Just announced: Google Optimize, A/B testing is sunsetting
Talk about a Monkey Wrench! As if Google Analytics users weren’t busy enough planning their migration to GA4, now Google additionally announced the sunset of Google Optimize.
Experiments will still continue to run until September 30, 2023, but. no further. The news appears to cover all users of Google Optimize, regardless of whether it’s with
Google Universal Analytics free
Google 360 Universal Analytics
Google Analytics 4 (GA4)
So they really mean it.
Now What?
Don’t just look for a replacement, e.g. via the popular experimentation platforms from Optimizely, Kibo, Kameleoon, or many others they compete with.
It’s a great opportunity to strategize for giving your testing program an extra boost.
Turn the crisis into an opportunity! Combine your new A/B testing platform with a secret sauce ingredient that will help you create successful tests much more often.
Boost your A/B testing program by integrating it with Digital Experience Analytics
A/B testing is the stuff of legends. A great A/B test will turn the experimentation team into an instant hero. But too many A/B tests finish flat. After all that effort and weeks of running the test, zero benefit.
So how can the experimentation team be a hero more often? The secret sauce is not a secret actually.
Change the A/B test game during and after testing
Most A/B test platforms integrate with most digital experience analytics providers so that you can understand why a particular test variation won or failed.
During and after testing
See heatmaps of variation A vs. B
See anecdotal session replays
Understand why a test won, and what were the biggest success factors.
Combine this information to create even better tests.
But the real game changer is: Inform A/B test strategy by really understanding what makes customers click
This is where you’ll really make a difference for your program. Use your digital experience analytics to discover what you don’t already know about your customers.
Discover user journeys and compare successful vs. unsuccessful sessions side by side
Understand in-page behavior and what. makes customers click, vs. leaves them cold
What you’ll get is a much better informed perspective on which next A/B tests are most likely to move the needle for your desired conversion goals.
What to look for in A/B testing integration with Digital Experience Analytics
And it’s here that all digital experience products are not equal. Look for the following to boost your A/B testing program while you are deciding on your Google Optimize replacement
Ability to compare customer journeys side-by-side so you can discover customer intent
Ability to compare in-page behaviors side-by-side so you can discover what makes a successful interaction vs. failure
Ability to quantify the business impact of differing in-page behaviors with a click so that you can prioritize which tests to invest in.
Ability to import customer segments from Google/Adobe Analytics so you can further refine the groups of customers you are visualizing — based on segments that you’ve already created in Google and Adobe.
Necessity is the mother of invention
This is your opportunity to really boost your A/B testing program. Don’t just stay the course. Right the ship, be a hero more often!
How are others boosting A/B testing success with the help of Experience Analytics?
That’s one of many things you can learn in my brand new book, Customer Experience Analytics.
50 real-life case studies
30 cheat sheets
With a foreword by the one and only Tom Davenport, author of Competing on Analytics and other best selling books.
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