Google Optimize sunset: What to know for a successful migration

After much speculation, Google has confirmed that Google Optimize and Google Optimize 360 will no longer be available after September 30, 2023.

As an Optimize user, you may be wondering what to do now. 

What will happen with your data? How can you choose the best Google Optimize alternative?

We looked to top industry professionals to inform this comprehensive guide on how to prepare for the end of Google Optimize. Use this guide to help ensure your transition to a new tool is as smooth as possible in the coming months.

What is Google Optimize and Google Optimize 360

Google Optimize is a free website optimization tool offered by Google. It is often one of the first-used A/B testing tools due to its low barrier to entry, with the snippet being installed up to 9,000 times.

Google Optimize 360 is the paid version of Google’s optimization platform. It is an enterprise-level tool with advanced features and dedicated support from Google’s optimization team. 

Why is Google Optimize sunsetting?

According to an official statement by Google, Google Optimize and Google Optimize 360 will sunset because “it does not have many of the features and services that our customers request and need for experimentation testing.”

Many experts speculate that this change is also the result of the sunsetting of Universal Analytics in July because of how closely the platform is tied to Google Optimize.

What is the last service date for Google Optimize and Google Optimize 360?

Google Optimize and Google Optimize 360 will sunset on September 30, 2023. According to Google, “You won't be able to access your experience inference results or your historical Google Analytics raw data after the sunset date.”

Organizations using Optimize and Optimize 360 should begin a migration on the platforms long before this September date. This includes selecting a new testing tool, migrating all existing data, and running experiments on a new platform, as we’ll outline below.

Will Google Optimize and Google Optimize 360 be replaced?

As of February 2023, Google Optimize and Google Optimize 360 will not be replaced. Google announced that it would be investing in third-party A/B testing integrations with Google Analytics 4.

Google is currently working with A/B testing vendors to test their API to validate their integration. Once tested, it will become available to the public.

Firebase A/B testing, which applies to A/B testing mobile applications, will continue to operate for the time being.

There is some room for interpretation with Google’s announcement as to what will come of the Optimize platforms. However, the only way to guarantee you will be able to continue with A/B testing after September 30th is to invest in a new A/B testing tool. 

What you need to consider as a Google Optimize or Google Optimize 360 user

If you’re a Google Optimize or Google Optimize 360 user, you may be wondering what to do next. Here are three things to consider as you figure out your next moves.

The future of Google’s optimization tools

There has been a lot of speculation as to whether Google will announce another optimization solution that is compatible with GA4. 

Although Google has not announced a replacement for their optimization tools, some industry professionals remain unclear about its future.

You may decide that you would prefer to wait and see what free or low-cost alternative Google will offer. However, this poses several risks:

• You will be without an A/B testing tool for some period of time.
• A Google replacement for Optimize is not guaranteed.
• Your experimentation program will cease in the interim without a proper testing tool

For that reason, it is highly recommended that you consider Google Optimize and Google Optimize 360 to be permanently unavailable.

The current state of your experimentation program

Is your experimentation program growing or has it stagnated over the last 12 months? Are you seeing returns on your A/B testing investments, or are you struggling to get executive buy-in?

Most industry professionals agree that one of your first moves should be taking stock of how your experimentation program is performing overall. 

This includes determining:

• What is going well?
• What problems are you experiencing?
• What are the strengths and limitations with your current A/B testing tool?
• What kind of resources are currently available to you?
   

How you’d like to grow with A/B testing and experimentation

Once you consider the current state of your experimentation program with Google Optimize or Google Optimize 360, you’ll want to think about your future.

The biggest question for most companies is what does the future of your experimentation program look like?

Google Optimize users with immature testing programs who are looking to continue A/B testing should consider other free or low-cost tools. It’s worth mentioning that low-cost solutions present many challenges including lack of support, unreliable data, and limited capabilities.

Those who want to expand their A/B testing efforts and invest in an enterprise-level tool should consider a more advanced solution.

Here are some signs that you may be ready to expand your experimentation program:

• You’re looking for more advanced features like multivariate testing and an SRM checker.
• You’d like to explore server-side testing.
• You’re ready to expand into product and feature experimentation.
• You’ve seen some success, but you’ve reached your limit with what you can do with a free or low-cost solution.

Free or low-cost solutions are a good point of entry for new experimenters. However, they will only get you so far before they stop meeting the needs of you and your team.

