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Dovetail

Score8.7 out of 10

103 Reviews and Ratings

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What is Dovetail?

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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Categories & Use Cases

Media

Screenshot of an automate workflow with AI: Agents track every customer signal and act on what’s important before they turn into problems.
Screenshot of an example of an automated transcript with structured note-taking that anchors insights in the voice of the customer. This uses AI-powered Chat and Search to offer instant answers grounded in data—whether it is in Dovetail, Slack, or Teams.
Screenshot of the AI Dashboards that help spot risks before they escalate, act on new opportunities.
Screenshot of the dashboard to connect Dovetail to an existing tech stack, including Slack, Linear, and various meeting recording tools.
Screenshot of where to automatically clustering customer issues into prioritized themes and trends. Useful for surfacing actionable product opportunities from high-volume ticket data.
Screenshot of real-time dashboards that aggregate sentiment, NPS, and app reviews into a unified view of the customer experience.

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Screenshot of an automate workflow with AI: Agents track every customer signal and act on what’s important before they turn into problems.

Who Buys & Uses Dovetail

Dovetail Reviews

What users are saying about Dovetail.
View all Dovetail reviews

Pros

  • Centralized research repository for diverse data
  • Robust tagging and highlighting for detailed analysis
  • Accurate and fast automated transcription

Cons

  • Inconsistent accuracy and contextual understanding of AI features (beyond transcription)
  • Limited support for quantitative research and survey analysis
  • Suboptimal onboarding and training for new users

Useful AI interface should reverse the IA overhaul.

Incentivized
Luke oconnorView profile
Senior UX Researcher in Research & Development at Conde Nast (1001-5000 employees)

Use Cases and Deployment Scope

The single most useful improvement has been the AI chat interface, which reliably references the raw data. While the overhaul has led to confusing navigation and feels less intuitive than before, the ability to extract high-level insights at a glance proves very useful for a small team such as ours that runs at a high pace. I will note, though, there are contextual issues where the chat interface will misconstrue feedback, but this represents general AI limitations for analysis. Lastly, for visual concepts, the addition of Alloy has proved useful for bringing insights to life and framing them in a more visually engaging way for stakeholders to consume output in a different medium.

Pros

  • AI chat interface.
  • Alloys 'prototyping' feature.
  • Referencing the raw data.

Cons

  • As mentioned up top, the contextual errors that occur in AI analysis.
  • Your IA and discovery routes were better before; this overhaul was unnecessarily complex and frustrating to navigate.
  • I find assigning names clunky. Batch uploading data, or even agentic API plugins for drive or user testing, would make this more seamless.

Return on Investment

  • Time saved on producing high level insights.
  • Facilitated democratizing UXR insights.
  • Helps other teams with decision making.

Usability

Other Software Used

UserTesting, Typeform, Hotjar

Essential tool for anyone who needs an organised research repository

Incentivized
Talissa Walsh
UX Researcher in Research & Development at WP Engine (501-1000 employees)

Use Cases and Deployment Scope

I use Dovetail as a research repository tool. I upload sessions, create session summaries and use AI assistance and link to my presentation decks and recordings from here. I use the AI chat to ask specific questions about all my projects, a specific project and I use it for individual sessions too.

Pros

  • create session summaries
  • AI chat to answer questions I have about a session or project
  • identify themes form research

Cons

  • sometimes the AI hallucinates although it has got better, you just need to get it to back up where it found the information

Return on Investment

  • speeds up research synthesis
  • engages stakeholders as it is easy to use
  • organised research repository

Usability

Alternatives Considered

Great Question and Miro

Other Software Used

Miro, Great Question

Flexible user research repository with seamless intelligence tools

Incentivized
Verified User
Manager in Product Management (51-200 employees)

Use Cases and Deployment Scope

We use it as a...
- Central user research repository for product roadmap planning
- User trend and insight generation for planning
- A source of truth for validating ideas, concepts, and decisions on a day to day basis.

We don't use...
- It as a contact database (too much to manage)

Pros

  • Chat to docs is a powerful feature for validating stakeholder ideas and providing real user insights, next to a summary and doc I can send along in as little as 5 min.
  • The flexibility of the database works for multiple types of org cultures (e.g,. one that is more eng. centric likes things organized by feature, whereas more user centric orgs can easily tag and adjust for user themes and needs)
  • Dynamic highlighting and auto suggest has improves and saves a lot of time manually tagging user quotes and interviews.

Cons

  • Automated connections. As a team of one, I need the ability to connect to multiple other sources, import them, quickly tags these, and derive insights. The most frustrating thing is all the features are there, I just need a user friendly way to do this, without involving engineering.
  • Love the charts, but I can create a filtered view as a report. E.g., I track user complaints about features and requests for new ones, but I can link to a consistent view.
  • This is vague, but for the cost, it feels like it should come with something else. I am paying the same amount for Great Question and they have user testing tools and most of what you have.

