Switzerland for data: Data clean room
Data clean room is a catchphrase in digital & ad-tech industries. Data clean rooms aren’t an entirely new concept & the term is adopted from a medical space where cleanroom is designed to keep everything from dust to airborne organisms, or vaporised particles, away from it, and so from whatever product is being handled inside it.
In AdTech industry data-sharing arrangement between wall garden platform /non walled garden platforms & advertiser is known as data clean room. These clean rooms are secure spaces where insights derived from partner platform can be coupled with an advertiser’s first-party data for attribution, measurement, and data modeling purposes. A data clean room is an addition of a first-party data strategy. To use a data clean room, two entities (e.g., an advertiser and a publisher) bring their first-party data and upload them to the data clean room. Then, the data is encrypted and anonymized. Both parties get information in the form of cohorts and aggregated reports.
Data clean rooms act like neutral territories & for this reason, they are frequently called “Switzerland for data”.
Why use a data clean room?
Digital campaign measurement will be impacted by enhanced user privacy regulations & demise of third parties’ cookies & device ID. A data clean room is a part of the software that enables advertisers and brands to match user-level data without sharing any PII data with one another. The benefit to advertisers is a much clearer picture of advertising performance within each platform.
There are 2 main benefits of a data clean room.
Advance analysis: – Data clean rooms allow organizations to conduct in-depth analysis on combined data sets to gain insights on customer behaviour, segmentation, customer lifetime value, and more.
Build custom audience/cohorts: – Data clean rooms can be used to build custom audiences that can be used on advertising platforms, allowing marketers to fine-tune their ad targeting.
Apart from above benefits, data clean rooms help marketers understand if their ads are reaching the right audience & help them find out big untapped potential audience just waiting to be reached. Let’s understand this with an example of Amul as CPG brand & Online marketplace platform like Flipkart. Amul don’t sell their products to consumers directly hence have limited transaction data. They do, however, have first-party data collected from advertising, and loyalty programs. Flipkart which sells Amul products have additional transaction data from its own marketplace. So, if the two parties mutually bring their data into a data clean room, Amul could better understand how their marketing campaigns were driving purchases from flipkart & they could also analyze the collective data to improve targeting and segmentation of their campaigns and offers to specific high-performing segments through flipkart audience targeting solution.
Categories of DCR
There are three types of data clean rooms; ones offered by the walled gardens, ones from independent vendors, and custom-made ones built by brands. DCR is not limited to wall garden platforms & large M&E companies like Disney have already built clean rooms called Disney select. Disney’s clean room solution allows advertisers to run their First-party data on Disney select, for-pre planning insights, activation, and cross-portfolio measurement purposes. Disney Select gives marketers the ability to choose their desired audiences from a library of more than 1,000 first-party behavioral and psychographic segments. There are companies like LiveRamp which acts as an intermediary between two companies who want to exchange data. LiveRamp Safe Haven can be leveraged across many verticals, including retail, CPG, travel, publishers, and other applications. There are distributed data clean room like snowflake which allow you to safely share data with multiple parties (not limited to two parties) at the same time while still closely controlling the security of your own data.
Future of DCR
The first company to market a DCR solution was Google 2017 & which was named Ads data Hub. Gartner said that 80% of advertisers with media budgets of $1 billion or more will utilize data clean rooms by 2023. When considering a clean room solution for your business, it’s important to understand the ways in which it can be used. Before you dive into a specific clean room platform, the first consideration should be how much of your ad spend is focused on each advertising platforms. For example, if the majority of digital spending is focused on amazon or other e-comm platforms, then it’s probably not worth investing in exploring Google Ads Data Hub. There are also scaling challenges with DCR as currently it still operates on a mostly one-to-one scale, partner to partner. If you’re Amul and you want to share data with Google, Facebook, Hotstar & amazon that’s possibly four different clean rooms the brand would have to operate and manage independently and there is no interoperability of data possible. Using 3–4 clean rooms is not ideal, as Brands won’t have a cross-platform view of paid media campaigns & should urge for interoperability between clean rooms.
Future Clean room are renovating into applications with no code environments where results can be consumed via desktop & App, enabling everyday users to leverage the technology and understand the outcomes of collaborating on two datasets.
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About the author :
Prashant Nandan, Principal Partner – Client Leadership, Mindshare