Probabilistic Identity Resolution
Probabilistic Identity Resolution uses machine learning to infer connections between devices, sessions, and behaviors that likely belong to the same user. It relies on patterns such as IP address ranges, device types, and browsing behavior rather than personally identifiable information.
For example, if a user visits a website on mobile and later completes a purchase on desktop from the same network, probabilistic identity graphs can link those actions with high confidence.
This technology is crucial in a privacy-first world, where deterministic identifiers like cookies or device IDs are increasingly restricted. It enables accurate cross-device tracking, frequency management, and attribution without violating privacy laws.
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