A step-by-step guide to migrating off of Google Optimize and Google Optimize 360

If you’d like to continue A/B testing with a new solution, here is everything you need to know to ensure a successful migration.

1. Export all of your existing data

Google’s official sunset announcement states that “users won't be able to access experience inference results or historical Google Analytics 4 raw data after the sunset date.”

According to Deborah O’Malley, founder of the A/B testing website GuessTheTest, Google Optimize users should begin exporting and saving all of their historical data as soon as possible. 

Historical data will give you valuable insights into your past performance. Being able to easily reference this information allows you to use it to make better decisions going forward.

Deborah also suggests taking photos of tests for easy reference.

Data can be easily exported from Google Optimize and Google Optimize 360 via a CSV file. You have two options when it comes to exporting data:

• Optimize report: downloads a CSV file of Optimize's analysis of your variants.
• Analytics data: downloads a CSV file of the daily Google Analytics data for each of your variants.

Note that you should not export data while an experiment is running. This guide from Google explains exactly how to export your data from Google Optimize. 

2. Set a migration date two months out of Google Optimize sunset

September 30, 2023 is the last day Google Optimize will be available. However, you should be fully migrated off of the platform and using your new testing solution before this date.

Marianne Stjernvall, founder at Queen of CRO, suggests setting a migration date two months ahead of the Google Optimize sunset, on July 31, 2023. Your migration date is the date by which you need to be fully up and running with your new solution. 

The reason being that it takes approximately two months to complete one full cycle of an experimentation program.

This means you need to complete all the necessary migration steps including evaluating your existing program, selecting a new A/B testing tool, and running your first A/A test by the end of July.

3. Evaluate and select a new A/B testing tool

Selecting a new A/B testing tool is one of the most important steps in your Google Optimize migration process. It should consist of the following steps:

1. Request a demo from those selected vendors and evaluate them based on your table stake criteria.
2. Select one or two vendors that are compatible with your existing tech stack and meet your consideration criteria.
3. Deciding on a vendor at least one month out from your migration date to give adequate time for onboarding.

There are many ways to go about evaluating and selecting an A/B testing solution. Here are three useful frameworks to help you make a decision.

Eight questions to ask A/B testing vendors

We interviewed Shiva Manjunath, Experimentation Manager at Solo Brands and leading voice in the industry, to learn more about how to successfully switch A/B testing tools.

He listed eight questions you should ask A/B testing vendors when selecting a new tool. These questions will help ensure you are selecting a solution that will meet your business’s needs.

1. How long will it take from purchase to launching of the first non-A/A test?
2. Will the A/B testing vendor support migration of segments/data/past tests into the new platform?
3. How scalable is the platform/pricing model? 
4. What does support look like if I need help with my experiment setup/test results/data etc.?
5. Does the tool allow for deep dives into the data/analysis WITHIN the tool?
6. Are there any significant impacts on site speed associated with how the tool will be implemented? 
7. What does project management look like in the tool? 
8. Does the tool work within my current tech stack?

Speero’s “Familiarity vs. Specialty” matrix

Ben Labay, CEO at Speero, created a matrix which organizes A/B testing tools according to how familiar people are with them, what they offer, and how specialized they are.

You can use this matrix to find a tool that will fit the needs of your organization most effectively. 

Most organizations will do best with a tool that is somewhere in the middle in terms of “specialities.” Selecting a comprehensive tool that offers features you can grow into is a great way to future-proof your solution without becoming overly specialized.

It’s also important to understand “familiar” does not necessarily equal “better.” Many of the most familiar tools are also the least specialized and therefore, may not suit many of the needs of growing businesses.

Five stages of A/B testing and important features to consider

As mentioned, choosing the right tool comes down to understanding what you need to accomplish with your experimentation and business goals.

We worked with top CRO consultants to develop a comprehensive list of features to look for when choosing an A/B testing tool, organized by the stages of A/B testing. 

Those stages are:

• Stage 1: Setting your goals and your variants
• Stage 2: Preparing your tests
• Stage 3: Analyzing your results
• Stage 4: Ensuring you have the right support throughout the process
• Stage 5: Planning for future optimization: server-side testing and feature experimentation

For each of these stages, several features are essential to successfully carry out your A/B tests and obtain reliable results.

For a complete list of features that you’ll need to successfully carry out each stage of A/B testing, you can refer to our article on choosing an A/B testing tool.

