The travel industry vertical has joined automotive and financial services a top category for more precise consumer targeting and outcomes measurement via digital video. Nonetheless, there’s a still a lot of “heavy lifting” going on as brand marketers try to best identify their target audiences with first- and third-party data, according to Experian’s Brad Danaher.
During a break at the recent Beet.TV Leadership Summit titled Outcomes, presented by video marketing technology provider Eyeview, the Television Partnership Director for Experian shares his insights on product and service category success stories and what lies ahead.
Automotive, which is “a big TV category in general, is prime territory for consumer targeting and outcomes measurement, according to Danaher. “That’s been a huge success because even half a percent lift will drive thousands of extra cars sold, so that’s been a big win,” Danaher says in response to a question by Matt Prohaska of Prohaska Consulting.
Financial services, which has a lot of metrics inherent in the business, has been “a big category for us and interestingly, travel has been maybe not number three but it’s certainly significant,” Danaher explains.
Asked about the pricing model for using third-party targeting and measurement data, Danaher cites the usage model adopted by Experian and other third-party data providers. A big advantage is no major upfront commitment of budget.
“Since we’re measuring all of it we can see what works. And then they usually come back and buy more of what works. That usage model has really enabled a lot of people,” says Danaher.
What would he like to see 12 to 24 months from now in terms of industry progression on audience targeting and measurement? “The dream would be a cross-media campaign using an Experian segment in TV online and mobile,” he says.
“Right now there’s a lot of heavy lifting still” as brands seek the best data to define and target audiences. “Twelve months from now the ideal would be if the advertiser knows their metrics, they know what data to use and they know what they’re doing and it’s fast, smooth and efficient,” Danaher says.