Dovetail vs. Optimizely Web Experimentation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dovetail
Score 8.3 out of 10
Mid-Size Companies (51-1,000 employees)
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
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.N/A
Pricing
DovetailOptimizely Web Experimentation
Editions & Modules
Free
$0
Professional
$15
per month
Enterprise
Contact Sales
per year
No answers on this topic
Offerings
Pricing Offerings
DovetailOptimizely Web Experimentation
Free Trial
YesYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalOptional
Additional DetailsDiscount available for annual billing on the Professional plan.
More Pricing Information
Community Pulse
DovetailOptimizely Web Experimentation
Considered Both Products
Dovetail
Chose Dovetail
Better usability but less powerful in terms of integration. EnjoyHQ felt better for quantitave data when i used it for the last time. But my knowledge is not up to date.
Chose Dovetail
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 …
Chose Dovetail
Marvin's approach to AI has always been a core part of their platform, and so the integration of AI features (and the focus on building an AI product that works effectively for the kind of research we are doing) has always been at the forefront of their thinking and design. …
Chose Dovetail
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 …
Chose Dovetail
Dovetail meets our needs the best with global codebooks, data retention rules, etc. Other platforms offered functionality we had in other tools or limited our ability to control data management and access controls. We would love even more in Dovetail, but like the direction …
Chose Dovetail
Haven't used EnjoyHQ in the last three years, so cannot compare the new capabilities like AI. We switched to Dovetail because it was easier to use at the time.
Chose Dovetail
I tried this product and must say I think the AI features are way better here and more accurate
Chose Dovetail
We chose Dovetail because it was more powerful and simple to use when we evaluated these tools.
Chose Dovetail
I work at Notion and we could also save our docs within Notion
Chose Dovetail
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 , …
Chose Dovetail
Dovetail has some niche capabilities for market research that these alternative competitors do not like embedded transcription, insight clipping, sharing across a research team, etc. The others in my list have more features and are designed for knowledge management. For …
Optimizely Web Experimentation
Chose Optimizely Web Experimentation
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 …
Chose Optimizely Web Experimentation
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 …
Chose Optimizely Web Experimentation
Google Optimize and Hotjar
Chose Optimizely Web Experimentation
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 …
Chose Optimizely Web Experimentation
This is a platform that was already implemented when I started with my current company.
Chose Optimizely Web Experimentation
The feature set and ecosystem for Optimizely seemed much more robust and scalable.
Chose Optimizely Web Experimentation
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.
Chose 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 …
Chose Optimizely Web Experimentation
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.
Chose Optimizely Web Experimentation
We analyzed a few competitors and optimizely had the most robust feature set and scalability
Chose Optimizely Web Experimentation
I feel Optimizely Web Experimentation stacked up well against Split
Chose Optimizely Web Experimentation
We haven't used other Optimizely products apart from Web Experimentation.
Chose Optimizely Web Experimentation
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.
Chose Optimizely Web Experimentation
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.
Chose Optimizely Web Experimentation
We use both, it just depends on the use case. I personally prefer feature experimentation but I see why both are useful.
Chose Optimizely Web Experimentation
Optimizely Web Experimentation has more robust product for experimentation specialists than VWO
Chose Optimizely Web Experimentation
Handshake by Shopify (discontinued)
Chose Optimizely Web Experimentation
Better tools but more expensive
Chose Optimizely Web Experimentation
It exists unlike google optimize
Chose Optimizely Web Experimentation
Optimizely Web Experimentation appeared to be much more user friendly and easier to self-manage than AB Tasty
Chose Optimizely Web Experimentation
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.
Chose Optimizely Web Experimentation
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 …
Features
DovetailOptimizely Web Experimentation
Testing and Experimentation
Comparison of Testing and Experimentation features of Product A and Product B
Dovetail
-
Ratings
Optimizely Web Experimentation
8.0
Ratings
2% below category average
a/b experiment testing00 Ratings9.00 Ratings
Split URL testing00 Ratings8.50 Ratings
Multivariate testing00 Ratings8.40 Ratings
Multi-page/funnel testing00 Ratings7.90 Ratings
Cross-browser testing00 Ratings8.10 Ratings
Mobile app testing00 Ratings8.00 Ratings
Test significance00 Ratings8.40 Ratings
Visual / WYSIWYG editor00 Ratings8.10 Ratings
Advanced code editor00 Ratings8.00 Ratings
Page surveys00 Ratings6.20 Ratings
Visitor recordings00 Ratings8.40 Ratings
Preview mode00 Ratings7.60 Ratings
Test duration calculator00 Ratings7.90 Ratings
Experiment scheduler00 Ratings8.20 Ratings
Experiment workflow and approval00 Ratings7.80 Ratings
Dynamic experiment activation00 Ratings7.50 Ratings
Client-side tests00 Ratings7.80 Ratings
Server-side tests00 Ratings7.20 Ratings
Mutually exclusive tests00 Ratings8.20 Ratings
Audience Segmentation & Targeting
Comparison of Audience Segmentation & Targeting features of Product A and Product B
Dovetail
-
Ratings
Optimizely Web Experimentation
8.2
Ratings
4% below category average
Standard visitor segmentation00 Ratings8.40 Ratings
Behavioral visitor segmentation00 Ratings7.60 Ratings
Traffic allocation control00 Ratings9.10 Ratings
Website personalization00 Ratings7.80 Ratings
Results and Analysis
Comparison of Results and Analysis features of Product A and Product B
Dovetail
-
Ratings
Optimizely Web Experimentation
8.3
Ratings
1% below category average
Heatmap tool00 Ratings9.30 Ratings
Click analytics00 Ratings8.80 Ratings
Scroll maps00 Ratings8.50 Ratings
Form fill analysis00 Ratings8.00 Ratings
Conversion tracking00 Ratings8.70 Ratings
Goal tracking00 Ratings8.20 Ratings
Test reporting00 Ratings7.90 Ratings
Results segmentation00 Ratings7.70 Ratings
CSV export00 Ratings7.90 Ratings
Experiments results dashboard00 Ratings8.00 Ratings
Best Alternatives
DovetailOptimizely Web Experimentation
Small Businesses
Smartlook
Smartlook
Score 8.2 out of 10
Convert Experiences
Convert Experiences
Score 9.9 out of 10
Medium-sized Companies
Optimal
Optimal
Score 9.0 out of 10
Dynamic Yield
Dynamic Yield
Score 8.3 out of 10
Enterprises
Optimal
Optimal
Score 9.0 out of 10
Dynamic Yield
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Score 8.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DovetailOptimizely Web Experimentation
Likelihood to Recommend
7.5
(0 ratings)
8.7
(0 ratings)
Likelihood to Renew
-
(0 ratings)
9.5
(0 ratings)
Usability
6.0
(0 ratings)
10.0
(0 ratings)
Availability
-
(0 ratings)
10.0
(0 ratings)
Performance
-
(0 ratings)
7.3
(0 ratings)
Support Rating
-
(0 ratings)
10.0
(0 ratings)
Online Training
-
(0 ratings)
3.0
(0 ratings)
Implementation Rating
-
(0 ratings)
8.0
(0 ratings)
Configurability
-
(0 ratings)
6.0
(0 ratings)
Product Scalability
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
DovetailOptimizely Web Experimentation
Likelihood to Recommend
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.
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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.
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Pros
  • 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.
Read full review
  • 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.
Read full review
Cons
  • Search can be challenging for a company with multiple products and many user types.
  • Charts generated from survey data could have settings to allow us to change how they are filtered / displayed.
  • Having a table of contents in insights / linkable headers would help direct people the right spot of an insight.
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  • 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
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Likelihood to Renew
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!
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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.
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Usability
One of Dovetail’s key strengths is that it’s very easy to get started with — even for people without a research background. Uploading a transcript, tagging highlights, and generating a quick summary is intuitive and low-effort, which helped drive organic adoption at Dext.
However, mastering the more advanced features — like taxonomy management, insight reporting, or strategic tagging structures — does require more time and guidance. The learning curve becomes steeper as you try to scale insight operations or enforce consistency across teams.
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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.
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Reliability and Availability
I’ve never had any access issues with Dovetail, so I don’t see any problems in that area.
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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.
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Performance
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.
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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.
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Support Rating
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.
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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.
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Online Training
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.
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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).
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Implementation Rating
No answers on this topic
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.
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Alternatives Considered
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 tools I've used in the past due to the amount of time it takes and would choose Dovetail over Google Workspace, UserTesting, and Basecamp hands down
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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
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Scalability
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.
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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.
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Return on Investment
  • 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.
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  • we saved money by not implementing certain copy/design
  • we learned that customers from different states react different to a variation
  • we are slowly learning where conversion happens and where to fix the frictions
  • Testing shorter vs longer journeys increased funnel conversion in some states - we avoided implementing this nationwide
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ScreenShots

