Looppanel is a faster, smarter Dovetail alternative. Request a Free demo here.
80% of traditional repositories fail to meet their team's needs. Teams are unsatisfied with them, the repository has been abandoned, and they're still paying way too much money for software they simply don't use.
We frequently talk to teams that have this struggle. They often look to switch away from a traditional repository like Dovetail because:
- It's too expensive
- No one's using it on their team
- It requires a lot of manual tagging and maintenance
- They want useful AI features (and they're not finding them)
In this article, we'll go through:
We'll talk about each Dovetail competitors' strengths and weaknesses so you have the insider track on which one will work best for you and your team.
If you have no prior experience with repositories, check out our definitive guide first! This will give you the foundational information on what a repository is, and how it's supposed to work.
There are tons of research analysis & repository tools cropping up. To decide which one is right for you, you need to evaluate them (whether Dovetail, or Dovetail competitors) on these 4 criteria:
1. Transcription Quality
Your team shouldn't be spending hours correcting transcripts because your participant doesn't have an American accent—it's a waste of time, and not why you bought a repository. You want a solution that's at least 95% accurate with transcripts, even if your participant has an accent from half-way across the world.
2. Speed of Analysis
Remember how 80% of repositories fail? One of the biggest reasons this happens is if it takes longer to analyze your data in your repository compared to the quick and dirty excel or miro workflows everyone is used to.
If your repository (let's say it's Dovetail) slows your team down, they will simply not switch their workflow to use it. Instead, they'll keep using Miro / excel / Figjam, and the repository will become a dumping ground where research goes to die.
To make your repository successful, you need to look for AI-supported analysis features like these ones that will make your team more efficient. This will incentivize them to use the repository for analysis, organically building it out by default.
For an overview of the specific AI capabilities that'll actually help your team move faster, read this overview.
3. Maintenance and Upkeep Required
Related to point number 2, if your team has to do a lot of extra knowledge management work just to make the repository useful, your repository will fail. No one has extra time. No one wants to do extra work. The repository has to make their lives easier in order to be adopted, not harder.
4. Collaboration Capabilities
What good is a repository if only 2 people on the team have access to it? The whole idea of a repository is to centralize user insights so that your team can make good decisions quickly. If the team can't access these insights, or contribute their own learnings—well why are we doing all this anyway?
Now that we've decided what we'll evaluate our repositories on, let's actually do the evaluation.
Read More: Tips on repositories from researchers at Google & Razorpay
Before we jump into the alternatives, here’s a quick crash course on Dovetail.
Dovetail is a traditional user research analysis & repository tool. You can upload your recordings to Dovetail, have them transcribed and then tag your data for analysis.
What are the features of Dovetail?
Dovetail's core features include:
- Transcription in 28 languages
- Tagging taxonomies for a single project and across projects
- Ability to analyze data across a trello board, canvas, table and other views
- Filter / search across projects based on tags you've created
What is Dovetail good for?
Dovetail has a robust tagging-taxonomy system that is the backbone of the tool. This is a pro and a con (more on the con later).
The pro is if your team is comfortable with tagging taxonomies, has the time to manually analyze data and maintain a tagging taxonomy, Dovetail can be a great fit. The tagging taxonomies are robustly built out and the product is built with a coding-first approach.
What is Dovetail bad at?
On the cons of tagging taxonomies: they're hard to use and maintain, especially if:
- your team faces time pressure to deliver insights quickly
- you're not very familiar with taxonomies
- you don't have a full-time librarian for knowledge management
Using taxonomies for insight management is a very manual process. In fact, the effort of setting up and maintaining them is one of the key reasons 80% of repositories fail.
With Dovetail, the tagging taxonomy requires a lot of work to define upfront—teams often spend weeks or months deciding which tags will encompass their projects comprehensively.
Search is also powered by this taxonomy, which is a double edged sword. In order to power search via your taxonomy, you need to anticipate:
- What people will want to search for in the future (nigh impossible)
- Cover all the possible features, use cases, segments they may want to search with a tag
- Tag everything perfectly across all your data in the repository
This is all aside from the fact that every team member using Dovetail for analysis should adhere to this taxonomy across every project over time. This mammoth level of collaboration may only be possible in the army.
AI features would be a great help here, but Dovetail is notorious for doing a bad job integrating them well into the researcher’s workflow. Features are often tacked on top and not very useful to teams. If you want to stay on the cutting edge of what’s possible for research today, Dovetail is unlikely to be a good fit.
Lastly, with their change in pricing structure, a lot of large teams have had to pivot away from Dovetail. Their enterprise pricing plans are $$$ and often the new pricing information comes with no warning.
When to look for Dovetail alternatives?
It's time to look for Dovetail alternatives if you're struggling with any of these issues:
- You find Dovetail complex and confusing to navigate. It's got a significant learning curve for your team.
- You do not have a dedicated research librarian who can create, maintain and ensure adoption of your tagging taxonomy.
