Secure Data Collaboration

Deliver Data Clean Rooms for Your Customers

Aqfer’s secure data collaboration technology enables our clients to build and deploy a “data clean room” – a dedicated, secure, protected environment to enable collaboration and computation between multiple parties. Personally Identifiable Information (PII) is often encrypted and transformed in privacy-compliant ways to ensure it is only accessible by the brand. Data collaboration gives businesses access to more data, allowing them to improve their predictive models and provide more valuable services

Brands Remain in Complete Control of Their Data

Aqfer enables brands to own their data and bring their applications to it, all within a brand-owned secure environment. Whether it’s first or third-party data, brands have the infrastructure in place to collect and manage their data at a granular level. This opens the door for brands to build powerful multi-touch attribution models, which is a core use case for clean rooms.

With our low-code implementation, clients can easily capitalize on the benefits of Aqfer’s secure data sharing technologies which are scalable, repeatable, and customizable. Whether your brand customer wishes to utilize Aqfer’s environment or plug into a third-party clean room, the following allows Aqfer to be fit into any brand’s martech ecosystem for all possible scenarios:


The data structure in the Aqfer ecosystem allows brands to capture granular data insights


Aqfer never sees the data–the data is all completely owned by the brand, reducing touchpoints and risk of error


Privacy compliance is assured with every step of the data’s journey

Key Benefits for Solution Providers

Stringent Data Privacy

Your member organizations can only view their own critical data.

Reduce Data Matching Friction

Faster and more accurate data matching reduces the friction between data sets.

Improved Attribution Reporting

Gain confidence in the quality and accuracy of your marketing and advertising reports

Accelerate Time-to-Market

Aqfer manages, maintains, and operates the solution keeping it repeatable and scalable

Significant Risk Reduction

Maintain control and prevent data leakage, unauthorized user access, and data breaches.

Distraction-Free Empowerment

White-labeled delivery keeps you front and center with your brands.

What Do You Need to Accomplish?

Aqfer’s secure data collaboration solutions can help you deliver the results your clients need with varying levels of security and complexity. This flexibility provides you with a scalable platform that is configurable and repeatable from client to client based on their own unique requirements.

Common Requirements

in order of increasing complexity

Aggregated Outputs
Aggregated Outputs

Summary of the composite raw data to generally answer specific questions.

Example: Overlap Rate Analysis

Scenario: Two data sets are compared to see how many records appear in both sets. The overlap is often expressed as a percentage.

Snapshot Analysis
Snapshot Analysis

Point-in-Time Analysis uses data–subject level de-identified data over a specific time period.

Example: Site Visits

Scenario: Brand X emailed a list of IDs from Supplier Z and Brand X wants to see how many of them ended up on the brand’s website

Longitudinal Analytics
Longitudinal Analytics

Repeated examination of the individual record to detect changes over time

Typically appends or enriches data records at the row level to create a more complete record.

Example: Attribution

Scenario: Matching consumer experience outcomes with media investments

Audience Activation and Decisioning
Audience Activation and Decisioning

Defining the audience criteria from multiple data sets to generate a list of IDs that match the filtering of one or more specific attributes

Example: Niche Audience Builds

Scenario: Find all consumers in New York State within 40 miles of a physical location who like to buy blue running shoes

“Aqfer’s white-label approach allowed our team to create a clean room solution for our clients and get the offering out within months. Plus, we keep competitors like Snowflake and Habu out of our client’s tech stacks, thus increasing our market share and decreasing risk.”

SVP, Product Development

Data Provider