Dovetail Screenshots

Screenshot of the Contacts interface, used to find, schedule, and incentivize research participants.Screenshot of a visualization of customer feedback, used to identify patterns before they become problems. Using LLM and ML techniques, Channels continuously classifies and tracks themes in large data sets like support tickets, app reviews, and feedback.Screenshot of an example of a conversational insight, available in Slack. Here, users can quickly ask questions to access automatic podcast-style updates for all related data across Dovetail in Slack and Microsoft Teams.Screenshot of the navigation and project interface, designed to makes it easy for everyone to get started and find what they need in Dovetail.

Optimizely Web Experimentation Screenshots

Screenshot of AI-Powered Experimentation with Opal:

- Instant Test Ideas: Generates high-quality A/B test ideas based on any goals and audience insights.
- Smarter Experimentation: The AI can suggest impactful variations, reducing guesswork and increasing test velocity.
- More Than Just Ideas: From hypothesis generation to analyzing results, Opal helps optimize every stage of the experimentation process.Screenshot of the Web Experimentation Visual Editor :

- Tweak experiments using the visual editor or dive into custom code when needed.
- Modify elements, update styling, or add dynamic behaviors.
- Ensure perfect variations while keeping control over every detail of the experiment.Screenshot of AI Content Suggestions:

- Generates copy variations to supercharge experiments.
- The AI suggests high-impact messaging for tests when hovering over a field.
- AI-powered content suggestions help skip the brainstorming process.Screenshot of Advanced Audience Targeting:

- Delivers personalized experiences by targeting users based on behaviors, attributes, and real-time conditions.
- Defines precise audience segments using first-party data, geolocation, and device type.
- Can test and optimize for different audience groups to maximize impact and engagement.Screenshot of Custom Templates in the Visual Editor:

- Offers pre-built templates for common test setups.
- Standardized variations and maintains brand integrity with reusable templates.
- Templates can be customized visually or tweak them with code for full flexibility.Screenshot of the Web Experimentation Results Page:

- Data visualizations help interpret experiment performance.
- Displays which variations are winning with built-in statistical significance calculations.
- Results can be filtered by audience segments, events, and conversions to uncover key trends.