![]() This learning process involves moving away from trying to measure what we no longer can and focusing more and more on how to build new utility into consumer ad experiences via connected data sets.įirst, a bit of background on what ADH does: ADH is a "data clean room" solution that allows multiple parties to analyse the intersections among respective first-party data sets, but without revealing granular row-level, user-level, or log-level data.Īt MightyHive, we're discovering what's possible first-hand working with clients to generate very new and very exciting insights from multilateral data co-ops.Īs an example, Brand A could upload transaction records tied to first-party cookies. As part of our own process of discovery and experimentation, we are learning that we need to fundamentally change the way we and our clients use data as a tool and a value generator. We at MightyHive are finding that ADH and other emerging technologies are facilitating new and interesting ways of interacting with customer data that were not previously possible. ![]() Only later do we find that there has been a complete paradigm shift and new use-cases have emerged. It's usually true of technological disruption that we first try to retrofit old paradigms onto new technology and miss the forest for the trees. The introduction of GDPR and the general global trend toward digital privacy has pushed us into a new era in the digital media world-but it doesn’t appear as though some have accepted that reality just yet. With the redaction of DoubleClick (now Google Marketing Platform) IDs, the rollout of Google’s Ads Data Hub (ADH), and growing interest in data clean room solutions, marketers must "unlearn" what was possible in the past and become rapidly familiar with what is now possible in the ID-redacted world. Change has come to the world of digital marketing measurement.
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