You can use this list of features when evaluating A/B testing platforms to ensure you are choosing a solution that has the features you’ll need the most.

4. Begin the migration process

When migrating off of Google Optimize, you need to think about what you want to move over and what you don’t. 

You may decide you want to download historical data and start completely fresh with a new A/B testing platform. Or, you may want to move over as many existing elements as you can.

Now is a great time to audit your existing experimentation program and see what is and isn’t worth bringing to your new platform.

Here are three things you may want to consider migrating and why.

• Business metrics: you should migrate over the main KPIs from your website or app such as conversion, revenue, form completion, or demo requests.
• Recurring segments: any recurring segments that you have in Google Optimize should be migrated over to your new tool.
• Deviated tests: only deviated tests should be migrated over to your new platform. As a best practice, we recommend releasing into production most of the modifications done in deviated tests.

Kameleoon is currently offering Google Optimize and Google Optimize 360 users complimentary set-up service for all migrating users. Our top-rated customer support teams will set up your goal tracking, segments, and integrations based on your program needs.

Learn more about moving to Kameleoon after the Google Optimize sunset.

5. Integrate your existing tools

Having an integrated tech stack will improve your operational efficiency and make for a more seamless data experience.

Before launching your first test, check to make sure that your tools are integrated with your existing tech stack, and the integrations are working as expected.

Some notable integrations that you may want to set up include:

• Analytics: GA4, Amplitude, Contentsquare, Hotjar
• CDP: Segment, Tealium
• CMS: Shopify Plus
• Automation: Zapier

6. Check for data accuracy

Experts across the board agree that the most important thing when it comes to migrating off of Google Optimize or Google Optimize 360 is ensuring data accuracy.

Once you have migrated your data to your new A/B testing platform, you should check that the data you’re obtaining is accurate.

Run an A/A test

An A/A test is where you test two identical versions of an element. The result should not be statistically significant, as in, no difference should be detected between the two versions. This indicates that your tool is sending equal amounts of traffic to both elements.

Running an A/A test is one of the best ways to ensure your solution is working as it should. If you get an unusual result, then you’ll know your tool needs to be reconfigured. 

Compare your new data to your old data

One of the advantages to migrating off of Google Optimize early is you can compare the data you’re getting to your old data and see if the numbers make sense.

Use an in-app SRM checker

If your new solution has any built in measures for ensuring data accuracy, you should leverage these to ensure you’re getting accurate data. 

An example would be using an in-app Sample Ratio Mismatch (SRM) checker to ensure   variants are receiving the appropriate amount of traffic based on the parameters you’ve set.

There is perhaps nothing more valuable than getting data you can trust. One of the best ways to ensure accurate data is by prioritizing and selecting a solution that values data accuracy.

Once you’ve migrated your data, set up your integrations, and checked for data accuracy, you’re ready to launch your first test with your new solution!

Kameleoon: The best Google Optimize 360 alternative

Kameleoon is an excellent alternative to Google Optimize 360. It is a leading A/B testing platform and the only optimization solution with web, full stack, and feature experimentation capabilities in a single unified platform.

Google Optimize 360 users will appreciate Kameleoon’s vast range of features, intuitive UX, and focus on data privacy and security.

As an enterprise-level solution, Kameleoon is ready to support a wide range of advanced experimentation needs including feature experimentation and hybrid experimentation.

Below are five reasons why Google Optimize 360 users are choosing Kameleoon as their preferred solution:

1. The Kameleoon web experimentation snippet is 2-3x faster than leading optimization solutions, and flicker-free.
2. Kameleoon has a native, two-way integration with GA4 so you can drag-and-drop segments stored in GA4 for your tests built using Kameleoon.
3. Brands moving to Kameleoon from Google will receive complimentary setup service, as well as a waived license fee for the first month.
4. With advanced server-side testing, feature flagging and feature experimentation capabilities, Kameleoon scales with you as your experimentation program grows.
5. Kameleoon graphic editors work on any SPA site, with powerful goal tracking and the most-advanced data accuracy features.

Kameleoon is the highest-rated experimentation platform on G2 and Trust Radius, and a leading alternative to Google Optimize 360.

Learn more about how Kameleoon can support Google Optimize 360 users successfully migrate to a new A/B testing tool.

Ready to get started with Kameleoon? Request a demo today.