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In June 2013, Joe Germscheid, director of consumer engagement at Carmichael Lynch, bought a season pass to a ski resort through its website. Despite having made this purchase, online banner ads for the same season pass were still following him around in mid-November.
“As a consumer, I’d expect [purchase history] to be something they’d have figured out,” Germscheid said. “As a professional, it sort of pisses me off to see clients wasting their money like that.”
Germscheid’s story is not unique. Nearly all consumers have been followed around by banner ads after they’ve made a purchase, long abandoned the idea or never had any interest in the product.
“If you’re hitting the same person over and over again, you’re just wasting your money,” said Erin Matts, chief marketing officer at Annalect, Omnicom’s marketing technology division.
In November, Omnicom set up its own internal data management platform to help address that potential waste. Omnicom is just one agency that is turning to a data management platform (DMP) to sift through data from a wide variety of online media and channels. This way, advertisers can see which ads are hitting which consumers, how often and how effectively.
“The world has changed. It’s a much more diverse and complicated digital world,” said Matts. “The more complex the world gets, the more you need a DMP. Otherwise, you’re optimizing against [separate] environments.”
Matts said that beginning early next year, Omnicom’s media agencies will use the DMP to view information across different ad servers and networks (e.g., Facebook, Yahoo, etc.) with an ability to view reach, frequency and overlap across them.
“If I’m looking at them separately, I might be making wrong decisions based on that [separate] information,” she said. “Without a DMP, you might not be able to see what that Venn diagram looks like. … The ability for us to generate next-generation analytics and insights requires a DMP.”
The importance of those analytics and insights will become even more pronounced as programmatic audience-buying technologies begin to spread beyond online platforms into other media, said Raymond Velez, chief technology officer at Razorfish. “You’re going to see more and more of that,” Velez said. “If automated buying is about hitting the best [audience] segment, then you have to start thinking from a data-driven perspective.”
Data-driven efficiencies can also help with the nagging problem of ads following people around long after they’ve been effective. The latest generation of DMPs are able to scrub the data for freshness as well, Matts said. Working with data that is days or months old is of little service when consumers are making decisions within seconds and are no longer following a traditional funnel-based purchase path.
With consumers bouncing between different spheres of influence for their purchases (from search to social to traditional advertising, in no particular order), it’s crucial to use information from multiple touch points to get a true picture of how much or how little a specific campaign element influences specific behaviors, Velez said. At Razorfish, it’s called a “cookie jar” approach that links the cookies of ads, purchases and other data for a clearer picture of influence.
“The technology to help enable that is amazing. Ten years ago, it was nearly impossible,” Velez says. “If you’re not using data to create a better ad experience, … people are going to think you’re not listening to them.”
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