Data matching will replace attribution as one of the major topics across the advertising industry in 2016. Perhaps that's because a multitude of mismatched data sources continue to create major problems in accuracy.
Accurate data boosts ad targeting, but only if one source matches another. While attribution was about identifying the media and assigning a value to its contribution to conversion, it also pushed the idea of spending less media dollars on audiences not relevant to the brand. Programmatic moved in to tidy up the process through automation.
Since everything functions as a data point, because so many devices connect to the Internet, "the [advertising] industry quickly became addicted to data," says Yariv Drori, VP of programmatic advertising operations at MultiView.
In the old days, media was sold contextually. All of a sudden advertisers gained new insights into the audience, but there hasn't been that much improvement in targeting results, Drori says, pointing to the quality of the data as a lingering problem.
Matching quality data will become the focus for 2016. Often advertisers bring their own data to publishers. Advertisers curate, bring lookalike data and probabilistic algorithms to the publisher in hopes of reaching a broader audience.
For example, ESPN has many sections on its site, including one dedicated to soccer. If Adidas comes to ESPN wanting to buy an ad on the ESPN soccer page to sell products, Drori might use the sports brand's first-party data. "You would expect data from ESPN and the Adidas ad buyer to match very high, but it's actually dismal," Drori says. "It's a huge problem."
When the match doesn't occur, the advertiser and the publisher look at each other and scratch their heads.
"Data is like a clock that gives you time," Drori says. "Too many clocks, all with a slight variation in time, create chaos and the inability to confirm accuracy."