In this piece James Prudhomme, chief revenue officer at Optable, a provider of clean room technology, outlines how he believes clean rooms can solve issues around measurement and targeting in CTV environments.
By now, most of those involved in digital media know something about data clean rooms. They probably identify them with the walled gardens of the big tech players – places where Google or Facebook share aggregated, anonymised data for marketers to analyse.
They may also know that data clean rooms are rapidly gaining currency in the open internet as a means for brands and publishers to collaborate on data projects in a similarly privacy-compliant context.
These are, of course, valid and extremely important use cases. There are many reasons to be excited about the possible applications of data clean rooms in a post-cookie world, as brands collaborate with publishers, retailers and other data-rich entities to build better insights than even cookies allowed – and, this time, with fully opted-in data.
But there are also environments in which portable public identifiers have never been used at all – where even the confirmation of ad delivery is not a given. And here, too, data clean rooms provide the key to solving the challenges of fragmentation.
Perhaps the best example is CTV platforms. Historically in CTV there have been no cookies at all with which to stitch together audiences. To this day, a brand running campaigns on Samsung, Roku and Amazon Fire doesn’t have any sense of its unduplicated reach across those three buckets. In most cases, it is not possible even to witness ad delivery.
Media buyers are understandably eager to reach audiences within the booming CTV space, but they have no data to work with – they are flying blind.
But they have the same requirements in CTV as they have elsewhere: for planning, activation and measurement. And if buyers lack even basic data across their media buys, that inevitably biases them towards inventory that is more measurable. Brands that care about measurement end up being driven into the arms of Facebook and Google by default. The more you run with Google, the more reporting you’re going to have.
So CTV requires alternative rails. To plan and activate campaigns, to build pre-planning insights, to allow reporting and cross-portfolio measurement, platforms need the ability to onboard data and connect it to complementary sets in a safe, privacy-preserving way.
The clean room approach to planning, activation and measurement for CTV offers three specific benefits to both buyers and sellers:
- Trust. Clean rooms create trust through software, allowing partners to safely compare data in such a way that no audience data is leaked
- ID-agnosticism. Instead of using a centralised ID, clean rooms are built for a fragmented world in which everyone operates their own identity graph
- Differential privacy. By describing the patterns of groups in a data set without disclosing information about individuals, clean rooms ensure that individual users’ data cannot be used to triangulate on a specific person
Over time, as clean room tech is embedded into a wider variety of platforms, we can expect it to become more interoperable and pervasive. We will witness the emergence of core technology that allows marketers to turbo-charge any first-party data strategy.
For now, the huge promise and the inherent challenges of CTV oblige us to get back to the basic building blocks of ad tech. In some channels, after all, it is not just about thinking beyond cookies, but about setting out the future in an environment where they have never existed.