"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Sergey Shprints, head of analytics operations at Hearts & Science.
For the last two decades, advertisers, publishers and data/tech providers have relied on “centralized identity.” They’ve gotten used to finding, reaching, engaging and measuring customers via cookies, mobile IDs and set-top box IDs.
But as consumer privacy laws take hold, we’re entering a new phase of marketing analytics in which connectivity and addressability become more and more fragmented.
It’s no surprise, then, that clean rooms are becoming a hot topic among advertisers.
Initially set up by walled gardens like Google, Facebook, Amazon, LinkedIn and Verizon, clean rooms are authenticated environments built to give advertisers access to data in an anonymized fashion. Advertiser and agency analytics teams can use these environments to understand consumer behavior, experience and engagement for logged-in or registered customers. They can also bring their first-party data into the clean room and match it to platform data for activation and measurement without user-level visibility.
But clean rooms don’t just come from these platforms.
Publishers and media companies – historically skittish about giving advertisers access to user data – are faced with the reality of their footprint and media spend shrinking due to the same signal loss.
As a result, they’re partnering with technology providers to build their own authenticated and privacy-safe environments called ”neutral clean rooms.”
There, advertisers enrich their data with publisher data sets and measure performance – all on the publisher’s properties.
The digital landscape is increasingly starting to look like a federation of clean room environments, each with its own unique data and capabilities. “Identity” is becoming increasingly decentralized. So how should advertisers respond?
First, they need to assess their marketing stack and media allocation to decide which clean room to use.
For example, if the brand is on Google’s tech stack, marketers should prioritize Ads Data Hub for reach/frequency measurement, attribution across Campaign Manager and DV360, and mobile ad data for first-party data mapping. YouTube data also becomes more powerful when considered alongside the rest of Google’s data, enabling cross-device exposure analysis.
Once they make their selection, marketers should hone their clean room strategy into three parts.
1. Build the audience
Advertisers need to locate new paths for finding and growing audiences within each clean room. Start by mapping first-party data to each clean room to find existing consumers and potential prospects. Repeat the process in as many clean rooms as strategically necessary.
Then test, enrich and analyze behavior and performance across new audiences. This enrichment will offer durability as audiences from cookie-based tracking drop, while providing new insights to inform prospects.
2. Shift to a new engagement model
Without cookies, advertisers need to shift to a mobile-centric engagement model where they can reach consumers within their logged-in or in-app experiences. Recapturing this data will help obtain cross-device insights and enable device-based remarketing.
3. Rethink measurement and optimization
Cookie deprecation means the loss of a unified view of campaign performance across the entire customer journey. It becomes even more important, therefore, to use cross-device data within each clean room to find new signals.
Advertisers should also consider the impact of additional mobile signals on campaign reach, frequency goals and, most importantly, attribution models. This requires a multi-clean-room measurement and optimization strategy.
Each clean room will have its own multi-touch attribution measurement. Advertisers will then need to combine the results across all clean rooms and normalize the weight through media mix modeling.
A post-cookie future
Responding to challenges around targeting, optimization and measurement will require marketers to define a clean-room strategy across dozens of environments. The work won’t be simple, but the returns will be immense.
Instead of inferring customer journeys based on small samples of data, we can be more rigorous in how we identify, target and measure audiences by leveraging de-identified (and previously inaccessible) publisher and platform data. Meanwhile, as we’ve seen time and time again, industry dynamics will force everyone to the table to develop cohesion amidst the chaos.