Thinknear’s Portnoy on Scoring Accurate Location Data
In the world of location marketing, precision matters. In a presentation at Street Fight’s Local Data Summit in Denver on Tuesday, Thinknear GM Eli Portnoy described how location data is derived and how it can be improved.
Portnoy began by explaining the difference between location targeting and location data, telling the audience that location targeting can be used to get a better picture of the type of person who is likely to be in a location at a specific moment. Location data, on the other hand, offers insight into whether a person who is going to see an ad is actually at a specific location right now.
“Location data is the data that’s actually coming from the device itself, that’s telling you where the person is,” he said.
As marketers pull in more data, they’re able to get a clearer picture of the type of person who is in a location at a specific moment. However, Portnoy said it’s important that marketers get their location data right. Without accurate location data, any targeting data that a marketer collects is wasted.
Mobile application developers have a huge incentive to collect location data from users — but wanting to have accurate location data and actually having that information are two different things. There are a number of restraints — including user permissions and clear lines of sight — that make it difficult to obtain good location data. Although 70% of mobile impressions come with latitude/longitude information, Portnoy has found that the data provided by publishers is often wrong. Only 32% of impressions are accurate within 100 meters, and 26% of the impressions measured by Portnoy’s team were off by 10,000 meters.
In measuring conversions, Portnoy found a massive dropoff after 1.5 miles. Beyond that point, people just don’t convert, he said.
Portnoy has worked on a number of successful location campaigns, one of which targeted frequent business travelers who had been in an airport five times in the past month. Another campaign, for Benedryl, used local pollen counts to talk to consumers in high allergy areas. “Location helps you [generate] really targeted messages based on context,” he said.
So, what’s the secret to securing accurate location data? Portnoy covered the process of location scoring to eliminate centroids and recommended that businesses start looking at the ratio of impressions in any given area compared to neighboring areas. If one area has significantly fewer impressions, then that is likely the result of latitudes/longitudes being derived in-organically. Manual publisher audits are also an effective way to secure more accurate location data, however the method that Portnoy really recommends is experimentation.
“Run all types of experiments,” Portnoy said. “Ultimately, it’s about caring really, really deeply about location data. It’s really important to understand it really deeply.”
Stephanie Miles is an associate editor at Street Fight.