Switzerland for data: - Data clean room

Data clean room is an increasing 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.

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 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 data clean room.

o Advance analysis:-Data cleanrooms allow organisations to conduct in-depth analysis on combined data sets to gain insights on customer behaviour, segmentation, customer lifetime value, and more.

o Build custom audience/cohorts:-Data cleanrooms 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 that sells Amul products have additional transaction data from their own marketplace. So, if the two parties mutually bring their data in 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 has already built clean room 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 behavioural 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 in 2017 & named it 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 spend 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.?