Maze is a rapid user testing platform from Maze.design in Paris, designed to give users actionable user insights, in a matter of hours. The vendor states that with it, users can test remotely, autonomously, and collaboratively.
$75
per month 3+ seats
Optimizely Web Experimentation
Score 8.7 out of 10
N/A
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.
We left sprig to use maze because sprig had unreliable Figma questions and integrations. We chose maze as it was partnered with Dovetail and Askable, that's how we heard about them. We're not particularly loyal or wedded to maze.
We ran a proof of concept exercise between Maze User Testing and Optimal Workshop. We found both products to be as good as each other in the elements of the products that both offered. Optimal Workshop did offer a lot more than what was required for the specific project for …
A lookback is an alternative option if you think Maze User Testing is quite expensive for you, but look back has a different approach to Maze User Testing. Lookback focuses on qualitative usability testing instead of quantitative UserTesting. And also, Maze User Testing has a …
Maze User Testing is brilliant to test with a large volume of people and if you’re not after particular qualitative insights, like UserTesting would offer. The card sorting feature is basic and not as mature as Optimal Workshop would offer but it does the job and can be used in …
When looking for tools that could help us understand our customers better, we needed something that would be easy to use, had the functionality and flexibility of running multiple types of tests and exercises, and allowed our team to be able to do these tests quickly. Only Maze …
Figma helps to design and prototype out the concept but it does not allow to facilitate feedback gathering on a specific UI or even UX decision. That's where Maze comes into the picture with it's vaious features that helps to get the right insight to build a better product in a …
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 …
I do not have any issues with AB Tasty. They are great. We went with Optimizely because they have several other products that will work together with our business model. Optimizely has grown and it now offers many other products that work with experimentation like CMS, CMP, ODP …
Optimizely is highly intuitive, allowing marketers or non-technical folks to run experiments without complicated coding. It also allows for various types of experimentation, including A/B tests, multivariate tests, and personalization. This capability will enable teams to run …
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 a lot more, well, site stacked, it's way better than that. Adobe Target. I think the UI is easier to use on Optimizely. The one thing that I would say comparatively is our analytics talking to each other. Obviously Adobe, we use Adobe Analytics and Adobe Target, so they …
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.
Optimizely Web Experimentation was more robust and able to handle the broad array of sites we run than VWO. It has been a great platform to easily add additional sites onto, but still providing a universal overview of all of them, making management a simple task.
we used Optimizely Web Experimentation then AB Tasty but came back to Optimizley because of its robust stat sig and features as well as all of the products we will be able to work in synchronization.
I think that Optimizely Web Experimentation is much easier to implement and use, but the entire Adobe Experience Cloud provides a ton of value if you have multiple products.
Honestly, Optimizely Web Experimentation has its pros and cons just like any other tool. We use Optimizely because we have resources here in the country that can help us when e have issues. The support team being local helps a lot so we don't have long wait times to get things …
Suited for: - I think that this software is a must-have for any experience or product designer that needs validation from any audience - Designers that rapidly prototype with Figma - Designers looking to establish an inexpensive way to deliver on user testing Less appropriate for: - If you are looking for a survey replacement this is probably not for you even though it does that quite well, simply due to the cost. Google Forms would be a more fiscal choice. - Marketing visual designers who are adept at visual builder tools (WebFlow, Divi, Elementor, etc) with A/B testing ability would probably find other products more valuable.
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.
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.
The results view is dense and difficult to package easily for leadership, and when filtering by segment it's hard to read comparative outcomes without clearing or swapping filters
The organization of experiments and statuses is a cluttered list and the search is limited in use - would love to see that improve with time
There are so many other MarTech products out there, would love to see more dedicated integrations so we don't have to invest in something like Zapier or Tray to build hacky automations
Because it's an incredible and essential tool for my line of work as a conversion optimization specialist. Really couldn't do my job nearly as effectively without it. It's paid for itself many times over and I feel like I'm only beginning to unlock the tools potential.
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).
The implementation through the tag management system took a bit of trial and error at first, mostly due to the asynchronous nature of the TMS. We had to manipulate the implementation to assure that the Optimizely code was written to the page at the right time to allow the experiment content load in the browser without showing any of the original content first. We also needed to make some adjustments to the TMS code to get the integration with Site Catalyst timed appropriately.
When looking for tools that could help us understand our customers better, we needed something that would be easy to use, had the functionality and flexibility of running multiple types of tests and exercises, and allowed our team to be able to do these tests quickly. Only Maze could really tick all the above boxes.
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
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.