“Data Driven Thinking” is a column written by members of the media community and containing fresh ideas on the digital revolution in media.
Today’s column is Part II of a two-part column (Part I is here) written by Mike Afergan, CTO & SVP of Advertising Decision Solutions at Akamai.
Mention ‘shopping data’ to an agency or advertiser and the talk often goes straight to online retail. And to be fair, shopping data is a very effective way to predict what someone is in-market to buy, as I laid out here two weeks ago. But did you know that shopping data can be used to accurately describe who someone is in a way that other targeting approaches cannot? In part 2 of a two-part series on the value of shopping data, I want to introduce the concept of Shopographics as a great way for advertisers to find their target markets.
Part 2: Using Shopping Data to Find Target Markets
For years, we in the online advertising industry have advanced an idea about the so-called holy grail of online advertising: improved simplicity, efficiency, measurement, and control. Yet I’d bet that most of our colleagues, if pressed for an honest answer, would confess we’ve gotten further away from these goals; that today it feels like it’s become more complicated to sell to fewer and fewer people. Instead of delivering massive scale, we’re enabling brand marketers to reach the eleven middle-aged men from Lubbock who are fans of both ballet and monster trucks.
For those advertisers looking to target specific audiences in order to drive awareness, I encourage you to use shopping data to help you reach that goal. By shopping data I mean shopping behaviors, carting behaviors, and ultimately secure purchasing behaviors. It might seem counter-intuitive at first, but shopping data helps explain who someone is in a way that all other behavior targeting approaches don’t. Think about it – demographics might help describe an audience’s age or income, geography might tell you where someone lives, and psychographics could get you closer to what someone is interested in, but really they’re all based on assumptions. On the other hand, shopping data, or as I’d like to coin it, “Shopographics,” do describe people based on actual purchase decisions. And purchase decisions, I believe, have a distinct advantage over other behavioral descriptors.
The power of shopping data is that unlike other forms of targeting, it doesn’t rely on assumptions. You can target males, ages 18-34, who live on the West Coast and assume that this audience segment is, relative to the national average, inclined to surf. Or you can use anonymous shopping data to know that a person has bought a surfboard, looked at flights to Maui, and browsed wetsuits, and eliminate any guesswork. You can target females, ages 22-34 who live in suburban areas, and assume that this audience segment is, relative to the national average, inclined to get married. Or you can use anonymous shopping data to know that a person has shopped for a wedding dress, browsed men’s rings, and booked a honeymoon hotel suite. Shopping data revolves around purchase decisions intended or taken, which is a far better indicator of who someone is than where they live or the websites they browse. Few things in life are clearer than when someone is willing to pull out his or her checkbook!
If you’re looking to get as close as possible to understanding who someone really is for the purpose of showing them relevant, targeted ads, I think Shopographics get you closer to your goal than any other behavioral targeting approach. Simple yet effective, I think this approach can help the online advertising industry move closer to its long-standing promise of better efficiency, control and return on investment.
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