- Your team moves quickly and is interested in efficiency for analysis.
- You don't have budget for Dovetail's latest $$$ enterprise plans.
- You want to make use of the latest (AI) tech and what it can do to simplify the research workflow.
Okay, so if we don't want to use Dovetail, what alternatives do we have? Let's go through a list of our top 4 Dovetail competitors with a detailed review of each.
Looppanel is an AI-powered research analysis & repository tool. It's built like a research assistant—to automate the manual, tedious parts of qualitative research you don't have time for.
Looppanel's key capabilities include:
- 95% accurate transcripts (across accents and regions)
- 10x faster analysis via auto-tagging, automatic notes, and more
- Smart search for insights and quotes across your data
- Shareable video clips and insights (you can embed these into Jira tickets, Notion, etc.)
- Analysis across calls by question or tag
Looppanel vs Dovetail
What is the difference between Looppanel and Dovetail?
Let's take a look...
We tested a clip from Forrest Gump in both Dovetail and Looppanel to see how accurately both systems transcribed.
Dovetail had 4 errors, to Looppanel's 1. Also you'll notice that Dovetail's transcription broke the same speaker's text into lots of small chunks that were harder to process and read.
TLDR: Looppanel offers better transcription than Dovetail. You can learn more about the transcription capabilities here.
2. Faster AI-powered analysis
Just about anyone (and everyone) can and does claim to have AI features these days. What sets AI features and tools apart is how useful they are to your workflow. Dovetail for example has built a number of AI features, but if you speak to any of their customers— the reviews are poor.
Looppanel has invested heavily in making their AI features actually useful for analysis and search. Every AI feature carefully maps to the user research workflow and is built with the core principle of trust in mind. If you can't trust AI's output, you won't use it. Trust is built by ensuring:
1. traceability (you can always find the source for any AI output)
2. human in the loop (you can edit and improve anything the AI does)
3. quality (the output has to meet a very high quality bar)
The proof is in the pudding: customers rave about the hundreds of hours Looppanel has saved them in analysis. If you'd like to see them in action, you can request a free demo here.
3. Collaboration
Dovetail charges per user, which can be prohibitive to easy collaboration. If you want to invite PMs, Designers, the broader team to collaborate and add to your repository or analysis, you can hit budget constraints very quickly.
Looppanel on the other hand offers unlimited collaborators and viewers for Pro plan onwards—the more users, the merrier. However, the product does have limits in place on the number of files you can import in a year.
Which pricing model works for you will depend on the way your team is set up. To get a custom quote from Looppanel, book a call here.
Condens is basically ‘Dovetail lite’. It's a very similar product in terms of workflows, but it has fewer features and a slightly lighter price tag.
Condens' core features include:
- Automated transcription
- Ability to tag transcripts with themes or topics
- Ability to analyze data across calls (including a digital whiteboard)
- Filter or search by tag across projects
Condens vs Dovetail
1. Transcription quality
We compared Dovetail vs Condens on transcript quality (with a clip from Forrest Gump 😌). Both transcripts captured the text correctly, but both struggled with identifying the number of speakers. Condens struggled a bit more than Dovetail—picking up only 1 speaker, when there were 4.
TLDR: Dovetail > Codens for transcription quality
2. Analysis efficiency + AI features
Honestly, neither of these tools shine in this department. Similar to Dovetail in this respect, Condens hasn't invested heavily in cutting-edge AI features but both tools offer a robust manual approach for qualitative data analysis.
Read a more detailed analysis of Condens and it's alternatives here.
3. Pricing
Condens offers a far friendly pricing plan than Dovetail. We hear through the grapevine that Dovetail's enterprise plans start at $21,000+. Condens on the other hand offers an option at $14,400 / year with 10 researchers included.
EnjoyHQ has been around for a while and was acquired by UserZoom (which has now been bought by UserTesting.com).
We'll be honest, we're yet to find a team that likes EnjoyHQ and their price hikes post acquisition haven't helped.
EnjoyHQ's core features include:
- Transcription
- Integrations with tons of tools, so you can import data across sources
- Tagging and taxonomy capabilities (it's a bit complex though!)
EnjoyHQ vs Dovetail
What is the difference between EnjoyHQ and Dovetail? Here's the tea.
1. Transcription
EnjoyHQ's transcription is pretty decent. It distinguishes between speakers well enough, although it stumbled a bit with deciphering Forrest Gump's accent.
2. Ease of Use & Usability
EnjoyHQ is a challenging tool to learn and to use. Most teams don't end up using it for analysis at all, but just as a dumping ground for reports and data points. It's set up in a complicated way and the usability is poor.
3. Tagging efficiency
Although manual tagging is painful, EnjoyHQ has the ability to set tagging rules (E.g., all text mentioning "integration" should be tagged accordingly). This helps with large volumes of tagging, like when you're dealing with support tickets. It's not perfect, but if you're dealing with large numbers of tickets, it could be useful to have a rule saying, "tag everything that mentioned 'Slack'".
