What workflow would this feature improve for you?
A
Prioritize Feature Requests
Interviewer agent · 2.5K uses
Interviewer Agent
Uncover User Friction
Nobody reads your exit survey. Star ratings and text boxes capture surface-level sentiment. This template replaces them with AI conversations that dig into what users actually think, what’s frustrating them, and what would make them stay — then routes insights to the teams that need them.
Retention signals
Specific frustrations
Competitive context
Used 2,800+ times
How this AI template works
This template triggers an AI-powered conversation when you want to collect user feedback — after a feature launch, at a usage milestone, or on a regular cadence. The AI asks what’s working, what’s not, and what users wish was different. It adapts follow-up questions based on their sentiment, diving deeper into frustrations and probing on positive signals. Every response is analyzed for themes, quotes, and actionable insights, then routed to product, CS, or engineering.
Getting started
- 1
Choose your feedback trigger — post-feature launch, usage milestone, or scheduled cadence
- 2
Customize the AI conversation to explore satisfaction, frustrations, and feature gaps
- 3
Deploy via in-app embed, email, or link — reaches users where they already are
- 4
Review AI-generated analysis with themes, sentiment trends, and actionable quotes
Template Details
- Agent Type
- Interviewer
- Category
- Product & research
- Industry
- SaaS / Tech
- Business outcome
- Build the right product
- Job to be done
- Interview customers & users
- Journey stage
- Feedback & evaluation
- Replaces
- 1:1 interviews
- Times Used
- 2,800+
Forms collect fields. Conversations capture context.
Static forms force complex situations into rigid dropdowns. Perspective captures structured data and the reasoning behind it — so your team makes better decisions, faster.
The static form
yoursite.com/intake
Category *
Select...
Details
Describe your situation...
Submit
Result:Category: "Other"|Details: "It's complicated"
No context. No follow-up. No next step.
- Exit surveys collect useless ratings like '3/10 satisfaction' without explaining why the user is leaving or what would change their mind
- Feature feedback forms get responses like 'the dashboard is confusing' with zero specifics about which elements cause problems or how users expect them to work
- NPS surveys tell you someone is a detractor but not whether they're comparing you to a competitor or frustrated by a single workflow issue
The AI conversation
"Tell me more about the timeline — when did this start, and is there a deadline your team is working against?"
Extracted & structured automatically
Category
High-priority
Urgency
Deadline: 2 weeks
Sentiment
Frustrated but hopeful
Next step
Route to senior team
Triggered: Slack alert sent| CRM updated
Right team. Full context. Instant action.
- Adaptive conversations explore exactly why someone is considering alternatives and what specific improvements would retain them as a customer
- AI follow-ups dig into feature complaints to uncover which workflow steps fail and what users expected to happen instead
- Conversations naturally surface competitive context — which alternatives users are evaluating and what features are driving their comparison
What makes user feedback actionable vs useless?
Actionable feedback connects specific user experiences to product decisions. Instead of 'the interface is hard to use,' you need to know which interface elements cause problems and what users expected instead. Traditional feedback forms collect sentiment without context. Users rate features but don't explain their workflow or competitive alternatives they're considering. Adaptive feedback conversations probe deeper into each response, asking follow-up questions that reveal the specifics your product team needs to prioritize improvements and prevent churn.
FAQ
Frequently Asked Questions
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Replace drop-off, poor qualification, and missing context with AI conversations that capture structured data and real understanding. Set up in minutes.
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