August 20, 2012
By Ken Barbieri
With the heavy proliferation of mobile devices, marketers are increasingly looking to taking advantage of location based services (LBS)—and, more specifically, hyperlocal mobile technologies—as a means for targeting and attracting the attention of the ever-elusive, on-the-go customer.
There is no doubt that hyperlocal mobile targeting is an effective and powerful method of pinpointing the “where” and reaching mobile consumers. And with companies touting new mobile targeting technologies that effectively break the world into 100-meter tiles (or city blocks) and identify fairly precise locations of mobile consumers, mobile targeting sounds like the silver bullet of which marketers have been dreaming.
Do behave
The challenge is that by focusing solely on geographic location, ad targeting technologies may cause marketers to inadvertently ignore key customer attributes such as demographics, psychographics, lifestyle and purchase preferences.
By coupling hyperlocal mobile targeting methods with predictive analytics based on rich offline non-personally identifiable consumer profile data, marketers can more precisely pinpoint and serve up the right messages at the right time to drive more conversions.
With unmatched granularity on consumer household data that yields thousands of offline demographic attributes and lifestyles, predictive targeting gives marketers the ability to connect with specific audiences highly predisposed to their brand, product or service.
Before marketers heavily invest in any mobile targeting initiatives, they need to ask a few critical questions.
For example, who is the intended audience and what do my customer profiles look like? What is the context and delivery method for the mobile ad? And, equally as important, what is the message based on the two previous answers?
Leveraging consumer data to gain a more accurate model for predictive targeting will yield far superior insight on what consumers are likely to do prior to their actions.
By coupling predictive and hyperlocal mobile targeting, marketers gain a more complete picture of on-the-go consumers who have different behavior at work versus at home versus when traveling.
Increased dimensionality
Predictive targeting relies on a wide range of data points to anticipate future behavior across a deep array of interests, thus increasing the dimensionality of the target consumer profile.
These insights enable advertisers and their partners – agencies, trading desks and networks – to deliver relevant mobile display advertising from the moment they encounter a user by delivering an audience of anonymous, non-personally identifiable population segments based on verified offline consumer information.
So, by combining the precision of hyperlocal targeting with rich offline data, companies can supercharge targeted ads to reach intended recipients and drive a higher response rate.
For example, on-the-go consumers in the popular Tysons Corner shopping centers in Virginia typically receive the same offers via their mobile devices despite the consumer profile segments that typify their purchase behavior.
With predictive targeting, women ages 35-50 earning more than $100,000 annually will receive more meaningful mobile promotions and advertisements for nearby high-end stores versus recent college graduates with less disposable income.
Offline customer data must be delivered in real-time
New hyperlocal mobile applications are increasing the accuracy and ability for marketers to reach more mobile consumers.
Having access to critical offline data in real time with a precise location for on-the-go consumers translates into far superior targeted and meaningful messaging for successful ad campaigns.
For example, marketers working with their clients can immediately determine from rich profile information that high-earning financial services professionals travelling from Manhattan’s financial district to uptown Manhattan should be served up offers for high-end chic restaurants or nearby men’s clothing boutiques during transit.
Transient and persistent behavior
Predictive targeting also enables marketers to track and distinguish between transient and persistent behavior. It takes into consideration that consumers, no matter where they are located, have certain characteristics and brand affinities depending on life stage—and that those affinities are not likely to waiver.
Simply put, women ages 20-35 travelling through an airport are more likely to respond to mobile ads for a manicure/pedicure airport kiosk than their male counterparts.
With the rise of smartphones and tablets, mobile marketing and, more precisely, privacy-compliant mobile targeting, gives way to big opportunities for the online and mobile display space.
It is easy to get caught up in the “where” craze, but do not forget to include the “who” in your arsenal as well.
Ken Barbieri is managing director of AdAdvisor, a Neustar service, based in Sterling, VA. Reach him at kenbarbieri@targusinfo.com.
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