Tips: Analyzing Engagement

“The environment that marketers work in today requires them to do less with more,” DataXu CEO Mike Baker said. “And in a data driven world, strategy has become increasingly results driven.” DataXu recently worked with Universal Studios to create audience segments, coordinate ad spend and test engagement success for a campaign for the Matt Damon thriller The Adjustment Bureau.

According to Baker, “connection intelligence” — analysis of how, when and why consumers connect to a brand — was at the core of DataXu’s work for Universal Studios. According to the company, DataXu’s “audience discovery”  method, which involves looking at results within and outside of pre-defined audience segments, outperformed traditional ways of analyzing and garnering engagement by a 2X to 15x scale.

Baker listed three tips based on DataXu’s approach that marketers can employ to look at audience engagement;

1. Observe high variability in ad performance across times, content, consumer demographics, consumer psychographic segments, and geography. Use these instances to inform ad buys.

2. Identify and buy the highest performing impressions both within and outside the campaign’s identified targets. Build new audience segments based on ad buys that work well.

3. Don’t limit analysis to pre-defined target audiences. Look at variables which may influence ad success in these new segments and adjust strategy accordingly.

“There’s never been more information on consumers available, but within that broad area for Fortune 1000 marketers there needs to be a new category of intelligence, connection intelligence,” he said. Connection intelligence, stated Baker, goes beyond traditional parameters of audience segmentation by looking at “meaningful motivations” that drive brand-consumer engagement.

That may sound like broad-based behavioral targeting, but Baker states that looking outside of the segment targeting “box” to new, unexpected audience segments that are engaging with ads- of all stripes- is the key to moving the ad industry out of the “dark ages of data analysis”. “Compared to the way other industries — like the financial industry — use data, we are way behind,” said Baker.