Data Clean Room
Data Sharing and Collaborations Without Revealing Customer’s PII Data
After evaluations of privacy regulations and the loss of third-party cookies and other identifiers, the marketing and advertising industry is looking for a solution for data collaborations with multiple parties without revealing their customer’s data (PII).
The industry is looking for an environment for Secure Data Collaboration, Controlled Data Access, and Comprehensive Analytics.
With the increasing need to create customer-centric data and protect the customer’s privacy, the organization needs an effective solution that helps to set up a secure data-sharing platform which is possible through the data clean room.
Let’s learn more about data clean room, how to set it up, and how businesses benefit from it.
Overview
Data Clean Rooms (DCRs) are secure environments that enable multiple organizations (or divisions of an organization) to bring data together for joint analysis under defined guidelines and restrictions that keep the data secure.
These guidelines control:
- What data comes into the clean room
- How the data can be joined with other data sets in the clean room
- The kinds of analytics that can be performed on the clean room data
- What data – if any – can leave the clean room environment?
- Consumer-specific datasets (Who can read what kind of data?
Use Cases
Consumer Data Enrichment
Data Clean Room helps to leverage third-party data with existing customers and prospect raw data so they can understand their needs and interests to serve customers better. This gives more granular data on the existing customers to make better-informed business decisions.
Customer Data Enrichment could be done in many ways:
- Enrich existing datasets with customer demographic data like income level, marital status, and home address.
- Customer’s geographic details enrichment by adding postal data, latitude, and longitude in existing datasets.
Data Collaborations in The Media And Advertising Industry
This is the most demanding use case; many organizations are looking for a way to understand customers’ online habits. As they cannot track customers directly and adhere to privacy requirements and industry regulations, the company could not share the list of customers. But to promote their products and business, they want to place advertisements on the proper media platform to reach the right audience.
For example, a brand wants to advertise the release of new equipment. They can work with media providers to promote the shows their subscribers are most likely to watch.
They need to determine the overlapping customers and subscribers without sharing or exposing the customer data with each other.
Both parties have their own set of data, and they can use Data Clean Room capabilities to increase the value by showing the right ad to the right person at the right place and at the right time; advertisers use personal data points — including age, gender, location, income, the websites visited, the content was watched, the products were bought, the emails were opened, and even the other ads have been seen.
Customers Overlap Analysis
In this use case, Organizations want to know which customers they have in common for marketing initiatives. Both parties in Data Clean Room can get the standard customer list without revealing their PII.
Let’s say an example of IRCTC and a hotel. The IRCTC will receive the list of their customers who happened to be the hotel’s customers and vice-versa. Both parties can leverage this for various marketing co-activities. IRCTC can send offers of the hotel to the customers, and hotels can send offers of IRCTC facilities.
Other Industries
- Retailers share consumer trends with manufacturers to improve product development and forecast demand.
- Bank and Retailers sharing data to offer brand-specific credit cards.
The Hoonartek team is gear up in setting up Data Clean Room powered by Snowflake
Data Clean Room is a secure framework that allows multiple parties to collaborate without disclosing the raw data to one another. It leverages Snowflake’s existing governance features to build Data Clean Room.
- Row Access Policies: It is defined to act as a firewall to protect data access
- Stored Procedure: SP is defined to validate query requests called VALIDATE_QUERY
- Secure Data Sharing: It shares data across business ecosystems without copying or moving data
- Streams & Tasks: To automate the query request & validation process
Why do Marketers and Advertisers need Data Clean Room?
- Protection of data privacy, i.e. (cookie-free)
- It increases marketing effectiveness for publishers and advertisers
- Share information without revealing the underlying source in the cookieless world
- Due to confidentiality and minimal commercial trust between parties
- To allow data to be brought together to get the power of combined datasets.
- To allow brands and advertisers to run targeted advertising campaigns
- This can be used to identify high-value targets, lapsing customers, and opportunities to win new business.
- It can strengthen marketers’ and publishers’ direct consumer relationships, giving them access to more data than ever before.
Conclusion
Due to the privacy rules of CCPA and GDPR, all the browsers have stopped supporting third-party cookies, which will prevent advertisers from consuming customers’ data to run personalized ads, measurements, attribution, etc.
Data Clean Room is an emerging privacy-friendly solution that will provide an environment to share information without revealing the underlying source. It offers a good balance between protecting user privacy and allowing companies to reach their target audience, measure the performance of their campaigns, and attribute impressions and clicks to conversions.
The Hoonartek team has explored and implemented Data Clean Room and has the expertise and skills to set up Data Clean Room for your organization’s use cases. Reach out to us for further discussion.