Return on Investment

  • Improved decision making. Shows my team quickly what is worth investing engineering or design time in.
  • Improve prioritization since I can cross-reference OKRs with user feedback for annual planning.
  • Improved time savings. I hunt and peck so much less often for that "one quote I remembered from 12 months ago"

Usability

Alternatives Considered

Maze, Great Question, User Interviews and Userlytics

Other Software Used

Great Question, Maze, Optimal, Qualtrics XM for Strategy and Research

Love Dovetail

Incentivized
Verified User
Contributor in Product Management (51-200 employees)

Use Cases and Deployment Scope

Dovetail is a research repository of all our customer interviews and user testing. It centralizes our research, research plans, and insights. It allows us to analyze our interviews, gather comments into a theme and expose trends behind our gut feeling or bias. I love the ability to put together quick clips or collections for stakeholders

Pros

  • Transcriptions
  • Global tagging system
  • Ai automation

Cons

  • Better ai, especially tagging
  • More integrations
  • Stop making drastic changes that messes up all our files

Return on Investment

  • Improved decision making
  • Risk reduction

Usability

Alternatives Considered

productboard

Other Software Used

Hotjar, Pendo.io

Remove silos and speed up qualitative analysis.

Incentivized
Marlana A. Coignet, MSView profile
Staff User Researcher in Product Management at Shopmonkey (51-200 employees)

Use Cases and Deployment Scope

As a solo researcher at our startup, we use Dovetail to store all of our customer research. Before Dovetail, all research was stored on my Google Drive or in a shared drive, which made it a very manual process to look up past research. Implementing Dovetail allowed us to store all user research in a central location that anyone in the company could access. The search allows cross-functional teams to easily see what data we have from our customers on any subject. It has removed the silo that used to be a barrier to customer insights. Our biggest use case of Dovetail is the repository and search. The AI is getting a lot better, but still has some ways to go.

Pros

  • Dovetails search is amazing! It allows our teams to jump into Dovetail, ask questions of ALL the data we have there, and provide amazing summaries. This is really great for getting a high-level overview of a particular subject matter. It also provides links to transcripts that verify the summary's source.
  • Speaking of summaries, the AI's summary of a question is amazing. Again, it highlights parts of the transcription that validate the summary. This is an awesome tool for high-level summaries of any research question.
  • I love the tagging for research analysis. The tags are project-specific, so not across your entire data set, but still incredibly helpful. I can review calls and transcripts, highlight and tag any text relevant to the research questions I'm trying to answer. And look through all data for a specific tag, and much more easily spot trends or patterns. This is my bread and butter as a researcher with Dovetail.
  • Lastly, I love the collaborative aspect. Anyone in our organization can log in to Dovetail and review data. I will often share clips directly from Dovetail with stakeholders, who can easily view them. Overall, the collaborative effort has been a huge help in getting more team members into Dovetail.

Cons

  • I think one of Dovetail's biggest challenges is discoverability. They are constantly shipping new features and adding more functionality, but I find the help articles and videos do not go deep enough or even provide enough help to get started. I'm sure I'm not utilizing the platform to its full potential, and I think better training or onboarding across all tiers would help us get more out of Dovetail. Its hard to even know what you're not using or what you don't know.
  • On the Enterprise plan, you get a dedicated account manager who can handle your onboarding. That's the only plan with an account manager. And it's a little unfortunate. When you write into the help center, they direct you to a help article, which again does not go deep enough. I wish there were more opportunities for training and enablement for lower tiers.
  • I think Dovetail is amazing for qualitative research, but I find it very frustrating and lacking for quantitative research. I don't think it makes survey analysis very easy. I would be looking for something closer to a Sheets or Excel for quant analysis, but Dovetail is pretty crude in what it allows you to do with survey results.

Return on Investment

  • The first biggest ROI is the time savings. As a research team of one, there is only so much that I can do with my bandwidth. Dovetail allows me to close out research projects much faster than doing it manually. I can upload video interviews, highlight and tag parts of the transcript that relate to research questions, and easily summarize. Highlighting allows me to get the perfect soundbite for a research readout, and overall, Dovetail has helped me move faster and with greater accuracy.
  • Another huge ROI for us is the improved productivity. Product managers, designers, and other colleagues can easily go into Dovetail and ask the chat/search for answers to questions they are trying to figure out. All of this without having to reach out to me, the solo researcher. This saves me a ton of time in Slack messages and meetings.
  • The value of the repository itself is huge. Since all of our research is stored in Dovetail, we can easily search previous research to ensure we are not duplicating efforts or even missing key customer information that may have come up in a separate study. This gives our research a longer shelf life, making it even more valuable.
  • .

Usability

Alternatives Considered

Marvin

Other Software Used

Slack, Anthropic Claude

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