Google offers the Optimize A/B testing tool for testing website content and versions.
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Optimizely Web Experimentation
Score 8.6 out of 10
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Whether launching a first test or scaling a sophisticated experimentation program, Optimizely Web Experimentation aims to deliver the insights needed to craft high-performing digital experiences that drive engagement, increase conversions, and accelerate growth.
Google Optimize is a great entry-level test platform and is an ideal solution for my clients that want something simple to start with and see value. Although not as robust as the paid platforms, it still does the job well and delivers believable data ties to one of the most …
Optimizely by far wins over Google Optimize. The UI is so much better, easier to use and share. The reporting and overall experimentation flexibility beats Google Optimize hands down.
Google Optimize was great, but our organization already had contracts with Optimizely Web Experimentation for their other tools. unbounce wasn't really an option either mainly because it was only a landing page testing tool and had to use their platform to host the tests. We …
We pivoted to Optimizely Web Experimentation because Google Optimize was sunsetted as a product by Google. Optimizely Web Experimentation has more features available, such as the statistical significance estimator, ability to run more than 5 experiments at a time, and ability …
Google Optimize was used previously and sunset in October. We were looking for a new system that had similar capabilities that was organized and would allow code manipulation as well as ease of use without touching code so more members of our team could seamlessly implement …
Google Optimize was much less flexible for our program needs and requires Google Analytics for analysis and metrics tracking. Optimizely Web Experimentation lets you build any number of metrics which can be much more complex than standard GA goals. Optimizely Web …
It's slightly more complicated to use, but in my experience, it has more capabilities. Also, Google Optimize was depreciated, so this is definitely the next best platform.
The creation and customization of events in our AB testing is an important feature that Google Optimize does not. Because of how we prioritize our Client journey and leading to more form submissions, it's critical that we can identify pivotal moments that influence our User's …
The ability to do A/B testing in Optimizely along with the associated statistical modelling and audience segmentation means it is a much better solution than using something like Google Analytics were a lot more effort is required to identify and isolate the specific data you …
None of them have a best in class stats engine and live within an ecosystem of marketing technology products the way that Optimizely does, so the scalability of using any one of those tools is limited as compared to using Optimizely Web Experimentation.
Optimizely has everything in one place. It is also more thorough, letting you do any kind of experimentation. It also has a much better interface that allows you to manipulate the creative/code much more easily.
Optimizely is my favorite due to its ease of use and exceptional testing capabilities. It is not the cheapest tool, but the other tools that could be compared are not cheap—you get what you pay for. Some of the smaller tools are making gains, though!
Analytics are vastly superior, platform UI is by far the easiest to use, and capabilities are best in class. If your organization has any budget for a web experimentation tool, it should be using Optimizely Web Experimentation.
Whilst Optimizely is more expensive (for us at least) we found it was far technically superior and easier to use. We have not run into the technical constraints that we have with other tools. In addition when we went to market to evaluate different suppliers optimizely won …
It is pretty good in comparison. The biggest difference is the metrics dashboard for experiments which gives us granular data related to the experiment being run. I think honestly there is a lot right now my company is probably not utilizing when it comes to optimizely but I do …
We have evaluated Optimize every year against Optimizely. I am a google fan, but their product is not up to the level of Optimizely. They do not offer multi-page tests, and a lot of our changes sometimes span the whole funnel. For that reason alone, it's currently unusable.
It is a little too limited for a full stack experimentation programme. Many times we required development support or tech advise but we were simply unable to get this due to it being google. This was a big problem for us. However it is quite good if you were looking to get started in experimentation and didn’t have the budgets for a wider tool
I have found Optimizely has been really useful to run some quick experiments to validate the approach to changes to the website, exploring multiple options simultaneously to save time and effort prior to making more permanent changes with our development team. The biggest challenge has been ensure ideas from the wider business have all the necessary criteria to make them a worthwhile experiment. Encouraging stakeholders to create a proper hypothesis for each experiment has helped focus the minds on the outcomes we're expecting. This also makes the analysis easier once we've concluded a test
Easy to follow set up procedures. Once I walk a client through the process, it's effortless for them to emulate on subsequent tests.
