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.
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UserTesting
Score 8.1 out of 10
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UserTesting helps UX researchers, designers, product teams, and marketers gather actionable insights through research, testing, and feedback. With a network of real people ready to share their perspectives, UserTesting enables organizations to make customer-first decisions at scale.
Optimizely is more user-friendly and cost-effective, ideal for experimentation-focused teams, while Adobe Target excels in advanced personalization and seamless integration within the Adobe ecosystem, making it better suited for large enterprises.
We chose Optimizely specifically for its split testing and advanced audience segmentation capabilities. It makes it way easier to see which option objectively performs better.
I think it can serve the whole spectrum of experiences from people who are just getting used to web experimentation. It's really easy to pick up and use. If you're more experienced then it works well because it just gets out of the way and lets you really focus on the experimentation side of things. So yeah, strongly recommend. I think it is well suited both to small businesses and large enterprises as well. I think it's got a really low barrier to entry. It's very easy to integrate on your website and get results quickly. Likewise, if you are a big business, it's incrementally adoptable, so you can start out with one component of optimizing and you can build there and start to build in things like data CMS to augment experimentation as well. So it's got a really strong a pathway to grow your MarTech platform if you're a small company or a big company.
Well suited to its original purpose- usability testing and interviews. This can be performed at pace, given the large audience (although our brands are very well known so this should not be a barrier) and there is a decent level of task customisation when conducting unmoderated testing. Its less appropriate for survey where you are looking to capture genuine intent/behaviour, even with screeners the data skews more positively than onsite survey, makes me question the quality of survey respondents.
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.
Quality of participant pool - many are career testers, and many are untruthful. Since sessions are auto-scheduled if the screener is past, you often don't know until they've completed the test. Allow double screening or be more stringent in removing users from the platform.
Unfinished products - focus on making one product the best it can be before moving on to a new one. Unmoderated testing is still missing features (randomization of 3 or more prototypes, etc.)
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
I'm very happy with my experience of the product and the level of service and learning resources they provide. If the service becomes more expensive than it currently is then we might not be able to justify additional cost - but this is theoretical. I would recommend UserTesting and would ideally renew our contract.
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.
It can be difficult to organize our tests and go back and find information. I think the AI tools are helping and will help with this, but for now it is time consuming to sort through all of the tests and information and then synthesize it and share it with others. It just takes a lot of time.
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.
I have contacted UserTesting's customer service online, by email, or by phone a few times, and each time, I have encountered the same professionalism and expertise. Even in person during a work event, they were there, and it was the same experience.
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.
From a technical perspective, the implementation was extremely smooth. Most of the change management / implementation hurdles were clearing use of the tool through our various security, legal, and information privacy teams. Once these concerns were addressed (UserTesting.com was very helpful in providing all the needed documentation), the implementation process was very simple and we were able to get going right away.
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 need to confidently make changes
The quality of the participants: they usually have good feedback and act like "professional" users. Which is good when we want a few insights in a short amount of time. Also, the interface is good. I miss having more features, like a good transcription tool like we have in Condens
We can use it flexibly across lines of business and have it in use across two departments. We have different use cases and slightly different outcomes, but can unify our results based on impact to the bottom line. Finally, we can generate value from anywhere in the org for any stakeholders as needed.
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.
