Customer Effort Score (CES) Survey Template
CES surveys give you scores, not solutions. Traditional CES surveys only capture scores without context. This conversational template digs deeper when users report high effort, identifying specific UI issues, workflow bottlenecks, or feature gaps that impact your product experience.
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.
On a scale of 1-7, how easy was it to complete your task today?
What specific task were you trying to accomplish?
How it adapts
Follow-ups that change based on what people say.
If CES score is 6-7, ask about specific steps that felt difficult
If user mentions mobile experience, ask about device and browser type
Where it routes people
Different paths for different answers.
Route high effort scores (5-7) to product team for feature feedback
Route bug reports to technical support with priority tagging
Automations it can trigger
Actions that fire the moment a response comes in.
Create Jira tickets for reported UI/UX issues with effort context
Update customer health scores in ChurnZero based on CES responses
Send follow-up sequences in Intercom for users reporting high effort
How this AI template works
Users rate their effort level, then the AI asks targeted follow-ups based on their score. High effort responses trigger questions about specific pain points, while positive scores explore what worked well for future optimization.
Getting started
- 1
Define your CES scale and effort measurement criteria
- 2
Set up conditional flows for different effort score ranges
- 3
Configure follow-up questions for friction point identification
- 4
Connect responses to your product analytics and support tools
Template Details
- Agent Type
- Evaluator
- Industries
- SaaS / Tech
- Roles
- Customer SuccessSupport
- Integrations
- Slack, Hubspot, Webhook
- Times Used
- 2,354+
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 CES surveys capture effort scores like 4/7 but provide zero context about what actually caused the friction. Teams receive ratings without understanding which specific steps, features, or processes frustrated customers most.
- Traditional customer effort score forms ask the same rigid questions regardless of the customer's actual experience. When someone reports high effort, there's no way to immediately dig deeper into root causes or specific pain points.
- Fixed CES survey templates create completion fatigue because customers must answer irrelevant questions about touchpoints they never experienced. Drop-off rates spike when forms feel generic rather than tailored to their specific interaction.
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.
- Conversational CES collection automatically asks follow-up questions when customers report high effort, uncovering specific bottlenecks like confusing UI elements, missing information, or broken workflows that teams can immediately address.
- Adaptive conversations adjust questions based on the customer's actual journey, exploring relevant friction points while skipping irrelevant areas. This personalized approach doubles completion rates compared to static forms.
- Dynamic effort conversations feel like helpful support interactions rather than tedious forms, reducing survey fatigue. Customers willingly share detailed feedback when the experience feels conversational and responsive to their situation.
What makes Customer Effort Score surveys effective?
Effective CES surveys measure friction immediately after specific interactions when details are fresh in customers' minds. The key is moving beyond basic effort ratings to understand root causes of difficulty. Traditional CES forms ask customers to rate effort on a 1-7 scale but miss the context needed for improvements. The most valuable CES data comes from follow-up questions that explore which specific steps caused problems and how processes could be easier. Timing matters significantly - deploy CES conversations within hours of the interaction being measured.
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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