Third-party cookies are out, first-party data is in, and CDPs are racing to make first-party data work harder, better, faster, stronger.
Because while first-party data is valuable, it’s not enough on its own to fulfill advertisers’ needs.
To fill in gaps left by the loss of so much third-party data, Adobe announced on Tuesday a data collaboration product within its CDP. Adobe launched its CDP in 2019 with an emphasis on reaching customers in real time, while drawing from their known interests, behavior and environment to target them with ads or messages.
With the new data collaboration product – which is available for existing CDP customers and as a standalone à la carte product for new customers – advertisers can match their data to a publisher’s data to create lookalike audiences, target ads or attribute campaigns. The advertiser can also match its data to other partners with valuable first-party data, not just publishers.
“For a customer data platform to truly prepare brands for a cookieless future, it has to be more than only first-party data,” said Ryan Fleisch, Adobe Real-Time CDP’s head of product marketing.
Though first-party data strategies work well for existing customers, they alone won’t help marketers with “upper-funnel needs,” Fleisch said. Finding and acquiring new customers, for instance, inherently means moving beyond the brand’s first-party data set.
NBCUniversal – a pilot partner for Adobe Real-Time CDP’s data collaboration product – touted its improved targeting and measurement capabilities as it angled for advertisers’ streaming upfront buys at One24, its annual ad tech showcase, last week.
With Adobe’s data collaboration offering, NBCU has branched beyond reach and branding in campaigns, allowing it to be “more performance driven,” said Ryan McConville, NBC’s EVP of ad platforms and operations.
Going forward, CTV ad sellers like NBCU could earn more performance marketing spend by demonstrating they can provide “the same real-time analytics, performance insights and measurement” as typical performance channels, like search and social, he said.
The data integration
But how does the data matching between an advertiser and a publisher like NBCU work, exactly?
Well, say a marketer knows 1 million people who visited the brand’s website over the past 30 days. That advertiser could match within Adobe’s CDP to identify, say, 300,000 of its site visitors who also watched streaming content on Peacock – which has its own rock-solid identity set based on logged-in accounts. The Adobe CDP already combines data from many sources in its customer profiles, which contain demographic and behavioral information like age, gender, location, web and mobile app activity; products they’ve viewed or added to a cart; opt-ins for product communications; and the channels they frequent, Fleisch said.
So, if a car company wanted to target new consumers, it could use the CDP to create audience segments for first-time site visitors while layering in audiences who designed their own cars online or are considered in-market for SUVs.
The Adobe CDP integrates with the major cloud infrastructure services (it’s not like you must be on Snowflake), as well as ID partners like Acxiom, Blockgraph, Experian, LiveRamp, Merkle and Unified ID 2.0.
The car company can match those segments with data from NBCU to identify the audience overlaps between NBCU’s audience segments – for example, comedy lovers, horror fans or travel enthusiasts – and the advertiser’s own customers.
If prospective SUV buyers watch a lot of live sports on Peacock, for instance, it might make sense for the brand to sponsor a big sporting event. But there’s also value in “learning in real time” about these customers, McConville said.
Privacy protections
NBCU and advertisers (and Adobe) don’t acquire new user-level data through the Adobe CDP product.
“We can ensure there’s not PII being exchanged here,” Fleisch said, because audience targeting and measurement happens in aggregate rather than at the individual level.
In other words, to target or attribute based on a data set created by data collaboration, the audience must be large enough to be reported in aggregate, not at the individual level. So an advertiser might find out 10,000 new customers purchased a product after seeing ads for it on NBCU, but they don’t get the 10,000 user-level IDs (like they did in the world of third-party cookie tracking).
Advertisers have spent years sewing their data together, according to Fleisch. But if they throw some data in a clean room, some in walled garden campaigns and some in a CDP, they risk ripping the data fabric apart.
“Our goal is to allow brands that have been trying to break down silos for years to continue doing that by providing more functionality,” he said. “Brands risk creating new silos in the cookieless future if this [data] is not all brought together.”
