AWS Clean Rooms: Privacy-enhanced collaboration use cases

Companies across industries are increasingly seeking ways to complement their first-party data to build a holistic view of their customers or business. This often means developing a view across channels and engagements, as well as complementing their first-party data with their business partners’ data. This need for data collaboration spans company size, geography, and industry.

For example, for advertising and marketing use cases, brands want to collaborate with media publishers using data stored across many different channels and applications. This will help improve the relevance of their advertising campaigns and create better engage for consumers with personalized communications.

In healthcare and life sciences, biopharma companies want to generate insights with third-parties such as startups, university laboratories, or population research institutions. They want to improve clinical study design, identify cohorts of ideal candidates for clinical trial recruitment, and reduce overall recruitment timelines, all without revealing underlying patient data.

AWS Clean Rooms is an analytics service that helps companies and their partners more easily and securely analyze and collaborate on their collective datasets—without sharing or copying one another’s underlying data. With AWS Clean Rooms, customers across industries can create a data clean room in minutes, and collaborate with any other company on AWS to generate unique insights about advertising campaigns, investment decisions, and research and development.

Based on customer insight, AWS has created the following list of use cases for privacy-enhanced data collaboration in advertising and marketing, healthcare and life sciences, financial services and insurance, and travel and hospitality.

Advertising & Marketing

With AWS Clean Rooms, advertisers across industries, media publishers, and their partners can expand their access to data as they create, deliver, and measure personalized advertising experiences for customers.

Enrich and personalize – Enhance your existing data set with attributes and signals to better understand consumers and personalize experiences while controlling data granularity.
Plan campaigns securely – Understand overlap and incrementality of audiences across channels and partners without moving or sharing underlying raw data.
Segment and activate – Run queries with your partners to build, match, and reach unique audience segments across channels, touchpoints, and media partners with relevant advertising.
Measure and attribute – Match impression data from media publishers with conversion events from advertisers and measurement providers without exposing raw user-level data.

Healthcare & Life Sciences

Hospitals, biopharma companies, and research and academic institutions can use AWS Clean Rooms, a HIPAA-eligible service, to collaborate on data to improve patient and health outcomes.

Research and scientific discovery – Leverage data across partners to inform the development of new medicines, vaccines, and treatments across therapeutic areas.
Patient journey analysis – Develop an interoperable patient record across the full patient journey from diagnosis through treatment to improve patient care and drive successful outcomes.
Improve clinical trial outcomes – Connect clinical trial data with real world evidence data to optimize and validate clinical outcomes, and execute studies on long-term safety and efficacy.
Analyze proprietary scientific data – Link scientific studies and proprietary research with real world data to improve population health outcomes and value-based care.

Financial Services & Insurance

Banks, insurance companies, capital markets organizations and payment companies similarly need mechanisms to enrich their data with external data sources. This can power customer-centric digital experiences, to build and strengthen their fraud detection programs, and to measure and benchmark industry performance.

Enhance customer insights – Enrich first-party customer financial profile insights with external data sources to build customer-centric digital experiences.
Detect fraud – Securely access and match data insights with external data sources to detect and prevent financial and insurance fraud.
Measure and benchmark performance – Benchmark performance with competitors, without revealing raw data, to understand position within an overall distribution.
Inform credit rating, underwriting and risk management – Leverage insights from additional data sources to improve credit scoring, underwriting, and risk management models.

Travel & Hospitality

Using AWS Clean Rooms, airlines, hotels, and restaurants can analyze collective datasets with other organizations to solve for their data collaboration needs.

Single view of the traveler – Bring together disparate data across engagement channels to form a 360-degree view of travelers or guests.
Connected guest experiences – Leverage data across all offline and online touchpoints during a traveler’s visit or stay to deliver a connected guest experience.
Customer loyalty data management – Break down data silos across formal and informal loyalty programs to drive repeat business and support retention.
Issue dynamic and personalized offers – Consortiums of brand can come together to leverage airfare, booking, shopping, and pricing data to price deliver dynamic offers to customers.

Conclusion

AWS Clean Rooms helps companies across industries solve for their specific data collaboration use cases. These are a few examples of the many use cases that customers have for using AWS Clean Rooms. If you’d like to learn more about these use cases and customer examples, Watch the AWS Clean Rooms video or contact an expert on AWS Clean Rooms.