You gave us a 7 — what would it take to make that a 10?
M
Uncover NPS Insights
Evaluator agent · 1.8K uses
Evaluator Agent
Customer Satisfaction Survey Template
Static CSAT surveys hide why customers churn. Traditional CSAT surveys only capture ratings without understanding why customers feel that way. This conversational approach explores the reasoning behind scores, identifies specific pain points, and gathers actionable feedback that teams can actually use to improve products and services.
Deeper context
Higher completion
Actionable insights
Used 1,525+ times
What's inside this template
Start from this conversation and adapt it to your team — change any question, add your own logic, and connect the tools you already use.
Questions it always asks
The core fields every response captures.
Overall satisfaction rating with our product/service (1-10 scale)
Likelihood to recommend us to others (NPS question)
How it adapts
Follow-ups that change based on what people say.
If satisfaction score is below 7, ask about specific pain points and frustrations
If customer mentions support, dive deeper into response time and resolution quality
Where it routes people
Different paths for different answers.
Route detractors (score 1-6) to retention team for immediate follow-up
Send promoters (score 9-10) to sales team for referral opportunities
Automations it can trigger
Actions that fire the moment a response comes in.
Create support ticket for reported issues with customer details attached
Add customer feedback tags to CRM profile based on mentioned topics
Send survey results to Slack channel with sentiment analysis summary
SOC 2 Type II and ISO 27001:2022 certified. Responses are encrypted in transit and at rest, and you own your data. View our Trust Center.
How this AI template works
The AI starts with standard satisfaction questions, then dynamically follows up based on responses. Low scores trigger deeper exploration of problems, while high scores identify what's working well. The conversation naturally flows to gather specific examples and improvement suggestions.
Getting started
- 1
Define your core satisfaction metrics and rating scales
- 2
Set up follow-up question flows for different score ranges
- 3
Configure customer data integration for personalized questions
- 4
Test conversation paths with different response scenarios
Template Details
- Agent Type
- Evaluator
- Category
- Customer feedback survey
- Industry
- SaaS / TechProfessional Services
- Business outcome
- Improve customer satisfaction
- Job to be done
- Collect customer feedback
- Journey stage
- Feedback & evaluation
- Replaces
- Survey tools
- Integrations
- Slack, Hubspot, Email
- Times Used
- 1,525+
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.
- Rating scales capture scores but miss the reasons behind customer dissatisfaction. Your team sees a 6/10 rating but has no idea what specific interaction or product issue caused the low score.
- Generic CSAT questions produce responses like 'too expensive' or 'poor service' that don't reveal which pricing tier frustrated them or what service interaction went wrong. Teams waste time guessing at solutions.
- Multi-page satisfaction forms with mandatory fields frustrate already unhappy customers. The customers most likely to churn abandon these forms halfway through, taking their critical feedback with them.
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 probe deeper when customers give low satisfaction scores, asking 'What specifically made that experience frustrating?' This reveals whether the issue was response time, knowledge gaps, or process failures your team can actually fix.
- Natural conversation flow encourages customers to elaborate on their ratings, turning a 4/10 score into detailed feedback like 'the onboarding took three weeks longer than promised and no one kept me updated on progress.'
- Context-aware follow-ups adapt based on customer responses, asking about specific features they mentioned or diving deeper into service interactions that caused problems. This personalized approach captures insights static forms miss completely.
What questions should I ask in a customer satisfaction conversation?
Start with an overall satisfaction rating, then let the conversation adapt based on their response. For low scores, probe deeper with questions like 'What specifically caused that frustration?' For high scores, explore what's working well to replicate across other customers. Include touchpoint-specific questions about recent support interactions, product experiences, or service delivery. The key is asking intelligent follow-ups that turn ratings into actionable feedback. A customer saying 'support was slow' leads to questions about which channel, what time of day, and what type of issue they had.
FAQ
Frequently Asked Questions
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