The Science Of Designing Interactions” (SXSW 2008)  by Andreas Weigend (people and data), and Ming Yeow Ng (Discoverio)
Why should you care about Discovery? ,[object Object]
What is it about a Web site that might make it  literally irresistible ? ,[object Object],[object Object],[object Object],[object Object],Source: WSJ, Why We're Powerless To Resist Grazing On Endless Web Data March 12, 2008
Done right, Discovery can make a website irresistible! ,[object Object]
Desire by humans to be a  live node  in the network ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Source: Etech 2006
What is Discovery? ,[object Object],[object Object],[object Object],[object Object]
Discovery of Information New  and  Richly interpretable  information triggers chemical reactions ,[object Object]
Twitter, Friendfeed: Constant stream of new information ,[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
Get Discovered by Others “ Who is paying  attention  to me?” “ Am I being  recognized ?” ,[object Object]
MyBlogLog Who is checking me out? ,[object Object],Twitter Who is following me?
Discover More About Themselves “ Who am  I  to  others ?” “ What do I  like ?” ,[object Object],Key here: People  do not know  what they want!
Tickle: What am  I ? (400 million personality tests taken) ,[object Object],The New Personality Test What am  I  to  others ?
Amazon : Collective Recommendation ,[object Object],Stylefeeder: Analyzing attributes
Facilitate the  Discovery Cycle  for your users ,[object Object]
[object Object],Continuous Learning, Contributing, Recognition Engage and allow contribution of  information , leaving of  footprints , and giving of  feedback 2) System to generate new insights for user 1) Discovery of  Content and Users 3) Other Users to discover him Data becomes basis for: Personalized  Recommendations Interactions  that lead to reciprocity and interactions User learning more about himself Throughout the process: (Keeps him coming back!) Meaningful connections gets established
“ Intermittent Variable Reinforcement  “ ,[object Object],[object Object],Done right, this leads to
Discovery is less about  predicting precisely  right about what the user wants  It is more about the entire  user flow of discovery , with all the hits and misses ,[object Object],Think window shopping down the mall or walking through an expo hall
Discovering Activity by Social Graph Based on live updates My good  friend The guy with  great events The babe I  check out Based on collective behavior  and attention data
Collective Judging Collective Behavior
No concept of individual Personalization
Crowdvine: Updated profiles, comments are on front page Helping users get discovered Clear attention/intention data Crowdvine: want-to-meet, fan
Apache Social Network: Open source projects worked on together ,[object Object]
Exploitation Exploration
Connecting based on mutual interest
[object Object],Flickr:  Interestingness Etsy:  Many ways to shop
Etsy: 10 different fun ways to discover! (boring categories are at the end)   ,[object Object]
Understanding the elements of “flow” Feedback, Rewards, Lightweight, Reducing uncertainty ,[object Object],Inspired by Mihály Csíkszentmihályi
Direct and immediate feedback Successes and failures in the course of the activity are apparent, so that behavior can be adjusted as needed ,[object Object]
Feedback can be by system or can be by other users ,[object Object],Metrics for: Maslow Hierarchy Contribution to  others Achievements Popularity Wrong-doings
Yelp: popularity, achievement, and contribution ,[object Object]
Cash = power Value = desirability ,[object Object]
Linkedin Profile Completeness  Pointing out “deficiencies” to induce actions ,[object Object]
Rewards Intrinsically Rewarding Clarity of Reward Recognition for contribution ,[object Object]
Twitter: Self Expression is its own reward ,[object Object]
Twitter: Validation, and Social Interaction are powerful rewards by themselves ,[object Object]
[object Object],Digg:  Made popular by… Crowdvine:  Updated profiles, comments are on front page
Best Match: Invite 10 to see “best matches” ,[object Object]
GetSatisfaction: I have this question too! ,[object Object]
Lightweight Interactions Make it easy for users to contribute ,[object Object]
Crowdvine: Fan : expression of confidence Want-to-meet:  initiate relationship ,[object Object],Yelp:  Variety of lightweight interactions directly on reviews
Lijit: Made the process entertaining and a little mysterious, with rewards at each step ,[object Object],Signup Time 15m  ->  2m Conversion 0.1% ->  4% Source: Lijit, SXSW 2008 Automated retrieval of external data, all user needs to do is confirm
Woot: One Single Action ,[object Object]
Reducing fear and uncertainty Uncertainty, even irrelevant uncertainty kills action ,[object Object]
Twitter: Communicating with little fear of incurring cost to recipient ,[object Object]
Zoosk: Flirt vs risk ,[object Object]
HotorNot: No risk of “rejection” ,[object Object]
Crowdvine: Showing social behavior right on frontpage ,[object Object],Latest Comments
Day Trading ,[object Object],MMORPG ,[object Object],[object Object],Source: "Ariadne - Understanding MMORPG Addiction"  Nick Yee
Systematically Introducing Discovery Into Your App  (uncompleted) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Process by Ming Yeow Ng, Yu-shan Fung (Discoverio)
We LOVE Feedback!!! ,[object Object],[object Object],[object Object],[object Object]

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Discovery Is The New Cocaine - Going Beyond Engagement

  • 1. Discovery is the new cocaine Going beyond engagement By: Ming Yeow Ng, Yu-shan Fung (Discoverio) Note: Section on “ Flow ” was derived from “ The Science Of Designing Interactions” (SXSW 2008) by Andreas Weigend (people and data), and Ming Yeow Ng (Discoverio)
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  • 19. Discovering Activity by Social Graph Based on live updates My good friend The guy with great events The babe I check out Based on collective behavior and attention data
  • 21. No concept of individual Personalization
  • 22. Crowdvine: Updated profiles, comments are on front page Helping users get discovered Clear attention/intention data Crowdvine: want-to-meet, fan
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  • 25. Connecting based on mutual interest
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