Street Fight’s recently published white paper, Hyperlocal Targeting on the Mobile Platform, takes an in-depth look at the emerging mobile-local landscape and lays out best practices for marketers to get the most out of location on mobile. The following is a modified excerpt from the paper.
The success of any mobile targeting campaign hinges, entirely, on the location data powering the messaging that is pushed out to consumers at just the right time in the right place. But this holy grail, while making great strides, is still facing great challenges. Its biggest hurdle lies in the quality and accuracy of this data, as an influx of embellished and incorrect location data is pumped into ad networks and exchanges by publishers looking to cash in on rising premiums for hyperlocal inventory.
The amount of location-enabled inventory available to marketers on display networks and exchanges has skyrocketed. Between August and December 2012, mobile advertising exchange Nexage reported a 33% month-over-month increase of location-enabled impressions (includes inventory with lat/long, zip code, or city-level location information) on its platform.
Nexage chief marketing officer Victor Milligan attributes the jump to publishers recognizing the increasing premium that marketers pay for hyperlocal inventory. Milligan says the growth is coming from more mobile publishers who were already collecting location data deciding to pass the information to advertisers, an increase in publishers using a device’s IP address to determine a user’s location, and a general growth in location-based applications and services.
“To pass location data, there are technical, business policy, and privacy considerations playing out,” Milligan says. “As the industry has matured, publishers have started to recognize the underlying value that collecting location data would provide them.”
Location inventory comes in two forms: hyperlocal inventory, which includes latitude-longitude data, and location-enabled inventory, which includes either lat-long or geographic information such as a city or zip code. A study of Nexage’s network released in December found that advertisers paid twice the run-of-network CPM for location-enabled inventory, and three to five times that for hyperlocal inventory.
According to Milligan and others, some publishers have also started to aggressively embellish location information they pass on to advertisers. These publishers transform less valuable geographic information such as a city or zip code that publishers generate from registration and IP lookup into more valuable lat-long coordinates masquerading as a user’s current location. Publishers create the so-called “dirty data” by using software to find the geographic center, or centroid, of a zip code or city, and then pass the lat-long of that centroid to an advertiser.
The race to scale mobile advertising networks and exchanges has only partially solved the dirty data problem. Screening processes meant to detect dirty location data often toss out a majority of ad requests. David Petersen, CEO at Sense Networks, a mobile display advertising company specializing in location data, says the firm’s algorithms regularly filter 70% of the impressions from major exchanges that include a user’s latitude and longitude.
For marketers, that means up 70% of their ad buys may show up on mobile user’s devices in the incorrect location. With location-based ad inventory priced at a premium, overlooking such problems could break the bank for little return.
Marketers don’t have to be at the mercy of bad data. A number of vendors can help marketers sniff out embellished or inaccurate data using machine-learning algorithms to identify lat-longs commonly derived from a centroid. Advertising networks also have a small advantage over ad exchanges in that they can work directly with a publisher to ensure that only quality data gets passed along.
Steven Jacobs is Street Fight’s deputy editor.