Stagwell's Privacy-First ID Matching

Stagwell deploys privacy-safe identity matching on Databricks, allowing brands to enrich customer data without exposing sensitive information.

Diagram illustrating the flow of data and privacy controls in Stagwell's identity matching solution on Databricks.
Stagwell's privacy-safe identity matching solution architecture on Databricks.
Visual TL;DR
Fragmented Customer DataDriver
brands accumulate valuable first-party data in silos
From the article 4 mentionsMarketers are grappling with a persistent challenge: securely connecting fragmented first-party data with identity graphs.
StagwellCore
Stagwell is pioneering a solution on the Databricks platform
From the article 5 mentionsThe app then initiates a "Packaged Clean Room," allowing the brand to execute Stagwell's matching notebook instantly.
Privacy RisksDriver
traditional data exports expose sensitive information and compliance hurdles
From the article 2 mentionsHistorically, this meant sending customer data to a third party, a process fraught with privacy risks and compliance hurdles.
Databricks Marketplace AppsCore
pre-built applications run directly within the brand's own Databricks
From the articleDatabricks Marketplace Apps fundamentally alter this dynamic.
Privacy-Safe ID MatchingEffect
From the article 6 mentionsNow, Stagwell is pioneering a solution on the Databricks platform that addresses this head-on, enabling privacy-safe identity matching at scale.
Enrich Customer DataEffect
brands can enrich customer data without exposing sensitive information
From the article 3 mentionsThis means data never leaves the customer's secure environment.
Actionable InsightsOutcome
from insights to activation for marketers
From the article 2 mentionsThey've developed a clean room application that securely ingests brand data, matches it against the Stagwell Identity Spine, and generates privacy-safe insights.
Contents(3)

Marketers are grappling with a persistent challenge: securely connecting fragmented first-party data with identity graphs. The traditional approach involved risky data exports, exposing sensitive information and creating compliance headaches. Now, Stagwell is pioneering a solution on the Databricks platform that addresses this head-on, enabling privacy-safe identity matching at scale.

Brands accumulate valuable first-party data, purchase histories, CRM records, website interactions, but this data often sits in silos. To build comprehensive audience profiles, they need to link this data to external identity graphs, which span emails, device IDs, and offline touchpoints. Historically, this meant sending customer data to a third party, a process fraught with privacy risks and compliance hurdles.

The Marketplace App Revolution

Databricks Marketplace Apps fundamentally alter this dynamic. Instead of brands sending data out, pre-built applications run directly within the brand's own Databricks workspace. This means data never leaves the customer's secure environment.

Stagwell's offering is a prime example. They've developed a clean room application that securely ingests brand data, matches it against the Stagwell Identity Spine, and generates privacy-safe insights. The process is streamlined: brands install the app, connect their data, and initiate the matching workflow.

Seamless Integration, Robust Security

The end-to-end flow is designed for efficiency and security. After installation and authentication, brand users select their first-party data tables. The app then initiates a "Packaged Clean Room," allowing the brand to execute Stagwell's matching notebook instantly. Critically, the brand sees the notebook's name but not its proprietary source code, protecting Stagwell's intellectual property.

During the matching process, the notebook joins brand data with the Identity Spine, resolving identities across multiple identifiers. It computes match rates, coverage metrics, and household/consumer IDs. All processing occurs within the clean room boundary, ensuring no raw data leakage and full policy enforcement.

From Insights to Activation

Once matching is complete, the app delivers aggregated insights like demographics, behavioral segments, and geographic distribution. This closes the loop, enabling brands to activate enriched audience profiles through Stagwell's Agentic Targeting System (SATS).

This shift represents a move toward governed collaboration and on-demand identity resolution. Other data providers can adopt this model to monetize their IP securely, offering solutions for retail media networks, healthcare data, and financial services without compromising customer data privacy.

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Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.