Lots of geo and user attribute customization features to be able to drill down into specific targeted audiences — all based on the power of Google's immense data system.
Google Optimize is the logical choice for many people to start with since most are already familiar with and using GA.
The Platform contains drag-and-drop editor options for creating variations, which ease the A/B tests process, as it does not require any coding or development resources.
Establishing it is so simple that even a non-technical person can do it perfectly.
It provides real-time results and analytics with robust dashboard access through which you can quickly analyze how different variations perform. With this, your team can easily make data-driven decisions Fastly.
I rated this question because at this stage, Optimizely does most everything we need so I don't foresee a need to migrate to a new tool. We have the infrastructure already in place and it is a sizeable lift to pivot to another tool with no guarantee that it will work as good or even better than Optimizely
Optimizely Web Experimentation's visual editor is handy for non-technical or quick iterative testing. When it comes to content changes it's as easy as going into wordpress, clicking around, and then seeing your changes live--what you see is what you get. The preview and approval process for sharing built experiments is also handy for sharing experiments across teams for QA purposes or otherwise.
I would rate Optimizely Web Experimentation's availability as a 10 out of 10. The software is reliable and does not experience any application errors or unplanned outages. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
I would rate Optimizely Web Experimentation's performance as a 9 out of 10. Pages load quickly, reports are complete in a reasonable time frame, and the software does not slow down any other software or systems that it integrates with. Additionally, the customer service and technical support teams are always available to help with any issues or questions.
They always are quick to respond, and are so friendly and helpful. They always answer the phone right away. And [they are] always willing to not only help you with your problem, but if you need ideas they have suggestions as well.
The tool itself is not very difficult to use so training was not very useful in my opinion. It did not also account for success events more complex than a click (which my company being ecommerce is looking to examine more than a mere click).
In retrospect: - I think I should have stressed more demo's / workshopping with the Optimizely team at the start. I felt too confident during demo stages, and when came time to actually start, I was a bit lost. (The answer is likely I should have had them on-hand for our first install.. they offered but I thought I was OK.) - Really getting an understanding / asking them prior to install of how to make it really work for checkout pages / one that uses dynamic content or user interaction to determine what the UI does. Could have saved some time by addressing this at the beginning, as some things we needed to create on our site for Optimizely to "use" as a trigger for the variation test. - Having a number of planned/hoped-for tests already in-hand before working with Optimizely team. Sharing those thoughts with them would likely have started conversations on additional things we needed to do to make them work (rather than figuring that out during the actual builds). Since I had development time available, I could have added more things to the baseline installation since my developers were already "looking under the hood" of the site.
Google Optimize being part of the Google stack makes it great in reporting and analysis. Wish Google would add more features like dynamic tests, multi funnel tests, conversion calculator based on the total number of traffic of the page being tested instead of using the websites total traffic. Should integrate form analysis, heatmap, and page analytics.
None of them have a best in class stats engine and live within an ecosystem of marketing technology products the way that Optimizely does, so the scalability of using any one of those tools is limited as compared to using Optimizely Web Experimentation.
It's incredibly flexible and adapts well to organizations of all sizes, whether you’re running a single site or managing multiple departments and platforms. The ability to deploy experiments seamlessly across different environments is a huge plus, especially for growing businesses. While it’s highly scalable, the last point would depend on the right team leveraging its full potential.
We're able to share definitive annualized revenue projections with our team, showing what would happen if we put a test into Production
Showing the results of a test on a new page or feature prior to full implementation on a site saves developer time (if a test proves the new element doesn't deliver a significant improvement.
Making a change via the WYSIWYG interface allows us to see multiple changes without developer intervention.
