Guide 173 · Conversions · GA4 + Tag Manager
User key events in GA4: users who triggered a key event, and the user key event rate
User key events counts users who performed a key event at least once in the date range. It is the user-scoped twin of sessions with key events, and it is smaller whenever one person visits more than once. This guide reads it in User acquisition, computes the user key event rate, and works out how the two counts differ for the same week.
After the steps, the purchase key event appears under the Key events tab in Admin, and the standard reports show it within a day. The worked example below gives the count and the rate to expect.
Download the reference: the purchase key-event reference (JSON) (750 bytes, MD5 0b9a43d3d44514e8eedb521979335715). It holds the event name, the counting method, the worked-example figures recomputed for this guide, and the checkpoints that prove the key event is recording. The figures in the file are the same figures shown on this page.
What you need
- Editor access or above at property level in GA4. Marking an event as a key event is a property setting, and the star in the Events table does not appear for a Viewer.
- At least one key event marked, so the numerator exists. In this guide the marked events are purchase and generate_lead.
- A date range stated up front. Users are counted once per date range, so the same user counts once in a week and can count again in the next week.
The trace
- Open Reports, then Acquisition, then User acquisition. The table counts users, with Users and User key events side by side. First user source / medium is the dimension here, because the scope is the user, not the session.
- Read the User key events column. It counts users who triggered at least one key event in the range. In the worked example the 28-day window shows 1,100 users and 143 users with a key event.
- Divide users with a key event by users. 143 / 1,100 = 13.00%. That is the user key event rate. It answers how many of the people who arrived did the thing at least once.
- Compare it with the session rate for the same window. The same window shows 1,842 sessions and 187 sessions with a key event, which is 187 / 1,842 = 10.15%. The user rate is higher here because repeat visitors stack up sessions faster than they stack up users.
- Check the gap between the two counts. Sessions with a key event number 187 against 143 users with a key event, a gap of 44. Those 44 are repeat sessions by users who already counted once at user scope.
- Do not add user key events across channels. One user can arrive through two channels in the same range and count in both rows. The total row is the deduplicated count; the channel rows added together are not.
Dead ends
DEAD END — ADDING CHANNEL ROWS TO GET THE TOTAL. Channel rows overlap at user scope. The sum of the rows is larger than the total row, and quoting the sum overstates the number of people who converted.
DEAD END — COMPARING A USER RATE WITH A SESSION RATE AS IF THEY WERE THE SAME. The two rates have different denominators and different meanings. A user rate of 13.00% and a session rate of 10.15% for the same window are both correct, and neither is the wrong one.
DEAD END — EXPECTING USER KEY EVENTS TO EQUAL THE KEY EVENTS COUNT. The key events count is events, and user key events is people. A person who buys twice counts twice as key events and once as a user with a key event.
End state
The window closes at 143 users with a key event out of 1,100 users, a user key event rate of 13.00%, against 187 sessions with a key event out of 1,842 sessions.
| Figure | Value |
|---|---|
| Users in the window | 1,100 |
| Users with at least one key event | 143 |
| User key event rate | 13.00% |
| Sessions in the window | 1,842 |
| Sessions with at least one key event | 187 |
| Session key event rate | 10.15% |
| Repeat sessions by converting users | 44 |
The user rate is 143 / 1,100 = 13.00% and the session rate is 187 / 1,842 = 10.15%, both recomputed in Python 3 and rounded to two places. The gap is 187 − 143 = 44. The figures are a worked example, not a real property.
Sources
- Analytics Help — About key events — marking an event as a key event, the 30-event limit for a standard property, and 50 for Analytics 360
- Analytics Help — Conversions vs. key events in Google Analytics — what a key event is, the event to key event to conversion flow, and where Google Ads conversions appear
Checked 11 November 2026. The click path above is the one in Google's help pages, read 11 November 2026. User key events as users who performed a key event, and the user key event rate as that count divided by users, are as Google documents them. No step in this guide was run inside a live Analytics property, because the reports need a Google sign-in and this site does not sign in as anyone. The figures on this page are a worked example recomputed in Python 3 with decimal arithmetic, not numbers from a real property. Google moves menu items without warning; if a path on this page no longer matches, the linked help page is the current map.