Dovetail, headquartered in Sydney, aims to enable the world to create better products and services through deep customer understanding. Dovetail states they empower 45,000+ people, from agencies to universities to Fortune 100 companies, to make sense of their customer research in one collaborative research platform.
$0
per month
Maze
Score 8.0 out of 10
N/A
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
Pricing
Dovetail
Maze
Editions & Modules
Free
$0
Professional
$15
per month
Enterprise
Contact Sales
per year
Professional
$75
per month 3+ seats
Organization
custom pricing
Offerings
Pricing Offerings
Dovetail
Maze
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Discount available for annual billing on the Professional plan.
Dovetail outperforms in qualitative research analysis by offering advanced tagging transcription and centralized insights. I think notion is good for large or complex documentation but Dovetail is nice for qualitative documentation. Maze is better for usabilty testing , …
Dovetail is 10X better. So much easier and truly meant for having one centralized workspace. Everything from the highlights and tags and videos and column customization when editing makes it easy to call them the winner in this field. I wouldn't want to go back to my other …
Dovetail is the most stakeholder-friendly research tool we've used.
Its visual insights, highlight reels, and intuitive interface make it easy for non-researchers to understand and act on customer feedback. Stakeholders can engage directly without needing deep training, making …
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 …
See 1st question answer for my use case, I went into depth there for the specific use cases we have. For less appropriate (touched on this earlier) the final report is not great in dovetail. The formatting options are not great and does not look professional because of the lack of customization and layouts. For my customer we wouldn't be able to present that data as it's constructed. So we have to copy and paste all the quotes and insights to a word doc. That's ok but then it means if we want to use Dovetail as a repository of data we have to then re-import a pdf of the report into the project page.
Maze User Testing is great if you're interested in doing user research from the comfort of your own desk. You can easily setup usability tests, surveys, card sorting and tree tests among other things to get a better understanding of how customers use your product. The only limitation at the moment with Maze that I can identify is only being able to do unmoderated tests, so if you'd like to be able to ask follow up questions in the moment, Maze is not the tool for you.
The tagging, linking, and repository features make it simple to maintain a living library of knowledge, ensuring past work is never lost.
Dovetail enables our researchers and non-research partners to engage more directly with findings, fostering a stronger culture of evidence-based decision-making.
Dovetail makes it simple to track engagement metrics with research insights proving overall ROI.
We should have a trust indicator for our insights, as it is difficult to quickly determine when they are trustworthy or not.
Chatbot analysis within different data, I mostly use it with a small sample and replicate the process instead of using the chatbot for more global analysis.
Insight creation, the format is not always really engaging, and you can't really create a presentation from it. It does not align with some stakeholder expectations and requires us to redo the work.
Because we are really happy with the tool and it’s capabilities at the moment. The price increase is the main issue we can have but the features are getting better and better. It really saves a lot of time for our team and allow us to collaborate more efficiently with certain stakeholders that often did not réalise how much research we conduct. Now they can just have a look to it by themself!
Very organized and user-friendly; however, the editing capabilities for the analysis report/insight doc could use some work. There was a recent update also causing it to be harder to find the in-project search bar and where to switch from the highlight list and highlight board view, which made the experience more challenging, especially since I was sharing my screen. Not only did it catch me off guard that it changed, but stakeholders and I were trying (on-call) to figure out how to access it and couldn't. After the call, I did more digging and finally found it, but that was after a bit of time. Outside of this and the editing for insight reports, I feel like the usability is actually very well thought out and effective.
Maze is easy to use most of the times. It is easy to integrate with Figma, It is easy to find testers worldwide with required filters. Maze gives recorded videos which are helpful in debugging and understanding the problem with flows. A/B testing is easy to add and test. Overall Maze is very easy to use
Regarding performance, I would say it’s satisfactory. Adding data and transcriptions is really fast and efficient, and can be done in the background, so I’m never hindered by these aspects. However, all the new AI-generated features are still somewhat slow to run. It’s nothing major, but it should improve in the future.
My customer success manager is very responsive and has always been able to answer my questions and resolve issues quickly. The collaboration is smooth, so I have no complaints in that regard.
The training went very well, and we co-built it to really address our needs. I also think it was beneficial to have feedback coming from someone other than myself (since I manage the tool), as it helped reinforce the points I wanted to highlight. The team’s feedback on the training was very positive.
Dovetail is the most stakeholder-friendly research tool we've used. Its visual insights, highlight reels, and intuitive interface make it easy for non-researchers to understand and act on customer feedback. Stakeholders can engage directly without needing deep training, making it ideal for cross-functional teams. Compared to other tools, Dovetail offers the best balance of depth for researchers and clarity for decision-makers.
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 free option but Lookback doesn't have it, but Lookback has a cheaper option at $19/month than Maze.
Management is quite straightforward; it’s easy to change access if certain stakeholders need to use it. The repository features are accessible to all teams, making it a good entry point into the tool. The more people use it, the more powerful the tool becomes, so it seems truly scalable to me. The limits are more financial, in terms of accessing additional features.
Researchers and designers now spend less time digging through scattered notes or redoing similar studies. Centralizing everything in Dovetail has significantly reduced the time needed to prepare synthesis reports, align stakeholders, or onboard new teammates into past research.
With Dovetail, user insights are no longer abstract or anecdotal—they're traceable, searchable, and backed by real quotes. Product teams feel more confident making roadmap decisions based on what users actually need, not assumptions.
Dovetail has encouraged more non-designers to engage with user feedback directly. This democratization of insights helps align everyone around real user problems, which ultimately leads to better product-market fit and faster iteration loops.
