Despite the hype about corporate data sharing, a recent report from Forrester suggests there are hurdles preventing truly pervasive data exchange, at least when it comes to second-party data. Second-party data sharing, or data swapping between direct partners including between non-competitive brands or between publishers and advertisers, is piquing interest among tech decision-makers, though.
The recently published Forrester Research report notes that nearly half -- 47% -- of technology decision-makers in North America and Europe found partner data "important." That's up from 30% in 2012.
But that doesn't mean they're getting their hands on it or giving up their own data. Forrester reports that data management platforms say they implement just 10 to 20 data-sharing projects each year.
There are multiple reasons for the lack of second-party data sharing, suggests the report. Not only is it difficult to isolate potential data partners -- most marketers are reluctant to reveal the types of data they collect much less express a desire to share it -- privacy concerns could shut down such arrangements before they get started.
"Many marketing organizations have privacy agreements that forbid giving away or selling first-party data," states the report. "They are able to share first-party data only in the context of a neutral partner, such as a DMP, that acts as a safe harbor…. This may not hold up to consumer or regulatory scrutiny when highly targeted marketing from an unknown brand raises questions about data provenance."
Forrester also suggests when considering data-swapping deals with partners, companies often price their information at a price that's too high, in part because "opaque one-to-one data sharing cannot benefit from market pricing mechanisms."
Still, the report indicates it may be worth it for firms to overcome the obstacles. While first-party proprietary data owned by brands such as CRM, loyalty or purchase data is limited, combining the information with a partner brand's data could extend the value and insights associated with each data set, creating a larger data set that is worth more than the sum of its parts.