The demise of cookie-based marketing research has prompted brands and data providers to come up with increasingly innovative ways to share market data with each other while adhering to strict privacy laws.
One of the potential solutions is the data clean room – a digital space that more and more companies are using as a means to safely gather the marketing insights they need to streamline their ad campaigns, understand their customers, and predict industry trends.
What is a data clean room?
A data clean room is an online platform where companies like Google, Amazon, and Disney can safely share data with advertisers without violating user privacy. They accomplish this by sharing aggregated data – or data that has been organized into groups or cohorts – rather than individual customer data.
Advertisers are then allowed to put in their first-party data to see how it matches up with the aggregate data. Any inconsistencies between the two may mean that the advertiser is serving ads to the wrong audiences.
No data clean room provider allows advertisers to export – or even access – customer information.
What are the different data clean room providers?
As of 2022, the major data clean room providers are:
With the rising global concerns over internet privacy, Google created and released Ads Data Hub (ADH) to balance the needs of individuals with the needs of advertisers and brands.
Google Ads Data Hub allows businesses to access aggregate marketing data from three of the the biggest sources of consumer information in the world:
ADH is built on infrastructure from Google Cloud and Google BigQuery, which is where you would construct the queries that will get you the insights you’re looking for. BigQuery is excellent at processing large data sets and yet is relatively fast given the amount of information it can handle.
As a data clean room provider, Amazon is only second to Google in terms of the raw amount of granular and verified consumer data at its beck and call.
Amazon Marketing Cloud is built on Amazon Web Services similar to how Google Ads Data Hub is built on Google Cloud. Unlike ADH, however, you can use Amazon Marketing Cloud without an AWS account.
AMC allows brands to access aggregate consumer data from its subsidiary brands like Whole Foods and Twitch. With Amazon Marketing Cloud, advertisers can now perform analytics across multiple pseudonymized data sets and generate aggregate reports. These reports can assist brands with campaign measurement, audience refinement, and more. It enables advertisers to make more informed decisions about their cross-channel marketing campaigns.
Data onboarding platform LiveRamp has released a new data clean room service called LiveRamp Safe Haven, although LiveRamp prefers to call it a “Data Collaboration Platform.”
Unlike ADH and AMC, Safe Haven is run independently and acts as a middle man between two companies who want to exchange data. A brand and a retailer can match data and refine audience segments, for example. Or a publisher and an advertiser can match data and measure advertising outcomes.
According to the LiveRamp website, Safe Haven comes pre-loaded with over 600 turnkey integrations to make data collaboration more convenient. LiveRamp Safe Haven can be leveraged across many verticals, including retail, CPG, travel, publishers, and other applications.
Snowflake is a data warehouse software platform whose main product is the Data Cloud – a data ecosystem where organizations share and consume data with one another, with commercial data providers, and with data service providers.
One of Snowflakes unique offerings is the Distributed Data Clean Room. In regular data clean room setups, only two parties are allowed in the clean room at a time: both sharing and consuming each other’s data like two poker players privately comparing their cards. Snowflake’s distributed data clean room, however, allows you to safely share data with multiple parties at the same time while still closely controlling the security of your own data.
Because Snowflake operates as a Data Warehouse as a Service, the Distributed Data Clean Room and other products can run with minimal IT admin support. Neither is there any need to install extra hardware or software.
Disney’s Advertising Sales group launched their own clean room solution on October 21, 2021, built with Snowflake, Habu, and InfoSum as strategic partners and powered by Disney Select.
The Disney data clean room allows advertisers to access over 1,000 first-party segments and functions as an entry point to its vast portfolio of brands across all screens.
This clean room is cloud-agnostic, which means that it can connect to and function within any could environment that an advertiser brand might use. This increases Disney’s accessibility with any organization that wants to take advantage of Disney’s aggregate customer data.
AppsFlyer promotes itself as having one of the safest data collaboration solutions in the market, and their extensive security- and privacy-focused measures bear this out.
They have invested heavily in cutting-edge cryptographic security solutions such as Homomorphic Encryption (HE) and Private Set Interaction (PSI), and have partnered with Intel to develop these technologies further.
AppsFlyer also has one of the largest independent data clean room implementations in the world, with integrations to major data providers like Facebook, Google, Twitter and Snap.
The data clean room that AppsFlyer uses is just one part of a larger Privacy Cloud Application (PCA) that lets businesses define their own business logic, compliance requirements, and data governance, making it an excellent solution for those who place a lot of value on security.
Habu is one of the global leaders in data clean room platforms, and has had multiple partnerships with other industry peers like Snowflake and Disney. Their software enables secure and streamlined data collabration between partner organizations.
Of all of Habu’s products, CleanML is the latest and one of the most advanced. It’s a distributed data clean room with a powerful machine learning component (hence the “ML” in the name) which companies can use to build, train, and refine complex machine learning models.
Habu also offers the CleanCompute module, which is a secure run-time environment that joins private datasets together for modeling or analytics purposes. Both products use advanced privacy-focused features and techniques to prevent each party from seeing one another’s data while still benefiting from the total output.
For more on data clean rooms, be sure to check back at Tinuiti’s blog for additional resources.