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.
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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.
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zeemo
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Dovetail
Optimizely Web Experimentation
zeemo
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Professional
$15
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Enterprise
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Dovetail
Optimizely Web Experimentation
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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.
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 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.
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.
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!
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
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.
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.
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.
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.
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.
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 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.
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.
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.
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
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.
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.
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.
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.
