AI researcher
AI user research that answers why, with the sessions to prove it
AI user research means a model reads your real user behavior and answers product questions for you. In UserExplorer you ask in plain English, for example why paid search traffic converts worse this week, and the AI researcher replies with findings, numbers and the evidence sessions behind each one.
- Ask questions in plain English, get findings with evidence
- Every claim links to the replays that support it
- AI user interviews ask visitors short follow-up questions
- Works on the same segments as funnels and heatmaps
- 1 Phone verification fails on mobile signup 31% of mobile signups 42 replays
- 2 Yearly toggle below the fold on /pricing 58% of paid search visitors 27 replays
- 3 Coupon field takes focus before Pay 18% of checkouts 19 replays
- 4 Export used in 24 h predicts retention 2.4x better week 4 33 replays
Sample data
The problem it solves
Nobody has time to watch four thousand replays
Most teams record far more behavior than they ever look at. A product manager opens a dozen replays, spots one odd pattern and has no way to know whether it explains two visits or two thousand. Classic user research fixes that with interviews and usability tests, which take weeks to plan and rarely match the traffic you have right now.
The AI researcher closes that gap. It reads the recorded sessions in a segment, the events your product sends, the answers from surveys and interviews, and the steps of your conversion funnels. Then it groups what it sees into findings, sizes each one and points to the visits where it happens.
You stay the researcher in charge. The model does the reading and the counting, you decide what is worth fixing. Each finding shows how many sessions it rests on, so a pattern seen in nine visits never looks as certain as one seen in nine hundred.
Ask anything
Questions you would ask a senior analyst, answered in minutes
Type a question the way you would write it in a team chat. Why does Google Ads traffic convert worse this week. What do trial users do before they upgrade. Where do mobile visitors give up on checkout. The researcher picks the relevant sessions, reads them and writes a short report.
Example findings on our sample data show the format. 31% of visitors abandon signup at step 3 because phone verification fails on mobile, with the twelve replays where the code never arrives. Users who activate Saved Views within 24 hours retain 2.4 times better, with the cohort split behind the number. These are example findings on demo data, your report reflects your own traffic.
Every answer can be pinned to a dashboard, shared with a link or turned into a segment for session replay and heatmaps, so the next step is one click away.
AI researcher
Read 1,284 sessions, sample dataYou asked
Why do users drop off at signup?
31% abandon signup at step 3 because phone verification fails on mobile.
- SMS code not delivered on 2 of 3 carriers in the US
- Users tap Send code 4 times on average, then leave
- Desktop completes the same step at 88%
Evidence sessions
What the researcher does
One research assistant for behavior, feedback and outcomes
It works across every data source in your project, not only replays.
Finds the patterns
Groups similar struggles across thousands of visits and ranks them by how many users and how much revenue they touch.
Shows the evidence
Each finding links to the exact replays and timestamps, so anyone can check the claim in under a minute.
Interviews your users
AI user interviews ask visitors who just dropped off or just converted two or three follow-up questions in a short chat.
Explains drop-off
Pick a funnel step and ask why people leave. The answer compares those who left with those who continued.
Summarizes customers
Writes a short summary on each user profile, from first visit to last ticket.
Tracks change
Run the same question every week and see which findings grow, shrink or disappear after a release.
AI user interviews
Hear the reason from the user in their own words
Behavior shows what happened. A short interview at the right moment tells you why.
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Step 1
Choose the trigger
Show the interview after an event, for example a cancelled checkout, a failed search or a finished onboarding.
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Step 2
Set the goal
Describe what you want to learn. The AI writes a friendly opening question and adapts follow-ups to each answer.
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Step 3
Keep it short
Interviews end after a few questions and never ask for personal data. Users can close the chat at any time.
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Step 4
Read the synthesis
Answers are grouped into themes with quotes and linked to each respondent's session replay.
Compared
How AI research differs from the methods you know
| Aspect | AI researcher in UserExplorer | Moderated interviews | Watching replays by hand |
|---|---|---|---|
| Time to first answer | Minutes | Weeks of recruiting and calls | Hours, for a small sample |
| Sample size | Thousands of real sessions | Usually five to fifteen people | As many as you can watch |
| Evidence | Linked replays and counts | Notes and recordings | Your own memory |
| Real context | Live traffic, real devices | Lab or video call setting | Live traffic |
| Hears the why | Yes, through AI user interviews | Yes, in depth | No |
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Time to first answer
- AI researcher in UserExplorer
- Minutes
- Moderated interviews
- Weeks of recruiting and calls
- Watching replays by hand
- Hours, for a small sample
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Sample size
- AI researcher in UserExplorer
- Thousands of real sessions
- Moderated interviews
- Usually five to fifteen people
- Watching replays by hand
- As many as you can watch
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Evidence
- AI researcher in UserExplorer
- Linked replays and counts
- Moderated interviews
- Notes and recordings
- Watching replays by hand
- Your own memory
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Real context
- AI researcher in UserExplorer
- Live traffic, real devices
- Moderated interviews
- Lab or video call setting
- Watching replays by hand
- Live traffic
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Hears the why
- AI researcher in UserExplorer
- Yes, through AI user interviews
- Moderated interviews
- Yes, in depth
- Watching replays by hand
- No
Moderated research still has a place for deep discovery. The AI researcher covers the daily questions in between.
Plans and privacy
Available on every paid plan with clear monthly limits
Each plan includes a fixed number of AI analyses per month: 50 on Startup, 400 on Growth, 1,200 on Scale and 3,000 on Enterprise. Asking the researcher open questions and running AI user interviews start on Growth. The one time demo after signup shows replays and heatmaps without AI.
The researcher only reads data you already collect, with masked inputs staying masked. Text you mark as private never reaches the model, and recording can wait for the consent signal from your own banner. Details are on privacy and security.
FAQ
Questions teams ask before they start
What is AI user research?
AI user research uses a model to read real user behavior and feedback, find recurring problems and answer product questions. In UserExplorer every finding comes with the number of sessions behind it and links to the replays that show it.
Is UserExplorer a user research platform?
Yes, for research on live products. It combines behavior data, surveys, NPS and AI user interviews in one place. It does not recruit panel participants for prototype tests, it studies the users you already have.
How accurate are the AI findings?
Each finding states its sample size and links to evidence sessions, so you can verify it quickly. Treat small samples as leads to check, and large ones as patterns worth acting on.
What are AI user interviews?
A short chat that appears after an event you choose. The AI asks an opening question, follows up on the answer and stops after a few turns. Answers are grouped into themes and linked to each session.
Does the AI see personal data?
Masked inputs and elements you mark as private are removed in the browser before recording, so the model never receives them. Interviews do not ask for personal details.
Which plan do I need?
AI session summaries are on every paid plan. Asking open questions, AI user interviews, cohorts and churn risk start on Growth at $499 a month, or $249 a month billed yearly. See pricing.
What happens when I reach the AI limit?
New analyses pause until the next billing period or until you move to a larger plan. Existing reports stay available and you are never charged extra.
Ask your first research question this week
Install the snippet, let real sessions come in and ask the AI researcher what is holding your users back.