Bohra compared this flat rate model to that of a traditional private marketplace. Publishers can sell their media at a discount or premium depending on who is actually buying that data and create customized pricing for particular customers.
Bohra claimed any data exchange facilitated by Adobe’s system is privacy-centric; in other words, Adobe scrubs any ingested data for PII in addition to what its customer scrubs out.
It remains unclear, though, how consumers can opt out of such marketing programs in the first place. Typically when a user clears their cookie history, their privacy preferences would go right out the window, too.
The industry as a whole doesn’t have an answer for this.
In Adobe’s case, the company said it is adding more controls and allowing clients to segment audiences based on pre-existing privacy policies through a new product called Data Export Control.
“We allow customers to classify different types of data being collected in the DMP so that the exporting or activation of that data is dependent upon the classification,” Bohra said.
For instance, if data collected is linked to a logged-in interaction, clients could classify it as “potentially containing PII while logged in” and thus set specific restrictions around the data hand-off.
So Adobe’s DMP could prevent marketers from combining anonymous third-party cookie data with PII or add additional restrictions based on data type – email data versus display ad impression data or modeling data, for instance.
Adobe’s expansion of its DMP encourages brands to continue their investment in technologies of this type, said Stuart Watson, SVP of emerging media and technology for Camelot Strategic Media and Marketing, an agency whose clients include Intuit and Southwest Airlines.
In addition to the second-party data opportunity, he said he liked that Adobe has stepped in as a referee to facilitate blind matches between a publishers and advertisers’ data sets, as well as deterministic/probabilistic matches.
“There’s also the fact that you can immediately begin to understand overlap,” Watson said, “and, based on your cycles for conversion, within a reduced amount of time know pretty quickly that [this data onboarding and segmentation] is backing out to the right number.”