New User / Returning User is a lifecycle split of the distinct user population within a date range. A new user is a browser/user ID that your analytics system first saw during the selected period. A returning user was first seen before the period and came back within it. This is about people (or more precisely, identifiers), not traffic volume like sessions or pageviews.
Why it matters: this split shows acquisition vs. loyalty. More new users means your top-of-funnel channels are working; more returning users hints at product-market fit, retention, and healthy engagement. Use it alongside User Retention and Cohort Analysis to see whether newcomers stick.
How is it measured?
- Identity basis: usually a first-party cookie or logged-in user ID. Cross-device or cross-browser behavior may fragment identity if you can’t stitch IDs under a single User.
- Date logic: classification is evaluated per report range. A user can be new in March and returning in April.
- Data retention: if identifiers expire (cookie purges, privacy limits), some true returners will be miscounted as new.
- Scope: counts are unique users in the period, not sessions.
Common pitfalls:
- Cookie resets / ITP / ad blockers inflate “new”.
- Device switching downgrades “returning” unless you have stable login-based IDs.
- Channel analysis should use consistent attribution windows to avoid miscrediting acquisition.
Formulas & mini-example
- New User Rate =
New Users / Total Users - Returning User Rate =
Returning Users / Total Users
Example (weekly report):
| Status | Count | Rate |
|---|---|---|
| New Users | 500 | 62.5% |
| Returning Users | 300 | 37.5% |
| Total Users | 800 | 100% |
Interpretation: acquisition is strong (62.5% new). Next step—check if these new users convert and come back (see Cohort Analysis and User Retention). Pair this with engagement metrics like Session depth and Pageview quality to avoid vanity wins.