Life After Google Optimize: Alternatives

Product and engineering teams should move forward with a new approach to A/B testing now that Google Optimize is being sunsetted

Best Practices
May 11, 2023
Image of Ken Kutyn
Ken Kutyn
Senior Solutions Consultant, Amplitude
Life After Google Optimize: Alternatives

After months of rumors and speculation, Google has officially announced that Google Optimize and Google Optimize 360 will be sunsetted on September 30th, 2023. Google acquired a significant market share in the website A/B testing space and this announcement has left companies scrambling to find a suitable replacement.

And making all of this even more complicated is the forced transition from Google Analytics 360 to GA4 which means many companies are now rethinking their digital analytics strategy overall. GA4 and Google Optimize customers now have an opportunity to consider whether another technology solution might give them deeper analytics along with an integrated approach to experimentation.

Teams are under pressure to find an alternative quickly. The question is: what should you do next?

The right next steps won’t be the same for every company and really depend on a variety of factors, including your team’s testing maturity, your use cases, the type of products you have, your technical architecture, team ownership, available resources, budget considerations, and your broader tech stack.

There are three choices Google Optimize customers have now that they must move on from Google Optimize.

1. Look for a similar a/b testing tool

The market is well-saturated with similar WYSIWYG-driven products that make it relatively easy to run simple experiments within a web browser. However, there are many differences in these tools that can make or break your experimentation efforts.

Evaluating a web A/B testing solution requires careful consideration of factors like tag size and performance, how they manage user privacy and personal data, what integrations are available, the tool’s compatibility with your tech stack, what stats methods it offers, and the commercial and licensing model.

While it might appear that your company will be better off searching for a comparable tool to Google Optimize, these tools will always be limited to running experiments in the browser only. This means that your product and engineering teams won’t have the ability to optimize your key product experiences and UI to deliver personalization. It will also make it very challenging to optimize your mobile and server-driven experiences.

2. Consider moving to a product-led experimentation platform

While this could be a significant shift in how you experiment today, it also unlocks substantial new opportunities to maximize your product investments, when you transition to product-led experimentation.

Some of these new opportunities include:

  • The ability to test more complex use cases
  • Align your experimentation workflows with product development workflows
  • Achieve higher performance tests with less latency
  • Ensure a safer approach to user privacy

For product and growth teams with access to developer resources, the “Google Optimize Sunset” represents a unique opportunity to align experimentation workflows with how they build and ship features. This could be just the push that you need to up-level your experimentation program and start building richer tests that run across devices and deep into your tech stack.

I recently wrote about this topic in more depth: here are the five signs that your team is ready for product-led experimentation.

3. Stop experimenting altogether

As a free tool, Google Optimize naturally attracted a lot of companies who were just dipping their toe into experimentation. Unfortunately, this means that for some of those companies they don’t have the resources or number of winning tests to justify a paid solution right now.


Regardless of which option makes the most sense for your company, it would be prudent to start thinking about the future of your experimentation program with your team now. Properly evaluating new software solutions, contracting and legal discussions, infosec and privacy approvals, and user onboarding can take months – and that September 30th sunset date will be here before we know it.

Check out Amplitude Experiment to learn more about our approach to product-led experimentation today.

About the Author
Image of Ken Kutyn
Ken Kutyn
Senior Solutions Consultant, Amplitude
Ken has 8 years experience in the analytics, experimentation, and personalization space. Originally from Vancouver Canada, he has lived and worked in London, Amsterdam, and San Francisco and is now based in Singapore. Ken has a passion for experimentation and data-driven decision-making and has spoken at several product development conferences. In his free time, he likes to travel around South East Asia with his family, bake bread, and explore the Singapore food scene.

More Best Practices
Image of Darshil Gandhi
Darshil Gandhi
Principal Product Marketing Manager, Amplitude
Image of Darshil Gandhi
Darshil Gandhi
Principal Product Marketing Manager, Amplitude