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Location based social networks are suggestion engines
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Location based social networks are suggestion engines

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  • This is where Bob Solish is going to work
  • This isn’t a shiny new thing. This is a search engine designed to pull data into one place. A list of things my community likes. A Suggestion engine that pulls suggestions from Facebook and FourSquare into one place. This is where things are going for people.
  • Transcript

    • 1. The rise of suggestion engines
    • 2. Early Internet
      • Before Larry Page and Sergey Brin created Google, search engines based results on the number of times a search term appeared on a page.
      • The results weren’t always good.
    • 3. The switch
      • About 3.7 billion people actively use about 4.3 billion mobile phones.
      • They use them to create massive amounts of content on location.
      • But Google doesn’t always return the best place to get a vegan cupcake.
      • For that, I require something else.
    • 4.  
    • 5. Location based social networks
      • FourSquare
      • Facebook places
      • Google Latitude
      • Twitter places
      • Gowalla
      • Whirl
    • 6.  
    • 7. Location based social networks
      • In 2010, FourSquare had 381 million different check-ins
      • All people with a Facebook App have Facebook places.
      • These are suggestion engines: search engines for getting suggestions.
    • 8. Location based social networks
      • Yelp
      • Google Earth
      • Facebook
      • Twitter
      • FourSquare
      • These are all places where one can get “Suggestions” on where to eat, drink, stay, vacate, etc.
    • 9.  
    • 10.  
    • 11.  
    • 12.  
    • 13.  
    • 14.  
    • 15. These are suggestion engines
      • To turn people’s suggestions into searchable engines, properties need to incent people to check in and leave tips using:
        • Game mechanics
        • Badges (rewards)
        • The reward of getting followed (being a go to resource)
        • Pulling data when you need it (what friends have left tips around here)
    • 16. What can brands do?
      • Understand the underlying dynamic.
      • Facebook, FourSquare, Yelp, etc are all trying to incentivize check ins because there aren’t enough brand offers.
      • Offers are the best reason to check in, but properties can’t make brands give offers.
    • 17. Examples of good ones
    • 18.
      • Brands that do get on board, can succeed in a world of check ins because all the properties are trying to build suggestion engines.
      • An offer is a reason to give a suggestion.
    • 19. In conclusion
      • We’re on the cusp of user-check ins.
      • But maybe we should call them suggestion engines.
      • It sounds like another buzz word, but instead of thinking about FourSquare, think bigger.
    • 20. Question to ask
      • Instead of thinking about offering deals, think about Optimizing for Suggestions.
      • Make it easy for people to suggest and review
      • Make sure there is a plan to interact with people who suggest or review.