Data clean rooms: The future of measurement or just another form of aggregated reporting?
Working in the mobile marketing and advertising space, you’ve probably heard the term ‘data clean room’ (DCR) at some point and have likely wondered if it's an area you should explore or invest in. In our increasingly data-privacy centric ecosystem, just hearing the word ‘data’ is sure to spike interest, and DCRs are an important topic of discussion. In fact, it’s because DCRs offer a privacy centric solution for unifying data in an industry with ever-heightening data privacy requirements that has led to their recent prevalence in our space. The idea that you can enrich your data securely is undoubtedly appealing, and while DCRs do indeed provide that, there’s a little more to explore when considering the value of the output.
From a mobile measurement perspective, the most crucial factor to consider is whether DCRs are effective in providing us with data that can be used for enhanced campaign optimization. As secure, protected environments, they are effective in allowing multiple parties to carry out joint data analysis and to potentially help marketers better understand their data. However, the data you get out is in the form of cohorts and aggregated reports.
In short, data clean rooms today and in the foreseeable future realistically function as a source of aggregated reporting (yes, another one), providing data outputs that can’t be directly leveraged for campaign optimization. Let’s take a closer look.
Campaign optimization and the tools modern marketers need to succeed
We hear from our partners and clients daily that the main concern industry-wide is campaign optimization, particularly on iOS. Despite being very helpful tools for data unification, data clean rooms are not currently providing outputs that network partners can leverage for their ad servers. Regardless of the granular information or data that an advertiser feeds in, the aggregated outputs simply don’t solve the issue of optimization on iOS, or at large. These outputs also don’t allow for partner optimization of algorithms, which is what advertisers would ideally like to see. There’s also the issue that DCRs can put a limitation on aggregated reporting, as both the app publisher and the partner must have at least one common variable to input. Without this, the DCR cannot do the aggregation. For this reason, we’ve found that partners are wary of investing in an area that doesn’t effectively enable them to provide better outcomes to advertisers, or that they are only able to work in this capacity with the limited number of partners that have this common variable capability.
At this stage we see the main value in DCRs being an additional source of reporting aggregation, which is only necessary if this is something your current MMP does not offer. Unfortunately, today they are not the silver bullet everyone was hoping for when it comes to optimization on iOS.
For now, the good news is that Adjust’s analytics solution Datascape offers just as many dimensions at the aggregated level as a DCR final output could provide, with the bonus of its swathe of features and actionable insights for smart, fast decision making. Investing in solutions like predictive analytics and machine learning is the most future-proof direction to take within the current climate—we’re already seeing success in SKAN optimization with Conversion Hub, our solution that predicts the best conversion value buckets for your iOS campaigns.
To learn more about Adjust’s measurement and analytics suite, and how we work with our partners to empower clients to drive sustained growth regardless of changes and developments in the mobile marketing ecosystem, request a demo here. You can also check out Datascape and our iOS/SKAN Solutions to learn how our next-generation solutions are already empowering data-privacy compliant, strategic methods of campaign optimization.
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