Track website traffic, user behavior, and conversion rates with comprehensive analytics
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GA4's interface is built for exploration, not for a recurring report. This template pins the dimensions and metrics you actually report on so the same numbers appear the same way every month.
The actual columns, with sample rows
| A | B | C | D | E | F | G |
|---|---|---|---|---|---|---|
| 1 | Date | Source / medium | Sessions | Engaged | Conversions | CVR |
| 2 | 2026-07-01 | google / organic | 3,412 | 2,180 | 64 | 1.88% |
| 3 | 2026-07-01 | google / cpc | 1,905 | 1,102 | 51 | 2.68% |
| 4 | 2026-07-01 | (direct) / (none) | 1,244 | 863 | 29 | 2.33% |
| 5 | 2026-07-01 | newsletter / email | 612 | 498 | 22 | 3.59% |
Why each one is written the way it is
=IF([@Sessions]=0, 0, [@Conversions]/[@Sessions])
Conversion rate per source. Guarding the denominator matters here because low-volume sources routinely have zero-session days.
=IF([@Sessions]=0, 0, [@Engaged]/[@Sessions])
Engagement rate, GA4's replacement for bounce rate. Reporting it alongside CVR distinguishes a traffic quality problem from a landing-page problem.
=SUMIFS(Sessions[Sessions], Sessions[Date], ">="&EOMONTH(TODAY(),-2)+1, Sessions[Date], "<="&EOMONTH(TODAY(),-1))
Last full month, computed rather than typed, so the report does not need editing each month.
=IMPORTRANGE("<sheet-id>", "GA4_export!A:F")
For Google Sheets: pulls a scheduled GA4 export from another file, keeping raw data and reporting separate. In Excel the equivalent is a Power Query connection.
A worked example with real numbers
A marketing team reported organic sessions from GA4's default view and paid sessions from the ads platform, and the totals never reconciled. Landing both in one sheet on the same date grain, with source/medium as the only channel dimension, removed the discrepancy — most of which turned out to be auto-tagged paid traffic being counted as organic in one of the two views.
Tab by tab
| Tab | Contents |
|---|---|
| Sessions | Date, source/medium, sessions, engaged sessions, conversions. |
| Pages | Landing-page level detail for the same period. |
| Report | Month-on-month summary with the comparisons you present. |
| Goals | Conversion definitions and their monetary value. |
| README | How to configure the GA4 export that feeds the Sessions sheet. |
What is included, and what to look at next
Specific to this workbook, not generic
In Google Sheets, yes, through the official GA4 connector or a scheduled export. In Excel, use Power Query against the GA4 Data API. Both are a small automation project if you want it unattended.
Because they change. Dimension defaults, attribution models and even metric names have shifted between releases. A sheet holding your own extracted history stays comparable across those changes.
Add a Property column to the Sessions sheet and every aggregation gains a dimension. Keeping them in one table beats one tab per property, which cannot be compared.
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