Privacy-first Analytics

Privacy-first analytics is an approach that measures behaviour with the least personal data possible: identifiers scoped to one domain, aggregated reporting and short retention.

This is not a single feature but a set of independent decisions: the scope of the identifier, how the IP address is handled, how long data is retained, where it is stored, and which fields are never collected at all. The cost shows up in analysis: cohorts and funnels on a first-party identifier still work, while cross-site audience building and multi-device attribution are lost without identity stitching. The common error is reading the phrase as a binary badge, since one tool can be strict on one axis and fully permissive on another, so the collection and retention settings and the tool's own privacy policy are what should be read, not the label.