User Intuition Description
User Intuition is an innovative customer intelligence platform that facilitates AI-driven market research interviews through chat, voice, or video formats. This platform transforms conventional text surveys into engaging conversations aimed at understanding the reasons behind customer behaviors such as buying, leaving, or remaining loyal.
By leveraging advanced AI interview technology, it poses insightful follow-up questions based on participants' replies, utilizing laddering techniques to uncover the emotional drivers and underlying motivations that shape customer choices. User Intuition boasts an impressive 98% satisfaction rate among participants, thanks to its conversational approach that fosters open and honest feedback.
Businesses utilize this platform for a variety of purposes, including monitoring brand health, extracting valuable shopper insights, gaining competitive intelligence, and testing concepts with actual consumers or carefully selected panel members. Additionally, the platform's ability to engage customers in meaningful dialogues sets it apart as a leader in the market research field.
Pricing
Access to 4M+ vetted respondents with industry-leading fraud detection—or bring your own customers
AI-moderated interviews via chat, audio, or video
Automated analysis and reporting for each study
Company Details
Product Details
User Intuition Features and Options
User Intuition User Reviews
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Three vendors down to one login Date: Aug 19 2026
Summary: Collapsed our stack without giving up interview depth, which was the fear. Recruiting, conversations, and the archive live in one place now. Brand questions get answered from what we already know instead of another fielding cycle.
Positive: A brand manager Slack'd me at four about our new resealable pouch and I answered before standup the next morning with quotes from a study we'd run six weeks earlier. Searched the hub and that was it. Used to mean a panel export, a Qualtrics export, and digging through Dovetail.
We've pretty much collapsed those three into User Intuition now. Broad U.S. grocery study asked for forty and filled in a few hours. I was skeptical an AI would dig past "I like it." It did. Project pricing also meant I didn't need an annual platform fight just to pilot.Negative: Three brand teams share the workspace and I'd like tighter role locks before someone junior can launch a huge study unsupervised.
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Great tool Date: Aug 11 2026
Summary: The best use I've found is prioritization. Request counts can be misleading, and AEs tend to repeat the loudest version of a problem. This helped us find the smaller issue underneath before we burned a sprint. I trust it for kill decisions as much as build decisions.
Positive: We started using user intuition a few months ago when we realized customers didn't need the automation engine we had in mind. A few interviews in, we realized they needed to see where an approval was stuck. Three people said that without being led there. Most had started with some version of "sounds useful," but the follow-up questions got into when they would use it, what they did today, and who else had to sign off.
We spoke with eight admins, six end users, and three buyers in a week. I started with a half-page brief on Tuesday and had conversations by Friday. We cut the MVP down to a status view and saved a ton of time.Negative: Zapier and HubSpot cover us. Zapier and HubSpot already cover most of our automation and CRM needs, so there is limited room for additional tools.
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Product — concept vs urgency Edited: Aug 10 2026
Summary: Clarity and urgency are not the same finding. This was the first tool that separated them clearly enough for me to pause a concept the design team was already attached to. Support was hands-on during our first run, which helped.
Positive: We used User Intuition to test our messaging and a few concepts after a few of our prospects said they understood the idea, but talked about using it someday. We ended up testing four screens and a concept image for a shared-lists idea that design was falling in love with. Fourteen video interviews later, we paused the build and saved a sprint on something people didn't connect with.
We loved that the report separated the assumptions that held up from the ones that looked shaky, with quotes under each. And Chloe from support walked us through setup and helped with the readout slides.Negative: Two of fourteen participants never turned on their video, which made it difficult to gauge their real-time engagement and feedback during the session.
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Good for UX Research Date: Jul 29 2026
Summary: I still use quick unmoderated tests for task metrics. User Intuition is better for understanding the reasons behind those metrics. Using both made the redesign much easier to defend.
Positive: We learned that about a third of our users don't think setup is their job. It was kind of like a throwaway comment: one person said they'd just ask ops to do that part. The moderator followed up on who "ops" meant, why they would hand it off, and what might make them do it themselves.
We had already seen people pause on step three of the invite-teammate flow. The heatmap showed exactly where, but not why. Twelve interviews on that flow gave us the missing context around expectations and confidence.Negative: No facial-expression scoring on the video. We watch the clips ourselves. Fine for us
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Churn analysis rootcause Edited: Aug 13 2026
Summary: User Intuition helped me understand what customers went through before they left. The direct quotes we’re able to get from there usually move the conversation forward faster than another dashboard screenshot.
Positive: We thought most of our churn happened because of price and in fact we’d heard it 90% of the time. The follow-up questions from User Intuition uncovered that most of those customers never connected a datasource so didn’t see much value from our product. As evidence, I even downloaded and shared five quotes in Slack with the team to show them the findings.
We’re now actively solving cancels and downgrades by focusing on the integration steps instead of discounting.Negative: None
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