The Future of Data Clean Rooms within Digital Advertising
Clean rooms have been used for a number of years to allow parties to collaborate on data, mostly as a solution to stricter privacy legislation about user data. At their simplest, clean rooms are a more privacy compliant way of matching data as only representations of the data are shared between two parties without the data ever having to leave the place where it was created. This can lead to higher match rates but most importantly a legally tighter solution than existing solutions within digital advertising.
The other reason clean rooms usage within digital advertising is on the rise is due to many more solutions and processes being available to ecosystem players that look to simplify and innovate on pre-existing and new use cases.
In this piece, we will look at how clean rooms have been adopted initially, explore pain points for early adopters and then look forward to some predictions on the future landscape.
Clean room capability now exists within the most common cloud data platforms used by advertisers (think Google Cloud, Amazon Web Services, Azure) - and for those that have the technical and specialist knowledge, ‘modules’ can and have been built internally that solve for specific marketing challenges. However, most brands are using AdTech specific solutions that have been created to solve for a lot of advertising use cases.
Regardless of the supplier, there have been some common hurdles that brands have had to overcome when attempting to adopt these AdTech specific solutions. The biggest hurdle has been in onboarding. Due to the nature of exploring a technology solution that connects first party data, internal privacy concerns alone have made integration processes lengthy. Data interoperability has also been a challenge; depending on the supplier, advertisers have come up against integration limitations as some suppliers have a fixed list of data partners that a brand can match data with. The other main challenge has been caused by a lack of flexibility on the analytics side, with some on the demand-side being left frustrated that once data has been matched or shared with a partner, there is then only a fixed set of rules or queries that can be run to create insights.
The Future of Clean Rooms
It's not then surprising to believe that future facing solutions will look to solve a lot of these early frustrations that the demand-side have uncovered.
Easy onboarding - to fix the problem of long onboarding cycles, solutions will have to evolve to 'sit on top of' where the data already exists negating the need for lengthy privacy talks internally.
Data interoperability - future-proofed solutions will allow for technology agnostic data partnerships where there is no need for advertisers to have a license with the same as your data partner.
Sophisticated use cases - leading solutions will start to allow for algorithms and queries that are not predefined and are written centrally. They can then be deployed to the data wherever it lives.
The emergence of a clean room service layer - advertisers are investing in this space and creating a data clean room strategy has become high up on the in-housing playbook. However, marketers that do not have the internal support or capability within engineering and analytics will be looking for help. The emergence of a service layer either within consultancies or agencies will then allow marketers to focus on organising data partnerships and building more creative use cases.
There is no doubt that this is a quickly changing landscape and ecosystem and there will be big growth in terms of adoption and the amount of partners and services that exist around clean rooms. There is an opportunity for large brands to gain a competitive advantage by leaning in early and making use of any first party data they have within the new and evolving space of data collaboration.
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