users
Also called: active users, total users, unique users
In web analytics, users are the count of distinct people (technically, distinct identifiers) who interacted with your site over a date range. In GA4, the default "Users" metric is Active users: the number of unique users who engaged with your site or app in that period.
Total, active, and new users
GA4 reports three flavors. Total users counts every unique identifier that fired an event. Active users counts only those who engaged, meaning they had an engaged session: one that lasts longer than 10 seconds, has a key event, or has two or more screen or page views. New users are first-time visitors who logged first_visit or first_open. Standard GA4 reports show Active users by default, so the “Users” number on your dashboard is usually engaged users, not everyone who loaded a page.
How GA4 decides who counts as one person depends on its reporting identity. It stitches activity using a User-ID you send when someone signs in, and falls back to a device or Client ID from the analytics cookie. One person on a phone and a laptop, or someone who clears cookies, can register as two users, so the number is an estimate, not a headcount. That is also why your GA4 user total rarely matches Search Console or an ad platform: they identify people differently.
For organic work, read users next to sessions and engagement-rate. Rising sessions with flat users can mean the same people returning more often. Rising users with a falling engagement-rate can mean you pulled in the wrong traffic. The metric answers “how many,” never “how good,” so it only earns its keep paired with an engagement signal.
How it affects your traffic
Users is the headline number most site owners judge SEO by, but on its own it hides why traffic moved. An SEO audit reads your GA4 users against sessions, engaged sessions, and landing pages to separate a real organic gain from a tracking artifact (duplicate GA tags, cross-domain gaps, bot hits) and to surface pages where users arrive but do not engage. That turns a raw user count into a prioritized fix list.
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