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
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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
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 Date: Jul 29 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: I like it.
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
The real reasons customers leave, in their own words Date: Jul 27 2026
Summary: It gave us a real handle on why people leave, which honestly used to be all guesswork. We looked into a group of cancellations everyone assumed were about price, and it turned out they were folks who never quite got set up in their first week. Once we knew that, we fixed the right thing first, and it's been one of the more useful things we've done all year.
Positive: The part I love is I can actually hear from customers who just left, without chasing anyone down for a call. Fifteen people who'd cancelled that week, all talked to in a day or two. And the follow-ups go past "too expensive" into what really made them go. Best of all, I can click any finding straight through to the exact quote, so when I take something to the exec team I'm not guessing, I've got the receipts.
Negative: None. Great product.
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Worked well to what we required
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