4. Integrations
EnjoyHQ is most useful if you want to pull data in from 10s of sources. They have native integrations with everything from Jira, to UserTesting, to survey tools. Consider this Dovetail alternative if you're looking to gather data from many sources. If you are focused on analyzing just interviews, usability tests and surveys, stick to Dovetail, Looppanel, or Condens.
5. Pricing
As soon as your team scales to 2+ people, EnjoyHQ moves you to a custom pricing plan, which means we don't know what they'll charge you but it's probably a lot. Now that Dovetail's pricing plan is $21,600, Enjoy may offer some comparable options depending on your needs.
Aurelius is an old-school Dovetail alternative (and it shows). It has confusing, clunky UX and its analysis view seems lacking.
Aurelius' key features include:
- Transcription and tagging of data
- Keyword or tag-based searcha cross the repository
Aurelius vs Dovetail
1. Transcription
Aurelius' transcription quality and speaker identification was actually better than Dovetail's, but the way the transcript was visually shown left much to be desired. Each line of the transcript shows up as a separate card. An hour long call would generate 100s of these blocks that are visually painful to look at and process.
2. Ease of Use & Usability
While Dovetail gets complaints for being confusing and hard to navigate, it's nothing near the usability issues that Aurelius has. The product is clunky and painful to navigate and use.
3. Tagging
One feature Aurelius offers that stands out: bulk tagging. You can select mulitple notes at once and tag them, saving many clicks. But bulk tagging doesn't make up for the painful UI of the transcript.
4. Pricing
Aurelius doesn't come cheap, especially if you want to try their monthly plan. If you're a small team, Dovetail's starter plan is probably a better fit. If you're a large team with enterprise requirements, you'll need to contact Aurelius to get a custom quote. Aurelius is also a bit vague about how collaborators are priced on the product.
Would you like to recommend any other analysis and repository tools for review? Reach out to us at support@looppanel.com!
Ready to start testing Dovetail alternatives? You can request a Free, personalized walk through of Looppanel here.
Want unfiltered reviews? We've taken a look at Dovetail reviews across popular platforms like G2, and Reddit—because after all, you shouldn’t have to take our word for it.
We fed the user reviews into Looppanel for a quick summary of reviews of Dovetail and Dovetail competitors. Here’s a summary of what customers think Dovetail.
G2 Dovetail Review: 4.4/5 Stars
TLDR: While Dovetail seems to be widely used, opinions on it vary greatly. The choice of platform seems to depend heavily on specific needs and use cases.
Dovetail received mixed reviews, with users appreciating its organization and tagging capabilities but criticizing its learning curve and some UX issues.
Positive Dovetail reviews:
Efficient organization of research data
- Easy tagging and sorting
- Good for collaboration
- Powerful search tool
Negative Dovetail reviews:
- Expensive for small projects
- Steep learning curve
- Complex user interface
- Limited text formatting options
- Basic people management features
Notable quotes:
"I like Dovetail because it organizes research data very well. It's easy to tag and sort information, making analysis quick and efficient." —Dovetail user on G2
“Their AI functions are just not there yet. Switching between chatGPT and DT gets old fast. I wish they were built in (they are, but they don't work that well).” —Dovetail user on G2
FAQs
What is the Dovetail app used for?
Teams use the Dovetail app to transcribe, manually tag, and analyze their interviews. They also use it for centralizing all their customer research in one place.
Does Dovetail use AI?
Yes, Dovetail uses AI for transcription and some analysis / call summarization features. But based on user feedback, Dovetail's AI features aren't very useful.
“Their AI functions are just not there yet. Switching between chatGPT and DT gets old fast. I wish they were build in (they are, but they don't work that well).” - G2
For a more robust AI-powered solution for research analysis & repository, check out Looppanel.
What is similar to dovetail?
Tools similar to Dovetail include Looppanel, EnjoyHQ, Condens, and Aurelius. These tools all have research analysis and repository features like transcription, tagging, and global search.
What is Dovetail research repository?
Dovetail Research Repository is a tool that helps UX researchers store and analyze their data. It lets you save interviews, surveys, and other research materials in one place. You can tag important parts, search through your data, and share findings with your team.
Is Dovetail free?
Dovetail isn't free, but it does offer a free trial for one project. After that, it costs $39 per user each month.
Is Dovetail legit?
Yes, it's a real, widely-used tool in the UX world. Many big companies use it for their research. But like any tool, it has both fans and critics. Some love its organization features, while others find it hard to use. It's smart to try it yourself and see if it fits your needs.
What does the company Dovetail do?
Dovetail is a User research analysis & repository product. The product is built to make it easier and faster for teams to make research-backed decisions. Alternatives to Dovetail include Looppanel, Condens, EnjoyHQ, and Aurelius.
For a robust AI-powered solution for research analysis & repository, check out Looppanel.
.svg)
