LocalResponse, which soft launched two weeks ago, aggregates more than 1 billion check ins per month from 200 million different users across a range of services like Facebook, Twitter, Foursquare, Instagram and more. It breaks that data down and makes sense of it so business owners can target different kinds of customers in specific locations.
The service debuted for local merchants and today it announced the second half of its business, a platform that will allow big brands to target users with deals based on this data. “We’re effectively using the “check-in” as a proxy for behavioral and location-based targeting,” says Nihal Mehta, CEO and Co-founder. “There’s finally significant reach and scale in this medium, and we’re excited to connect brands and agencies to it.”
It’s also important because LocalResponse is free for small business, but will charge national brands. Kathy Leake, former founder and CFO of Media6Degrees, will lead the branded efforts as President.
LocalResponse is a pivot from the folks at Buzzd, who built a city guide based on the same concept, aggregating data from different services to help users figure out what locations were trending nearby or relevant to them. Rather than compete head on with the consumer facing check in services like Foursquare and Facebook, the company is now trying to monetize that activity by making it useful to the enterprise.
“Our data is more valuable to local merchants and brands than to the consumer,” says Mehta. So for example Webster Hall would use Localresponse to see everyone who was checking in and perhaps offer up a free drink to users who shouted out the concert to friends or public feeds.
In a smart move, LocalResponse went beyond the standard check in services when building out their network of data points. A check in on Foursquare requires me to select a specific venue first, it’s explicit about the location. Folks can also attach location data to Twitter posts, but more often users just provide a status update on those two services. So in addition to reading obvious locations, LocalResponse tries to analyze natural language from simple phrases like, “I’m heading to Madison Square Garden!” and extract useful information about where users are.
The danger behind a service like this is that users will get fed up with a flood of push notifications about deals, especially from big brands, which won’t be offering as unique a location based experience. So Localresponse has decided not to send more than one message per day from its advertisers and just one message per week from any specific brand or business. The more accurate and timely the offers, the less chance users will begin to experience stalker syndrome.