Rippll seeks to clean up location data

Sobo: “It’s not that we have had bad data, just that there are a lot of smoke and mirrors in the market around location data”

Location has rightly been heralded as one of mobile’s major USPs. The fact that an advertiser knows where someone’s phone is physically located at any point in time is immensely powerful. It enables them to target an ad at a user when they are close to one of the advertiser’s physical stores, for example. Or to build up a picture of the sort of places the phone – and its owner – visits on a regular basis, to infer things the user may be interested in.

But location data is only as good as it is accurate, and according to Doug Chisholm, CEO of Rippll, there is a lot of bad – and fake – location data in the market.

“You might have a location data company offering an audience of cinemagoers, but there is currently nothing out there to tell the data buyer whether they are actually cinemagoers, or just people who work at the cinema, or live close to it, or who simply opened up an app as they passed by the cinema,” says Chisholm. “However, if you can establish how long the ‘cinemagoers’ spent in the cinema, then you can verify the accuracy of the data and the audience.”

Chisholm also has something of an issue with location data coming from the ad exchanges in general. “Every ad request has the opportunity to have lat/long attached to it and an unscrupulous app owner or publisher can make 10 times as much money by putting a fake lat/long on the request in the bidstream pushing this fake location data into the hands of unwitting ad networks and then the audiences that agencies buy from them,” he says.

Now, Chisholm is attempting to offer a solution to the problem, using Rippll’s own real-time location database to offer independent verification of the accuracy of location data an advertiser is buying. Rippll’s location data comes from around 500 apps built with the company’s SDK tools which give the app owners access to location-based analytics and push notifications. Collectively, these apps have around 2m users and generate a lot of high quality, anonymised location data. Chisholm’s plan is to use this data to allow media agencies to cross-reference the location data they are buying with Rippll’s data in order to pre-verify it and see how accurate, or otherwise it is, before launching campaigns.

The company has recently completed its first project, for MEC Interaction. Jide Sobo, head of mobile at MEC says: “It’s not that we have had bad data, just that there are a lot of smoke and mirrors in the market around location data, and when you dig deeper and start asking questions as to its accuracy, often the data providers cannot answer them. There are also some new methodologies and technologies coming into the market so we want clarity of what different partners have to offer.”

For this first study, Rippll analysed a variety of location data, ranging from IP address and bidstream to app SDK and beacon data. “We worked with the location vendors involved in a very collaborative way and in some cases helped them identify their richest sources of high quality location inventory,” says Chisholm. “Going forward, this is something we plan to offer as an ongoing service to both location vendors and media agencies.”

“We’re still doing our final analysis of the test results, but what we have already gives us much better transparency of the methodologies that our location partners are using, and will enable us to provide more robust solutions for our clients,” says Sobo.