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As Location-Ads Become More Popular, Targeting Accuracy Suffers

How precise is the location data connecting mobile ads and consumers? Not very, it seems. Thinknear is starting to keep score.

Thinknear GM Eli Portnoy
Thinknear GM Eli Portnoy

The promise of location-based advertising is clear and simple: consumers get ads sent to their mobile, connected devices when they appear to be in the close vicinity to a marketer’s physical business or service. But as the demand for technology associated with gathering and employing location data has risen quickly from advertisers, publishers, ad networks, and other online marketing players, the noise created from all that usage has drowned out quality results, according to a report from hyperlocal mobile ad net, Thinknear. Read the release.

Billed as the first tool to measure the mobile ad market’s capacity to connect advertising and a portable device based on its real-time position on a map, Thinknear initially built the Location Score for internal purposes, says Eli Portnoy, the company’s GM. The goal was to have a wide-angle view of how effective location-based ad campaigns were, so Thinknear would have a better sense of its own offerings and targeting acuity. But rather than keeping it for competitive advantage for clients — though, to be sure, most of the the company’s expanding troves of data remain behind closed “proprietary” doors.

With location-targeting becoming more mainstream, Thinknear believes that releasing a quarterly index detailing how well (or poorly) the industry’s performance is in hitting the right “lat/long” marks on mobile phone maps could help it influence the landscape.

And to start, Thinknear’s message to the industry about the current shape of geo-targeting: it could be doing a lot better. On a 100 point scale, the Location Score for the mobile ad industry—across Apple’s iOS and Google’s Android—was 49.  This translates to the true location of a mobile user only being accurate to within 100 meters a mere 34 percent of the time.

Missed Targets

There’s a great deal of discussion about reducing waste in online advertising lately. Whether it’s reducing the amount of impression fraud coming from botnets or trying to determine the right mix of metrics that will lead to clear ROI, the digital ad space is under pressure to show its ability to make good on its promises to deliver and account for an exact amount of unique impressions, as well as to behaviorally target and wield geo-data more narrowly.

In terms of giving marketers better visibility into the effectiveness of the ge0-data used on their campaigns, accuracy is measured on scale of 0-to-100 points. The technology uses Thinknear’s platform to count the difference between a mobile user’s stated location (per an ad request) and the true physical location of the user.

The breakdown from the report offers a fuller picture beyond the fact that less than half of location-based campaigns delivered on their target:

  • 67 percent of industry ad requests included latitude and longitude data
  • 34 percent of ad requests with location data were accurate to within 100 meters of the user’s true location
  • 45 percent lift in mobile time-on-site metrics for campaigns leveraging top tier location data
  • 30 percent to 51 percent lift in store visitation rates fore campaigns leveraging top tier location data

For volume by accuracy level, Thinknear drilled down on five tiers of location accuracy:   34 percent of ad requests were considered “Hyperlocal” and were accurate within 100 meters of a user’s actual spot; 9 percent were “Local” with accuracy rate between 100- and 1,000 meters of a person’s true real-time location; 30 percent were Regional (accurate within a range of 1,000 to 10,000 meters); 20 percent were Multi-Regional (accurate within 10,000 to 100,000 radius around a consumer’s signal source); and 7 percent of ad requests were “National” meaning the location meaning the data was only accurate enough to determine the user was in the U.S.

Portnoy’s Complaint

When asked what are the chief reasons for the lack of quality targeting for location-ads, Portnoy pointed to the success the industry has had in developing such wide attraction for its tools. For example, two years ago, roughly 10 percent of all ad requests contained geo-data; this year, the number of requests has been closer to 67 percent — a dramatic increase. As advertiser demand for location data has grown, so too has the number of publishers, ad networks, and other inventory sources willing to share location data.

Is this flood of new location data good for the industry? It all depends on the quality of the data.

Apart from the intensifying interest by marketers, the technology for figuring out where a consumer and their smartphone happen to be has also lagged demand. As Portnoy explains, a publisher generally has to take five steps to access a user’s location — and each one is less accurate than the next. The most reliable method of extracting precise location is with the A-GPS (assisted global positioning) chip in a connected device. A Wi-Fi signal is second strongest — but since most people use networks at home or work, as opposed to walking or driving near a retailer, it’s not terribly effective.

Cell towers are ubiquitous in most areas, but in places with many tall buildings like New York, interference with the location signal is common. And while IP addresses are great for serving websites, when it comes to pinpointing an individual phone in a large area, they almost always miss the target. The award for the worst method of gleaning location data, however, goes to apps that ask for user registration. In this case, a developer asks for a zip code when a person downloads their app. But that zip code is centered around their home or work and therefore has no way of finding that person as they go about their day.

It sounds dispiriting, but Portnoy anticipates that geo-marketers will catch up quickly.

“I think it’s going to get a lot better,” he says. “One of the things that we did was create a location score card for every one of our inventory partners. We shared it with them and basically the point is to show, ‘Hey, you’re at 62, the industry’s at 49.’ Or, ‘You’re at 33, and the industry’s at 49.’ We’re actually giving them a concrete set of things that they can do to improve their score. Our goal is that by bringing visibility to it and also providing the sources with additional information about how can they take and improve it, the industry will move forward. I’m very confident that the next time we publish the report, the number will definitely be above where it is today.”