“The accuracy rate is not a standalone question,” she explained. “It’s about how accurate do you need to be, depending on the campaign strategy that you’re employing. If your advertising strategy is focused on … being able to leverage intent to bring a specific product to top of mind through retargeting, then yes, you need a very high accuracy rate, but you might have broader goals.”
Simmons and Kohl both noted that because cross-device recognition methods were still emerging, it was difficult to pinpoint the accuracy rate and suggested that it could be at 50% or 75%, respectively.
In regards to other challenges, privacy complications could act as a deterrent, Kohl noted.
“Marketers believe that harmonizing messages and offers across devices has an impact in terms of customer experience, but you have to do this in a way that’s privacy-sensitive,” she said. “There are also explicit risks in getting it wrong. … Nobody wants to touch privacy because it’s super scary.”
And while data behemoths like Google might seem on the surface to be best positioned to leverage cross-device technologies due to a wealth of consumer data, marketers, according to Simmons and Kohl, are increasingly reluctant to give their best assets to the company. Kohl added that marketers increasingly perceive themselves as ”data owners instead of publishers” and think more strategically about how to “build high-value audiences from their data.”
Sivaramakrishnan, who was a senior research scientist at AdMob and worked for Google post-acquisition, pointed out that Google may focus on other areas besides expanding its cross-device recognition capabilities. “Just because Google can do something does not mean it will,” she said.
Looking ahead, all three panelists agreed that marketers are becoming more aware of cross-device recognition technology, even though, as Kohl observed, “there are a lot of barriers to taking on great cross-device marketing and … the CMO should be thinking about how that linkage strategy looks."