With the current transition to GA4, it is inevitable that platforms associated with Google Analytics would change. Marketers have already seen a name change with Data Studio, while BigQuery is picking up a larger role in analytics workflow.
The latest platform news involves Google Optimize. Google announced the discontinuation of its test suites Optimize and Optimize 360.
Any accounts still active after Sept. 30, 2023, will be eliminated. This will also mean customers who are extending or renewing their Google Analytics 360 (Universal Analytics) contracts during 2023 can still renew their Optimize 360 contracts, but the service dates will end on or before the Sept. 30 date.
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The Point: Why This Article Matters
- Coming to an end. Google will end its Optimize and Optimize 360 test suites on Sept. 30, 2023. These suites allowed marketers to integrate A/B testing features with Google Analytics 360 and measure the impact of design changes on conversions.
- Starting a trend? The company plans to announce new ways to bring experimentation, likely incorporating elements of AI and machine learning. Other analytics solutions with A/B testing features, like Adobe Analytics, may also follow this trend.
The History of Google Optimize
Google introduced Optimize as a complimentary A/B testing platform for Google Analytics 360 — I wrote about it when it was introduced in 2017 (You can read it here). Optimize was designed for integrating the testing features with a tag manager and analytics solution. Doing so eased A/B testing capability.
Marketers would run A/B tests, which would compare a control element — current state of an element on your website page, app page or landing page — and a test element — the altered design of the element.
The test was meant to measure if a response to a design change was significant enough to improve conversion results. The integration allows marketers to identify how metrics changed with respect to the test elements.
In practice, Optimize users would create an account and then link it to their Google Analytics 360 property and their tag manager property. Google later extended Optimize integration features to work with GA4, then with Google Ads.
The integration allowed marketers to further extend their test environment to key media associated with a website, namely landing pages and digital ads. The result is an integrated environment that allows for test result consistency between website page, digital ad message and landing page.
For example, marketers can conduct a single experiment for multiple keywords, even if the words appear across different campaigns and ad groups. So, in a test of the same landing page for a hotel, marketers can examine conversion rates for customers that search for “spa” in the “vacation” ad group and for customers that search for “event services” in the “trade show” ad group.
A/B and multivariate testing was developed to treat website elements as a proxy to how people were responding to digital campaigns. But as Jim Tincher, CEO of Heart of the Customer, mentioned in the CX Decoded podcast, managers are not interested in debates about where a button goes.
Many of the elements drive or are mixed into more complex customer behaviors. Over the years analytics providers have been adjusting their A/B testing solutions to better account for those behaviors.
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What The Future of A/B Testing Will Hold
Google stated it “will be sharing new ways to bring experimentation … in the coming weeks.” This is not a surprise, as growth of A/B testing paralleled with the expanded usage of digital ads. Tests are necessary for determining how a page should be best optimized for better conversion rates.
In an earlier article I noted an eMarketer prediction for increased B2B ad spending, implying that B2B firms would also increasingly turn to A/B and multivariate testing. That trend should continue despite the current anxiety over digital marketing spending this year.
Part of the reason, I suspect, is that any new platform will incorporate some element of machine learning or AI to help form better questions and hypotheses to investigate. The overwhelming public interest in ChatGPT, combined with Google's announcement of its own large language model (LLM)-based AI Bard, has ushered in a marketplace trend where solution providers are seeking integration opportunities for AI into the user experience.
Final Thoughts on the Sunsetting of Optimize
I am speculating a bit, but from my experience A/B and multivariate testing are a great fit for AI integration because the questions they trigger regarding test results can be so widely varied and require alternatives.
An AI enhancement like ChatGPT would help reduce the choices into a more manageable collection. I'm certain Google is planning something already after seeing Microsoft move quickly to introduce AI into its office and machine learning products. Marketers should also see how other analytics solutions that have A/B testing, like Adobe Analytics, respond as well.
Google seems to be planning a replacement, so we’ll all have to “stay tuned” for the news. In the meantime, marketers can download their historical test data until the sunset date. The information to do so is available at the Optimize Help Center.
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