It’s not everyday that you join your competitors to give advice to media buyers who you’ll likely compete for down the road. But the Interactive Advertising Bureau’s (IAB) commitment to sharing best practices and thought leadership led to the creation of the IAB Location Data Working Group, 26 expert companies united to furthering the mobile advertising ecosystem. PlaceIQ welcomed the opportunity to participate and is excited to empower media buyers to better recognize high quality, accurate location data.
The result of this industry-wide collaboration was a 12-question guide that advertisers, agencies and marketers can reference when exploring location-based digital marketing and selecting a mobile ad provider. Each question digs deep into the components that dictate the speed, accuracy and ROI of mobile ad delivery within a campaign. The 12 questions are split evenly between two categories: “place data” and “device data.”
The place data questions in the Buyer’s Guide revolve around the source, precision, and verification process of fixed locations in the physical world – such as a baseball field. While the status quo across the ad tech space is to rely on basic geo-fencing and licensed map data to locate these places, we want to pinpoint locations, not just get in the vicinity. So our internal cartography team draws polygons by hand on real-world locations – such as your neighborhood grocery store. That way all data sets on our 100-meter by 100-meter grid, which spans the United States, are truly targeted.
The device data questions are similar in their investigation of: type of location data, filtration methods, and data accuracy, but different in that they refer to the location of a user’s devices – which may be at a baseball diamond now, and a grocery store two hours later. For this half of the questions we rely on the work of our data science team and an analytics pipeline that rigorously evaluates the quality of location data within ad requests.
Because we know that opt-in data is the highest quality location information available, it is the only type of location data that PlaceIQ utilizes. To achieve this, we take data filtration further and selectively remove bad data points that don’t reflect normal human behavior, are clearly computer generated, or are artifacts of location data infrastructure. For you visual learners, here’s what we’re talking about:
In this example it doesn’t take a data scientist to recognize that these data points are unnaturally dispersed (left) and hyper clustered (right). These data points are far too organized to reflect the randomness of human movement patterns, and therefore must be removed.
We’re proud to have helped put together the IAB’s Mobile Location Data Buyer’s Guide, and to further the mobile ad tech ecosystem by educating current and future media buyers. While filtration and verification isn’t the sexiest part of what we do, not asking these questions could be detrimental to your mobile ad campaign.
To download the guide, please click here. And if you missed our panel at today’s IAB Mobile Road Show in Chicago, we’ll also be presenting at the NYC stop on the Road Show, on August 21.