Google Optimize Is Gone: Current A/B Testing Alternatives
Learn why Google shut down Optimize in September 2023 and which A/B testing platforms to migrate to, from VWO and Optimizely to server-side testing.
Google Optimize was the free A/B and multivariate testing tool Google offered for websites; the company shut it down in September 2023. This page answers the two questions people searching for Optimize actually have: why it was discontinued, and what to use in its place today.
Why was Google Optimize shut down?
Google stated that the tool did not deliver the scale and feature set its users expected, and redirected its resources toward third-party integrations inside GA4. The practical consequence: any testing program built on Optimize now has to migrate to an alternative, and the old setup guides no longer apply.
Current A/B testing tools
| Tool | Strength | Best fit |
|---|---|---|
| VWO | Visual editor and heatmaps in one place | Mid-sized teams |
| Optimizely | Enterprise experimentation infrastructure, server-side testing | Large teams |
| AB Tasty | Personalization and testing combined | Marketing-led teams |
| Convert | Privacy-focused, transparent pricing | Accessible for SMBs and lean in-house teams |
| Your own stack (server-side) | Full control, data ownership | Product teams with engineering resources |
What to watch during the migration
- Rescue your experiment archive. If the historical test results in Optimize were never exported, that institutional memory is gone; the list of winning variations should be carried into the new tool.
- Anchor measurement to GA4 events. Whichever tool you choose, the conversion definition must live in a single source of truth (GA4); when in-tool metrics and GA4 tell different stories, no decision can be made.
- Protect statistical discipline. The tool changes, the rules do not: pre-test sample size calculation, a 95 percent confidence threshold, and no early stopping.
Can you start without a tool?
On low-traffic sites there are cheaper steps to take before building full A/B infrastructure: locating the bottleneck with scroll and click maps, running sequential single-variable tests, and reading the outcome from the conversion funnel. The full approach is covered in our work on AI-driven A/B testing, and the Acıbadem success story shows step by step how such an experiment is set up in practice.
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