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.
  • Location based social networks are suggestion engines

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