Distributed Data Clean Rooms: A New Approach to Sharing and Protecting Data
Authors
Beate Lettman
Principal Consultant, Consulting CPG
Ivneet Kaur
Engagement Manager, Cloud and Data Tech
Shagun Parab
Design Consultant, Strategic Center
With technology continually evolving, the data available to businesses is growing exponentially. Principal Consultant Beate Lettman, Engagement Manager Ivneet Kaur and Design Consultant Shagun Parab take you through the workings of data clean rooms and how they offer businesses a secure space in which they can de-identify and share their invaluable assets on modern digital platforms.
As technology advances, data available to businesses increases exponentially. Data clean rooms provide organizations with a safe environment for deidentifying and sharing their valuable assets and are thus necessary for effective management and protection of modern digital platforms.
Consumer brands are adapting to changing data conditions by utilizing Zero- and First-Party Data with consumer consent. With this, they can deliver personalized experiences to optimize target content for the right audience. Digital platforms must eliminate any friction associated with obtaining user information (e.g., emails or questionnaires) to collect these insights efficiently.
How can brands drive customer data sharing?
To drive customer data sharing, brands should strive to create an omnichannel marketing strategy. This involves leveraging digital platforms to track consumer interactions with the brand to enrich its understanding of buyer behavior. With this information, brands can craft customized experiences. A smooth UX/UI experience that detects potential obstacles before users encounter them on their journey of engaging with the brand’s digital assets is significant to attract attention and helping retain customers.
Data clean rooms keep personal information safe in the customer’s journey. By availing of enhanced security and privacy options through data clean rooms, customers will find comfort in partnering with the brand and continue to share relevant information that can help provide better service and products.
Enterprises can collect first-party data through:
- Discounts (Trading fee/Maker-Taker Fee/AMC) if you share referral/Signups
- Product recommendation based on traits shared
- Registrations online for articles, Health suggestion Webinars, Live events, Sponsorships, Site visits
Converting first-party data into a strategic asset through Data Clean rooms and CDP
Collecting first-party data is a cycle that starts with data clean rooms. When a data clean room is established, and data from the first-party sources is collected, a customer data platform (CDP) creates an ecosystem to connect data across various channels by storing and processing the collected data in an isolated environment compliant with data privacy regulations such as General Data Protection Regulation (GDPR). The benefit is twofold: data is cleaned, enriched, and organized through the data cycle to identify patterns and trends, as well as guard against data leakage. Moreover, via a CDP, enterprises can quickly extract meaningful intelligence from data points without manually searching or storing data. By gathering this data in one place, discrepancies and fragmentation are minimized, ensuring the highest quality data is collected.
By combining enterprise data in a centralized place, marketers can separate data silos and unify their customer view, enabling customers to reach their target audience more accurately and efficiently.
However, building data clean rooms present unique challenges for organizations.
Data deprecation is a significant challenge as older data becomes less relevant and obsolete. Enterprises must constantly assess their databases to ensure that only useful information is kept. Moreover, as modern businesses require more real-time insights to make decisions quickly, existing data must be updated.
Data clean rooms involve escalating costs for their operations, including the requirement of advanced security measures to ensure data integrity and protection. Beyond technical requirements, data cleaning processes often utilize a range of tools and personnel to review large datasets quickly and efficiently for accuracy and correctness. As a result, cost per operation increases due to the time taken to carry out multiple checks on the same data or from having to manage immense amounts of information.
Moreover, the frequent need for rapid access of critical inbound and outbound workflow data, while retaining its integrity, has necessitated automated solutions capable of managing high speed transfer and storage of such information with robust security measures. Besides this, another challenge includes need for modernizing outdated in-house IT infrastructure as well as maintaining systems to meet ever-evolving regulatory environment and compliance requirements.
Enterprises must carefully consider these points when developing their data clean room strategy to ensure that any potential gains outweigh the cost of upkeep in the long run.
Digital Marketing Platform (with Customer data)
- Reducing reliance on third-party data for activation
- Persisted, Unify data from multiple sources for a comprehensive view
- Convert unknown into known customers to build ‘trusted profiles’
- Privacy: PII classification, right to forget
- Integrated with analytics
- Prioritize proximity of data to consumer-facing engagements: real-time, contextualized information to activate campaigns
- Pseudonymized second-party data sharing
How does a data clean room work?
With a comprehensive system of controls, data clean rooms ensure secure and reliable data handling. Users can be sure that the information they receive is free from unauthorized tampering or alteration. Data owners have complete control over permissions to access their sensitive Personally Identifiable Information (PII) data, granting approved partners anonymized feeds.
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Data resides in the respective environments
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Identified keys are used to join datasets (Exact/ rule-based/ third-party identity resolution)
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Define, validate & execute the query to be executed
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Publish aggregated results
Data clean room utilities
Data clean rooms are dynamic and secure data containment solutions to facilitate collaborative workflows while protecting confidential information, and can be used in various scenarios, such as
- Facilitating financial transactions,
- Performing market analysis,
- Conducting secure vetting processes, and
- Providing disclosure reviews.
Additionally, they help enterprises maintain information privacy while meeting regulatory compliance standards like the Health Insurance Portability and Accountability Act (HIPAA) or GDPR, protecting their customers and businesses by minimizing cyber-attack risks. By utilizing data clean rooms, companies can access up-to-date customer information without compromising their databases’ accuracy or integrity.
Data clean rooms are becoming a popular tool for many enterprises, mainly digital marketers.
Enterprises also benefit from efficient data clean-up processes to improve accuracy and data consolidation, providing better data analysis options. These processes add tangible value to companies that use data clean rooms as they help streamline operations, make data more secure, and reduce operational costs.
Through consistent monitoring and increased awareness, data clean rooms promise a more secure future for data-driven industries as they move into Industry 4.0.
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