Before you start, make sure you understand what you lose and gain when leaving Google Analytics.
Switching analytics tools isn’t hard. Switching without losing data, breaking reports, or confusing your team — that’s where most companies stumble. This analytics migration checklist covers everything you need to do before you flip the switch.
I’ve helped 50+ businesses migrate from Google Analytics to privacy-first alternatives. The ones who followed a checklist had smooth transitions. The ones who rushed? They spent weeks fixing problems that could’ve been prevented.
Why You Need a Migration Checklist
Analytics migration isn’t just installing a new script. It’s a process that touches:
- Historical data — years of insights you can’t recreate
- Custom reports — dashboards your team relies on daily
- Integrations — tools connected to your current analytics
- Team workflows — habits and processes built around old metrics
Skip any of these, and you’ll feel the pain for months. A proper checklist takes a few hours upfront but saves weeks of cleanup later.
Before You Switch: The Complete Checklist
1. Export Your Historical Data
For automation options, see our data export comparison of Plausible, Simple Analytics, and Fathom.
This is non-negotiable. Once you switch analytics tools, your historical data stays in the old platform — and if you’re leaving GA4, Google’s data retention policies mean it won’t stay forever.
What to export:
- Monthly traffic summaries (at least 2 years)
- Top pages by pageviews
- Traffic sources breakdown
- Conversion data (goals, events, transactions)
- Geographic and device reports
How to export from GA4:
- Use the GA4 interface: Reports → Export (CSV or PDF)
- Connect to BigQuery for raw data export (requires setup)
- Use the Google Analytics API for automated exports
- Third-party tools like Databox or Supermetrics can help
Pro tip: Export more than you think you need. You can’t go back once access is revoked.
2. Document Your Current Tracking Setup
Before you can rebuild, you need to know what you have. Create a document listing:
- Events you’re tracking — button clicks, form submissions, video plays
- Goals and conversions — what counts as success
- Custom dimensions — user properties, content groupings
- Filters — IP exclusions, spam filters, internal traffic
- E-commerce tracking — if applicable
Most privacy-first analytics tools are simpler than GA4. You won’t recreate everything — and that’s often a good thing. But you need to know what exists before deciding what to keep.
3. Identify Critical Reports and Dashboards
Talk to everyone who uses your analytics. Ask them:
- What reports do you check weekly?
- What metrics drive your decisions?
- What would break your workflow if it disappeared?
You’ll likely find that 80% of your team uses 20% of available reports. Focus your migration on recreating those critical few, not everything.
Common critical reports:
- Traffic overview (daily/weekly/monthly)
- Top content performance
- Referral sources
- Conversion tracking
- Campaign performance (UTM reports)
4. Audit Your Integrations
Your analytics likely connects to other tools. Check for:
- Marketing platforms — email tools, ad platforms, CRMs
- Reporting tools — Data Studio, Tableau, custom dashboards
- A/B testing tools — that rely on analytics data
- Tag managers — Google Tag Manager configurations
- Automation — Zapier, Make, custom scripts
For each integration, determine: Can the new analytics tool connect? Do you need a workaround? Or can you drop it entirely?
5. Choose Your New Analytics Tool
For EU businesses, GDPR compliance is crucial. See our GDPR-compliant analytics guide for detailed tool comparisons.
If you haven’t picked a replacement yet, consider:
| Factor | Questions to Ask |
|---|---|
| Privacy compliance | GDPR-compliant? Cookie-free? EU data storage? |
| Features needed | Event tracking? Funnels? E-commerce? |
| Budget | Monthly cost at your traffic level? |
| Technical setup | Cloud hosted or self-hosted? API access? |
| Team adoption | How easy for non-technical users? |
Popular privacy-first options include Plausible, Fathom, Umami, and Matomo. Each has trade-offs — simpler isn’t always better if you need advanced features.
6. Plan Your Parallel Tracking Period
Never switch analytics cold. Run both old and new tracking simultaneously for at least 2-4 weeks. This lets you:
- Verify the new tool is collecting data correctly
- Compare numbers between platforms (they won’t match exactly — that’s normal)
- Catch missing events or pages before you lose the safety net
- Train your team on the new interface
Warning: If you’re removing Google Analytics for privacy reasons, check whether running both temporarily affects your compliance. Some businesses need to switch immediately.
7. Prepare Your Team
Technical migration is easy. People migration is hard. Before switching:
- Announce the change — explain why you’re switching (privacy, simplicity, cost)
- Provide training — even 30 minutes on the new interface helps
- Update documentation — SOPs that reference old analytics
- Set expectations — some historical comparisons won’t be possible
The biggest migration failures I’ve seen weren’t technical — they were teams reverting to old habits because nobody explained the new workflow.
8. Update Your Privacy Policy
Your privacy policy likely mentions Google Analytics. When you switch to a privacy-first tool, update it to reflect:
- Which analytics tool you now use
- What data is collected (usually much less)
- Whether cookies are used (often none)
- Where data is stored (EU vs US)
This is especially important if GDPR compliance was your reason for switching. Your privacy policy should match your actual practices.
Migration Day Checklist
When you’re ready to make the switch:
- ☐ Historical data exported and stored safely
- ☐ New tracking code installed on all pages
- ☐ Events and conversions configured
- ☐ Team trained on new interface
- ☐ Critical reports recreated
- ☐ Integrations updated or replaced
- ☐ Privacy policy updated
- ☐ Old tracking code removed (after parallel period)
Common Migration Mistakes to Avoid
Rushing the timeline. A proper migration takes 2-4 weeks minimum. Trying to do it in a day leads to gaps and errors.
Not exporting historical data. “I’ll do it later” becomes “I can’t access that anymore.” Export first, always.
Expecting identical numbers. Different tools count differently. A 10-20% variance is normal. Don’t panic.
Forgetting mobile apps. If you have apps, they need separate migration planning.
Ignoring team adoption. The best analytics tool is useless if nobody uses it.
Bottom Line
A successful analytics migration comes down to preparation. Use this checklist before you switch analytics tools, and you’ll avoid 90% of common problems. Rush it, and you’ll spend months cleaning up the mess.
The checklist might seem long, but most items take minutes. The historical data export is the only time-consuming part — and it’s the most critical.
Ready to migrate? Start with step one: export your data. Everything else can wait, but your historical data can’t.
