The Economics Of Inaccurate Location Data

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Mark Slade, CEO at Location Sciences.

It is near impossible to solve for the location data supply shortage. Only apps with a legitimate need for GPS data are permitted by operating systems to ask users for it. When apps do request location data, only about 25% to 35% of users agree to share it.

This makes location data expensive. To keep up with demand and take advantage of location data’s high CPMs, some players in the value chain loosen their definition of quality and work with less accurate data or even create the data from thin air.

Inaccurate location data inflates the market, giving an illusion of scale while compromising quality, and possibly pricing. Brands and marketers pay good money for location data. But accurate data may be worth even more. If the bad stuff is removed, supply would drop, theoretically driving prices up.

What would happen next is hard to predict. Prices might go up and marketers would pay the increase. Or prices might increase and only a few big brands would be willing or able to pay. If advertisers put their foot down, prices might stay the same.

A pricing ceiling coupled with a decrease in supply as inaccurate data is cleared away doesn’t sound good for the location data market, which could explain why some players seem just fine with keeping things murky.

But at what point does the granularity of targeting stop correlating with an increase in campaign effectiveness? It is possible that marketers can get the same campaign results without being uber-targeted. Is it a case of diminishing marginal returns for location-based targeting?

And are we increasing the granularity of our targeting because we think it will deliver success – or just because we can? Perhaps a more realistic approach to scale would not compromise effectiveness.

Quality location data is in high demand for the same reason McDonald’s takes out billboards near its restaurants: It works. But everyone – buyers, sellers, agencies, brands – needs to readjust expectations for the type of scale we can deliver against targeting perimeters. “Super hyperlocal,” or whatever the latest marketing catchphrase may be, is tough to achieve, especially outside of big platforms like Facebook and Google. We need to be honest about the market dynamics of location data, including how much targeting it takes to achieve effectiveness.

Location data is powerful. Given the predicted continued rise of mobile usage, location data is only going to become more valuable for brands looking to connect with users at a specific place and time, or to better understand users’ real-world behavior. But we need a different narrative. If location data suppliers keep telling marketers they can target people on a precise corner, at scale, but the only way to deliver that scale is to loosen quality, it is time to stop telling that story.

Follow Location Sciences (@LocationSci) and AdExchanger (@adexchanger) on Twitter.

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