1. Devise a way to look for patterns in social network communications/comments to predict when a consumer might be looking for a specific type of good (i.e. a House, Car, etc)
    2. This data could help forecast future sales, or help our agents/broker prospect through their social connections.
    3. Could help agents find people in certain areas who may be willing to sell their home, etc.
    4. Could look for buying signals like job changes or promotions on LinkedIN, or specific types of comments on Facebook, or wishful posts on Instagram , etc.

Use Cases:

  1. User posts to Linked on or Facebook that they are moving to a new city for a job. Agent has an app/website that they see this and can actively contact the user to see if they are looking to buy/rent a property. 
  2. User starts posting details about needing a change of scenery or how much they are wanting to change their surroundings/environment and Agent can pick up on these and actively canvas for potential move. 
  3. User posts how much they hate their car, how much it`s costing to repair/upkeep, or how much they like the newest model of something. Pick up on this and allow a report that will prompt a dealer/agent to actively contact them about buying a new one 
  4. User has been talking a lot about remodelling and has posted numerous articles on Snapchap, Instagram, Facebook with ideas, styles, etc. Agent sees the analysis that they are possibly wanting to consider a new house that might cover these ideas and allows them to target them with all the ideas incorporated in that new property. 
  5. You might want to basically build a Facebook listing widget; so that if we think someone might be a good candidate to buy a new home – or look for one – then you can push listings to their feed.

    Or maybe create a HomeShare (automatically) that posts to the user’s wall / FB messenger or something (or gets emailed) with Homes you might like; based on the profile of the user.




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