CSAT Survey Template
Your CSAT scores hide the real problems. CSAT surveys collect a rating after ticket close. Your evaluator asks what happened — were they transferred too many times? Did the resolution actually work? Would they reach out again or just churn quietly? Now your team can fix the process, not just the ticket.
Used 2,200+ times
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
No context. No follow-up. No next step.
- Static CSAT forms give you a number but never explain what went wrong - a 2-star rating doesn't tell your support team what to fix or your product team what feature failed.
- Fixed rating scales miss the emotional context behind dissatisfaction - you can't tell if a low score means minor annoyance or business-critical failure that will cause churn.
- Pre-written follow-up questions ask the same things regardless of the satisfaction level, wasting opportunities to understand what delighted happy customers or what specific steps would retain unhappy ones.
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
Right team. Full context. Instant action.
- Adaptive follow-ups explore what specifically exceeded expectations for satisfied customers and what exact improvements would retain dissatisfied ones, turning ratings into retention strategies.
- Conversational depth captures the business impact and emotional weight behind each score, helping you prioritize which satisfaction issues actually drive churn versus minor friction.
- Dynamic probing identifies patterns in your best experiences that teams can replicate and specific failure points that need immediate attention, not generic improvement suggestions.
How this AI template works
After a support ticket is resolved, your evaluator reaches out to understand the full experience. It asks about response time, agent knowledge, resolution quality, and overall effort. Frustrated customers get flagged for follow-up. Process issues get surfaced to leadership. Happy customers get asked to leave a review.
Getting started
- 1
Share your current post-ticket CSAT flow — we'll enhance it
- 2
Define what matters most: resolution quality, speed, agent knowledge
- 3
Connect to Zendesk for ticket context and Slack for alerts
- 4
Deploy post-resolution and start hearing the real story
Template Details
- Agent Type
- Evaluator
- Industries
- SaaS / Tech
- Roles
- Customer SuccessSupport
- Integrations
- Slack, Zendesk, Gainsight
- Times Used
- 2,200+
What is a CSAT conversation and how does it work?
A CSAT conversation starts with the standard satisfaction rating question, then uses adaptive follow-up questions to understand the reasons behind each score. Instead of fixed questions that every customer answers the same way, the AI asks different follow-ups based on satisfaction level and previous responses. Satisfied customers get asked about specific highlights and referral likelihood. Dissatisfied customers get probed about what went wrong and what would improve their experience. The result is structured satisfaction data plus contextual explanations your teams can act on.
When should you send CSAT conversations to customers?
Send CSAT conversations immediately after specific touchpoints when the experience is fresh in memory. Best triggers include support ticket resolution, onboarding completion, product feature usage, or purchase fulfillment. Timing matters - send within 24 hours for highest response rates. Avoid survey fatigue by limiting customers to one CSAT conversation per touchpoint per quarter. The conversational format feels less intrusive than traditional forms, so customers engage longer and provide richer feedback even when contacted multiple times.
How to calculate CSAT scores from conversation data?
Calculate CSAT by dividing satisfied customers (rating 4-5 on a 5-point scale) by total respondents, then multiply by 100. Industry benchmarks range from 75-85% depending on sector and touchpoint. However, conversation-based CSAT provides additional metrics beyond the standard score - sentiment analysis, issue categorization, and improvement priority rankings. You get the industry-standard CSAT number for benchmarking plus qualitative insights that explain satisfaction trends and guide specific improvements your teams can implement.
What CSAT questions drive the most actionable feedback?
Start with the standard satisfaction rating, then let adaptive follow-ups explore the story behind each score. For high ratings, ask what specifically went well and whether they would recommend the experience. For low ratings, ask what fell short and what single change would improve their satisfaction. The AI conversation adapts based on responses - if someone mentions slow response time, it explores communication preferences. If they mention product confusion, it digs into specific feature friction points.
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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