As publishers and brands increasingly harness first-party data to reach more targeted, higher-performing audiences, we’re entering a new era in data-driven partnerships: the age of direct sharing between brands and publishers.
In this scenario, brands and publishers each share what they know about consumers, co-mingling data to create second-party datasets that are significantly more valuable than third-party datasets, or than either dataset on its own.
In the past, marketers were reluctant to share their data with agencies, since agencies weren’t set up to handle it, or to use it exclusively to benefit that particular brand. Instead, agencies relied on third-party providers to develop an aggregate view of the consumer, then purchased data from vendors who could identify and target users who looked like the brand’s ideal customer.
Much was missed in this execution. Media buyers had a bottoms-up view of the consumer, based on syndicated research and campaign data — a fairly inaccurate view for a marketplace that sold itself as “precision media.”
With the rise of Universal IDs, media agencies have tried to make up ground by becoming an insights and activation center for clients, employing people-based targeting. This approach, however, still relies heavily on aggregated third-party data, lookalike modeling and surveys, and is often based on lowest-common denominator data (e.g., gender, geo).
While these aggregated datasets have been sold to clients as “targeted,” they aren’t based on a direct relationship with a user. For example, to drive in-store purchases for paint, an agency may target male homeowners in particular locales. Agencies may layer on past purchase data, but they wouldn’t know if a particular man is in-market for paint at this moment.
Publishers, on the other hand, have a top-down view of users. They start with what they know about the user, based on a direct relationship with that user (e.g., interests, engagement history), and then narrow their view to determine which content, formats, brands and even creative messages might resonate best. This can be accomplished with first-party datasets, including recency/frequency combinations around specific content and “event-based” attributes that signal true intent.
In this framework, 1:1 matching can still take place, but analysis can occur at the segment and attribute level, as well.
In short, what a media buyer sees and what a publisher sees, even when looking at the same user, can be startlingly different.
Accordingly, many marketers are adopting a new mindset when it comes to sharing data, recognizing that publishers have as much at stake as advertisers when it comes to data. Clients know what users they want to reach, while publishers know what unique data is available to help achieve a desired business outcome. This is especially true for categories like CPG, which often lack ongoing, first-party data relationships with consumers.
Together, marketers and publishers can pool their knowledge to create a more complete view of each user, delivering greater impact for each impression and putting control back in the hands of the marketer.
Both marketers and publishers own the relationship with the consumer. There is a sense of entitlement that comes with this reality, but it should really be a sense of privilege. In any case, who “owns” the user isn’t the most productive question to debate. Agencies, for example, often want to retarget users, feeling they “own” users they’ve delivered ads to, when that “ownership” isn’t earned, or isn’t often that valuable.
The real question we should debate is, “Does this data aid my understanding of the consumer?” Together, marketers and publishers can say, “We both know this user, and what do we each know about her?” — thus informing more direct, nuanced strategies. Agencies still play a critical role in this process, doing what they do best: strategizing and executing campaigns that leverage the combined insight from all parties.
Without this frank openness, marketers, publishers and agencies run the risk of devaluing the intelligence each has about the consumer. As an industry, we run the risk of hyper-targeted campaigns that rely solely on match rates, the overuse of DSPs and minimally scaled PMP deals that leave budget -- and insights -- on the table.