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Enterprise Layer Intelligence
Categories/Data Platform & Integration/InfoSum
InfoSum

InfoSum

Founded by Nick Halstead in 2015

Connect customer datasets across different companies without sharing or exposing sensitive underlying records

Pricing model

Paid

Rating

★ People love it

Time to value

Moderate Setup (1-3 hours)

You can use InfoSum to collaborate on first-party data with external partners without actually moving or sharing raw customer records. It lets advertisers, media owners, and data providers match consumer datasets in decentralized environments. You can run audience analysis, plan targeted marketing campaigns, and measure conversion lift while keeping private identifiable details secure across cloud providers. Teams can also build private data networks with commercial partners to uncover joint market segments and evaluate ad performance without relying on third-party cookies or centralizing data pools.

What InfoSum does

Connect internal customer data files to secure decentralized clean roomsCalculate match rates between brand audiences and publisher datasetsBuild joint audience segments for programmatic media activationGenerate conversion lift reports comparing exposed versus control groupsConfigure data governance rules to restrict partner query permissionsExport aggregated audience insights for media planningDecentralized architecture that prevents raw data from moving between organizationsDirect matching of first-party consumer records across separate cloudsBuilt-in differential privacy controls to block individual re-identificationMulti-party audience overlap analysis without centralizing database recordsDirect campaign activation across media owners and retail networksClosed-loop measurement and incremental sales lift attribution

Pricing breakdown

Pricing model: Paid

Frequently asked

SnowflakeSnowflakeGoogle CloudGoogle Cloud

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InfoSum, data clean room, data collaboration, decentralized data, first-party data, audience matching, identity resolution, privacy-enhancing technology, retail media networks, conversion lift, media measurement, differential privacy, audience overlap, clean room