- identify what city the user is in
- read/write user and friends’ check-in data
- look up information for a particular location
- make/send friend requests
- retrieve venue data
- perform a local search that includes information from your friends’ check-ins
- add venues, tips, and to-dos
This enables some pretty cool applications. For example, what about an AR app that shows me where all of my friends are? Or a navigation app that automatically checks in when I arrive at a location? It also opens up some interesting possibilities for advertisers. Want to create a location-aware application that can target relevant local offers – build a foursquare-aware version of Urbanspoon.
You could also use it to push foursquare data out of their own user base and to the public at large. For example, I could build an uber-app that would allow me to tell my family that I’m running late for Thanksgiving dinner, bundle in some traffic data to estimate an ETA, and push notifications out to foursquare, twitter, or even plain old SMS.
The comparisons to twitter are obvious but understated. Unlike twitter, foursquare has a historical record of high-value, targetable, structured data. It’s hard to make sense of a single twitter stream, let alone millions of them. But location data has structure – it can easily be parsed and sorted; relationships can be identified between people, locations, times – and that can be used to target advertising, tailor mobile services or even implement discretionary pricing.
Unlike twitter, an open foursquare solves a user, carrier, and advertiser problem with ready, revenue generating implications. As much as I hate to admit it, maybe Scoble was right – foursquare will be bigger than twitter.