IAB Tech Lab unveils ADMaP: a privacy-first digital ad attribution protocol

The Interactive Advertising Bureau (IAB) Technology Laboratory has unveiled a new protocol aimed at revolutionizing digital advertising attribution while prioritizing user privacy. The Attribution Data Matching Protocol (ADMaP) was released for public comment on October 15, 2024, marking a significant step towards addressing the challenges posed by the declining availability of third-party cookies and increasing restrictions on client-side data collection.

As the digital advertising industry grapples with the need for accurate measurement and attribution in an increasingly privacy-conscious world, ADMaP emerges as a potential solution. The protocol enables advertisers and publishers to securely share and measure conversion data without compromising user-specific details, leveraging advanced Privacy Enhancing Technologies (PETs).

Anthony Katsur, CEO of IAB Tech Lab, emphasized the urgency of the situation: "The shift away from traditional identifiers and associated techniques used for attribution has created an urgent need for new, privacy-forward solutions. Signal loss limits advertisers' ability to measure campaigns accurately and ultimately impacts publishers' revenues."

ADMaP utilizes several privacy-centric steps to ensure secure and private data handling:

1. Identity Mapping: Establishes a common identity space between advertiser and publisher datasets.
2. Attribution Computation: Performs attribution calculations using agreed-upon methodologies.
3. Report Generation: Produces aggregated attribution results while maintaining privacy.

The protocol employs advanced technologies such as Private Set Intersection (PSI) and Trusted Execution Environments (TEEs) to guarantee data security and privacy throughout the process.

How ADMaP works

The ADMaP workflow consists of two main components:

1. Mapping Protocol: Creates a common identity space between advertiser and publisher datasets using techniques like Private Set Intersection.
2. Attribution Protocol: Ingests exposure events from publishers and conversion events from advertisers to compute attributions securely.

The system architecture includes a Matching Service and an Aggregation Service. The Matching Service joins key records and performs attribution, while the Aggregation Service aggregates results, applies privacy measures, and generates attribution reports.

Privacy and security design goals

ADMaP adheres to strict privacy and security design goals:

1. Security of PII: Protects end-user Personally Identifiable Information (PII) through encryption.
2. Privacy of User Identity: Prevents participants from learning the identity of end-users not in their own dataset.
3. Privacy of Group Membership: Ensures participants cannot determine which of their end-users are in the computed overlap.

Industry collaboration and expert input

The development of ADMaP involved collaboration between advertisers, publishers, and data clean room experts. Edik Mitelman, General Manager of AppsFlyer, commented on the initiative: "By bringing together advertisers, publishers, and data clean rooms, we've collaboratively developed a solution that not only addresses the privacy challenges we face today but also paves the way for a more secure, transparent, and importantly measurable future for digital advertising."

Public comment period and next steps

The IAB Tech Lab has opened ADMaP for public comment until November 14, 2024. Industry stakeholders are invited to review the protocol and provide feedback. This comment period is crucial for refining and improving the protocol before its final implementation.

Implications for the Digital Advertising ecosystem

The introduction of ADMaP has several potential implications for the digital advertising industry:

1. Enhanced Privacy Compliance: By design, ADMaP helps advertisers and publishers adhere to evolving privacy regulations.
2. Improved Trust: The protocol aims to build trust between consumers, advertisers, and publishers by ensuring responsible data sharing.
3. Accurate Attribution: Despite privacy constraints, ADMaP enables more accurate campaign measurement and attribution.
4. Industry Standardization: As a potential new standard, ADMaP could streamline attribution processes across the digital advertising ecosystem.
5. Technological Advancement: The protocol encourages the adoption of advanced privacy-enhancing technologies in advertising workflows.

Challenges and considerations

While ADMaP offers promising solutions, there are potential challenges to consider:

1. Implementation Complexity: Adopting new protocols and technologies may require significant resources and expertise.
2. Industry Adoption: The success of ADMaP will depend on widespread acceptance and implementation across the advertising ecosystem.
3. Evolving Threat Landscape: As with any new technology, ongoing vigilance will be necessary to address emerging security threats and privacy concerns.
4. Balancing Privacy and Functionality: Striking the right balance between robust privacy protections and maintaining useful attribution capabilities will be crucial.

The launch of the Attribution Data Matching Protocol represents a significant step forward in the digital advertising industry's efforts to adapt to a changing privacy landscape. By enabling secure, privacy-centric attribution measurement, ADMaP has the potential to address key challenges facing advertisers and publishers alike.

As the protocol undergoes public review and refinement, its impact on the future of digital advertising measurement and attribution remains to be seen. However, the collaborative approach and focus on privacy-enhancing technologies suggest a promising direction for the industry.

Industry stakeholders are encouraged to review the ADMaP specification and provide feedback during the public comment period, which ends on November 14, 2024.

Key Facts

• Release Date: October 15, 2024
• Public Comment Period: Until November 14, 2024
• Developed By: IAB Tech Lab's Rearc Addressability Working Group
• Key Technologies: Privacy Enhancing Technologies (PETs), Private Set Intersection (PSI), Trusted Execution Environments (TEEs)
• Main Components: Mapping Protocol, Attribution Protocol
• Primary Goal: Enable secure, privacy-compliant attribution measurement in digital advertising