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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteYou can move tracking from Google Analytics 4 (GA4) to Umami without losing the ability to answer important business questions, but a tracker swap alone will not preserve your reports. First document the metrics and event definitions you rely on, retain a separate copy of GA4’s event data where possible, then run GA4 and Umami in parallel and validate the replacement against matched dates and scopes. Treat any Umami history import as unverified until you confirm exactly what it accepts and reproduces.
What to preserve before changing your tracker
Start with the decisions your analytics support, not a list of every GA4 report. For each important report, write down the question it answers, the date range and filters people use, and the numbers that affect a decision. Include acquisition, landing pages, conversions and campaign performance, along with any custom event or parameter analysis the business actually uses.
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Make a measurement inventory
Record the current event names, parameters, trigger conditions, key events, UTM conventions, domains, and custom dimensions or metrics. Note exclusions and filters that affect reports, too. Two products can show the same event label while counting different actions or applying different rules; the label alone is not proof that the measurements match.
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- Events: What action triggers each event, and which parameters give it meaning?
- Conversions: Which events count as key outcomes, and under what conditions?
- Campaigns: Which UTM values and naming conventions are in use?
- Scope: Which domains, streams, date ranges, time zones, and filters belong in the reports?
- Decisions: Who uses each report, and what would they need to answer after the migration?
Keep a separate GA4 data archive
If BigQuery export is available for your GA4 property, configure it before relying on a replacement for historical analysis. Google’s setup guidance describes choosing data streams and events for export, so check those selections against your preservation plan. BigQuery can involve storage and query-processing costs; Google also describes a sandbox with limits and says a valid payment method is required for export to proceed. Review the current BigQuery export setup requirements before enabling it.
GA4’s BigQuery export includes daily tables named events_YYYYMMDD. If streaming export is enabled, an events_intraday_YYYYMMDD table is created and later replaced by the completed daily table. The schema includes event names, timestamps, event parameters, and other event-specific fields. Google says daily tables can be updated for late-arriving events for up to three days after an event date, so wait for that window to pass before treating a daily table as complete. See Google’s BigQuery export schema.
Keep the export and your measurement inventory as separate source records. Do not make access to important GA4 history depend on a new tracker or an import whose behavior you have not confirmed.
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Recreate the measurements that matter in Umami
Use the inventory to configure Umami around the questions you need to answer, rather than mechanically copying every GA4 event. Umami documents custom event tracking and built-in features that include goals, funnels, retention, UTM insights, and dashboards. Its feature documentation describes those capabilities; the exact fit depends on how your own events and reports are defined.
Umami’s tracker documentation says the default setup initializes pageview tracking, click tracking, and path-change detection. It also documents domain restrictions and controls for automatic tracking. Check tracker configuration against your implementation, especially if you use a single-page application, have staging domains, or depend on particular event parameters. Confirm that consent and privacy requirements are met in your actual deployment before treating the new data as a valid replacement.
Keep campaign naming consistent
Use the same agreed UTM conventions in links after the cutover. Umami’s UTM insight breaks down views using utm_source, utm_medium, utm_campaign, utm_term, and utm_content; its documentation says the insight requires no additional parameters. See Umami’s UTM documentation. Test representative campaign links and check the resulting classifications so a change in spelling or naming does not appear to be a change in campaign performance.
Run GA4 and Umami together, then compare like with like
Keep both systems collecting during a defined validation window. Choose matching date ranges, domain scope, and event definitions, then compare pageviews and a small set of priority events, conversions, and campaign dimensions. The goal is to establish whether Umami can support the decisions identified in your inventory—not to assume both tools will produce identical totals.
- Confirm collection: Trigger each priority action on the site and check that its corresponding Umami event appears.
- Match the comparison: Use the same dates, domains, time-zone assumptions, and comparable event definitions in both products.
- Check campaigns: Test representative UTM-tagged links and confirm source, medium, and campaign values are classified as expected.
- Investigate differences: Check trigger logic, exclusions, time zones, filters, duplicate tagging, and differences between product definitions.
- Test the real work: Have the people who use the reports answer their named decision questions using Umami, the archive, or both.
Google’s published 2–5% expected difference concerns total event counts when comparing GA4 reports with GA4’s BigQuery export after checking relevant settings. It is not a tolerance for comparing GA4 with Umami. Google’s comparison guidance also calls out confirming the intended property and BigQuery project, aligning reporting identity and time zones, and checking that streams or events have not been excluded.
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What happens to GA4 history in Umami?
Umami’s platform page advertises importing data from Google Analytics, but the reviewed product material does not specify the exact GA4 export formats, importable fields, time-range limits, or which reports and dimensions are reproduced. That means an import option is not proof that every historical report, event detail, or dimension will be available in Umami afterward. Check the current import workflow or vendor documentation for those specifics before making an import the sole copy of your history. The Umami platform page describes the advertised capability.
Google’s own Data Import documentation does not establish what Umami accepts. Google describes its Data Import feature as joining imported data with GA4 data, with joins occurring during collection or processing in some cases and at report or query time in others; the effects on historical data and deletion differ. See Google’s Data Import documentation.
Use a cutover gate, not an arbitrary date
Switch off the old collection only after the migration passes checks tied to your requirements:
- Priority events appear in Umami when the corresponding actions are triggered.
- UTM classifications make sense for representative campaign links.
- Stakeholders can answer their named decision questions with Umami reports, the GA4 archive, or a documented combination of both.
- The people who need historical analysis can access the GA4 export.
- The organization’s retention and privacy policy supports ending the old collection.
Umami presents both managed cloud and self-hosted deployments on its platform page. Choose the operational model that fits your hosting and administration needs; regardless of deployment, the measurement mapping and validation work still applies.
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