For marketers, the concept of targeting ads is not new. Sure, it’s more of a science today, but for decades, media buyers placed print ads and bought televisions spots based on who they envisioned would consume the media. During the late 90’s, that could mean running a spot on MTV to reach teens, or putting a Viagra ad in a golf magazine to reach ‘men of a certain age.’ The online platform introduced interactivity, and loads more data, forcing marketers to rely on software, not people, to find a message’s intended audience.
Now, marketers are rushing to grapple with a new medium in the smartphone, struggling to understand what audience means in the mobile age. In considering audience on mobile, marketers need to understand the constantly changing context of a user and the implications it has on the needs and attitudes of the consumer. A mobile user reading ESPN or browsing Complex, isn’t just a sports fan or millennial male; they’re also a teenager on their lunch break, a father coming home from work, or millennial heading out at night. To discern that context, marketers need to listen to all the signals a smartphone provides, the most important of which is undoubtedly location.
Unearthing context is a not a trivial process. Location, as a measurable piece of information, is complex. Material privacy concerns limit what advertisers can access, and technical implications like battery drain limit the breadth of data publishers can access. Meanwhile, location data requires massive amounts of contextual information to turn a latitude-longitude into a meaningful audience for a marketer.
That’s where geo-fencing comes in. Over the last few years, marketers have turned to the geo-fence as a first step to begin to take advantage of the mass of location data, which has started to flow through ad networks and exchanges. The problem with geo-fencing is that it’s only about place: geo-fencing is a great way to target a location (e.g. geo-target), but it’s a poor method for understanding a user, and his or her context.There’s an easy corollary to print targeting: We’re going to place ads in said magazine or said place, because that content or place tends to draw a certain audience.
Recognizing its limitations, the industry has shifted. Over the past 18 to 24 months, companies have started to aggregate massive amounts of information about locations, using this data to create audience profiles — say, middle class moms or travelers — for a given location, packaging data with information about the location/place. In the same way that an online marketer might use ComScore data to identify a given audience, and buy media across the sites that fit a profile, marketers use these systems to buy media for users who are within a given place that fits a profile, too. A hotelier might deliver ads to users in airports to target “travelers.”
Over the last year, however, the big breakthrough has been device profiling — the closest marketers have come to recreating cookie-based targeting on the mobile device. Marketers use massive data processing engines to index the billions of ad impressions flowing through mobile networks every data, using devices identifiers to pool together the ad impressions, and the affiliate data, by user. Then, these vendors analyze the location data include in the ad impressions for each user, drawing out insights about where they’ve been and lumping devices in familiar audience segments. Marketers can then target sets of users based on past behavior, reaching consumers who, for instance, have been to a car dealership in the past year, or who have visited a competitor’s store in the past month.
But here lies the problem: Vendors have effectively recreated print, online, and behavioral targeting for mobile. Ad tech has circumvented a number of limitations endemic to the device — namely, the lack of cookie data — to build a mobile version of the desktop world. But it still does not address the unique qualities of the platform. The static vision of audience, where a user is defined in a single way through his or her day, simply does not apply to a mobile device where a user’s context is constantly changing.
On mobile, the challenge for marketers is to unearth context through a variety of means. As a consumer, I’m as much “on the way home from work” as I am a millennial or a periodic traveler. Marketers need to create a new, reflexive definition of audience that considers the mindset and context of a user in that particular moment, and understand what impact that has on their desire or interest in a given product. Can that problem be solved by iterating on the existing targeting model? It may require a paradigm shift to get there.
The question is whether context is problem that can solved by iterating on the existing targeting model, or if it is paradigmatic shift that merits a new approach, built from the bottom up.
This post was generously underwritten by Ubimo. Ubimo was founded with a mission to transform mobile advertising. For more information, visit Ubimo.