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appESP goes gold
 

appESP goes gold

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    appESP goes gold appESP goes gold Presentation Transcript

    • by
      October 2010
      Chris DeVore, CEO + co-founder
      chrisd@appstorehq.com
      http://www.appstorehq.com
      (206) 801-1080
      1
    • App discovery is a hard problem;Android Market isn’t helping
      “ Discoverability is a problem that has long plagued the world of mobile applications. The issue worsens with each new title added to Apple’s App World and Google’s (not-yet-as-massive) Android Market.
      …the problem of discoverability will only
      grow worse before getting better. ”
      Colin Gibbs, How Carriers Can Crack the App Discoverability Nut, GigaOm, Oct. 9, 2010
      2
    • App discovery engine for Android*Personal, social, on-device
      Automatic
      no user input required
      Personal + Social
      informed by your – and your friends’ – currently installedapps (social data via Facebook Connect)
      Relevant
      statistically generated app-to-app affinities based on install/uninstall data among all participating users
      individual recommendation sets enhanced with fresh AppRank* + social data for maximum relevance
      Always on
      handset app data is polled daily
      recommendations are recalculated several times/day
      background notifications are delivered weekly (or at user-defined intervals)
      *appESPrecommendations engine and methodology are patent-pending IP created by AppStoreHQ. See Appendix for AppRank methodology details.
      3
    • 1
      How does work? (1 of 4)
      2
      Install + opt-in
      Acquire data
      User installs application, opts-in to background (on-device) app discovery and registers at AppStoreHQ
      AppESP polls on-device memory for currently installed applications and passes that data securely to AppStoreHQ servers
      4
    • 4
      3
      How does work? (2 of 4)
      Find patterns
      Recommend
      Statistical relationships among apps are identified via a “collaborative filtering” algorithm (the same approach used by Amazon and Netflix to generate product recommendations)
      We generate individual sets of app recommendations for each user, with a “boost” applied for:
      Apps with high current AppRank score, and
      Apps used by friends (for users who register via Facebook Connect )
      5
    • 5
      How does work? (3 of 4)
      Discover…
      Users are notified of new recommendations via the on-device Notifications shutter
      Recommendations can be tuned via the “Like / Dislike” buttons shown in the app detail view
      Users buy recommended apps directly from Android Market or other approved source
      6
    • 6
      How does work? (4 of 4)
      …with friends
      Facebook is built into appESP’s user-experience and recommendation engine.
      Each user’s social graph is mapped and used to boost app recommendations.
      appESP also shows users what apps their friends have installed and liked.
      7
    • product status
      Production app available now
      Go to http://www.appesp.com or search for “appesp” in Android Market
      Fresh app recommendations are being generated daily based on:
      1B+ app-to-app relationships
      200K+ app-to-content matches
      50K+ individual user profiles
      The appESP recommendations engine is also available to authorized licensing partners via cloud API
      AppStoreHQ is actively seeking distribution partners for the AppESP engine among leading wireless, retail and consumer media players
      8
    • Company Details
      Company: Mobilmeme, Inc.
      Location: Seattle, WA
      Founded: April 2009
      CEO: Chris DeVore, chrisd@appstorehq.com
      CTO: Ian Sefferman, iseff@appstorehq.com
      Lead Investor: Founders Co-op (Seattle)
      9
    • APPENDIX
      AppRankSM by
      10
    • 2
      1
      How does AppRank work? (1 of 2)
      Continuously index Android Market to maintain a current database of all published apps
      Monitor hundreds of online publishers, plus social streams like Twitter and Facebook, to identify influential reviews and commentary about Android apps


      11
    • 4
      3
      How does AppRank work? (2 of 2)
      Follow every link in discovered content – including shortened URLs and redirects – to match app mentions to published apps
      Several matching approaches are used, including:
      • Android package name
      • Developer website URL
      • AppBack widgets
      • Manual validation
      Several times a day, force-rank all listed applications based on an algorithm that takes into account:
      • The number of discovered
      mentions for each app
      • The relative authority of each
      mention (using both 3rd-party
      sources and internal quality
      scoring methods)
      • The recency of each mention
      (adding decay so older mentions
      matter less than new ones)
      12