This week's guest blog post is contributed by Anurag Mehta, Gravy Analytics, SVP & GM Audience Data Solutions.
Nearly a hundred years after John Wanamaker famously said, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half,” the advertising industry is still struggling to address the conundrum. Targeting, particularly on mobile devices, is intended to solve just that problem.
Advertisers that know the characteristics of their target customer can purchase impressions designed to reach only high-likelihood customers. However, not all targeting is created equal. More robust consumer-targeting profiles translate into more productive advertising spend with fewer wasted impressions—and the most vigorous profiles include behavioral attributes.
Consider a targeting maturity model to better understand which advertising data best fits your objective. At Gravy, we segment this into five targeting categories: untargeted, demographic, online activity, location and behavioral activity, which includes event participation and attendance.
Online search and browsing activity is superior to demographic data because it provides some indication of intent, interest or both. However, we know there are many reasons why someone might wind up on a website landing page. The visit may be for work research, a recommendation from a friend or an errant click, but generally it is much better than what existed in the pre-digital age.
Location data is the next step up, tying online personas to offline locations visits. People don't go to locations accidentally and there is more effort involved than clicking on something, so location data tells us something about affinity or consumer habits, which enables the development of richer profile segments.
However, the most robust targeting is based on understanding the full context behind the location data: the behavioral event activity. This combines location intelligence with event information to indicate what activities people attend as participants or spectators. These offline behavioral signals represent the highest indication of commitment to an intent, affinity or participatory activity. These are not casual users. They are dedicated and identified by matching their location with scheduled events.
While it’s useful to know if a consumer goes to Madison Square Garden, that information alone doesn’t give you actionable insight. Consumers that attend multiple Knicks games, a single Taylor Swift concert, or a Disney on Ice performance will certainly fall into different behavioral and lifestyle categories.
Let’s say a woman visits a local church every afternoon, but you knew she attends a yoga class there. What about someone that shows up in an open field, but you didn’t know a wine festival was going on that weekend? The event data provides rich context that location alone cannot.
Visits to retail and restaurant locations are often assumed to express consumer affinity for a particular brand and sometimes that is correct. However, consumers attending a fantasy football draft at a local bar should be viewed differently from other patrons there to eat lunch. A consumer that goes to a home-improvement store might be a do-it-yourselfer or in-market for a new home and more focused on appliances than electrical supplies.
This is the hidden power of combining event and activity information with location to develop more robust consumer audience segments for advertising campaigns and consumer insight.
For more information about Gravy Analytics and their products, visit their website.
Anurag first became involved in mobile ad tech in 2006 when the space was in its infancy. He spent the last decade in and around mobile, online advertising and marketing analytics. Prior to Gravy, Anurag served as vice president of Wireless & New Media at Neustar and was formerly SVP of sales and business development at Mobile Posse. He is passionate about data-driven decision making and personalized marketing.