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.