Insurance Claims Experience & Satisfaction Survey
Measures policyholder satisfaction across the full claims journey — from submission through resolution — using CSAT and NPS metrics to pinpoint friction points and improvement opportunities.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
Have you filed an insurance claim in the past 12 months?
- Yes
- No
How did you submit your most recent claim?
- Website
- Mobile app
- Phone
- In person
- Through an agent or broker
- Other (please specify)
Through which channels did you receive updates about your claim? Select all that apply.
- SMS / text message
- Mobile app push notifications
- Phone call
- Web portal status page
- I did not receive any updates
- Other (please specify)
What is the current status of your most recent claim?
- Resolved — fully approved
- Resolved — partially approved
- Denied
- Still in progress
Overall, how satisfied are you with your claim handling experience?
What is your age group?
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
Thank you for taking the time to share your feedback. Your responses will help us identify ways to improve the claims experience.
When was your most recent claim submitted?
- Within the last 30 days
- 31–90 days ago
- 3–6 months ago
- 7–12 months ago
How easy was it to find where and how to submit your claim?
How would you rate the frequency of updates you received about your claim?
Approximately how many calendar days passed from your claim submission to the final decision? If your claim is still in progress, please estimate the number of days so far.
How likely are you to recommend this insurance company to a friend or colleague based on your claim experience?
In which region do you currently live?
- Africa
- Asia-Pacific
- Europe
- Latin America & Caribbean
- Middle East
- North America
- Prefer not to say
How clear were the instructions and information required to complete your claim submission?
How clear and easy to understand were the updates you received?
How would you rate the speed of your claim handling?
Please rank the following aspects of the claims process from most to least important to you.
- Speed of resolution
- Clarity of communication
- Fairness of outcome
- Ease of submission
- Supportiveness and empathy
Which gender do you identify with?
- Woman
- Man
- Non-binary
- Prefer not to say
How easy was the overall process of completing and submitting your claim?
How easy was it to reach someone when you had questions about your claim?
How fair was the final outcome of your claim?
What is one thing that could be improved about the claims process?
Approximately how many minutes did it take to complete your claim submission? Please estimate if you are unsure.
Based on your responses in this survey, please share any additional thoughts or feelings about your claim experience.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- AI follow-ups automatically dig deeper when respondents report low satisfaction, uncovering root causes that static surveys miss
- Academic-grade scale construction with rubric-checked questions—no leading language or attention checks that bias results
- Every prompt, model, and logic branch is fully transparent and logged for reproducibility, unlike black-box competitor analytics
- AI interviewer dynamically follows up on churn reasons—if a customer says 'too expensive,' it probes whether that's absolute cost, perceived value, or competitive pricing
- Separate templates for exit diagnostic vs. win-back capture both the 'why they left' and 'what would bring them back' with distinct methodological approaches
SurveyMonkey
Customer Satisfaction Survey TemplateSurveyMonkey's flagship CSAT template is expert-certified and widely used, covering overall satisfaction, NPS, and CES together. It offers solid distribution channels (email, SMS, web links, QR codes) and built-in CSAT score calculation. However, it relies entirely on static pre-written questions with no adaptive probing.
What it does well
- Expert-certified methodology with built-in CSAT scoring formula and industry benchmarks
- Extensive distribution options including SMS, email, web links, and QR codes
- Large ecosystem with 400+ templates and cross-template metric comparison
Where it falls short
- No AI-powered follow-up questions—open-ended responses are passive, not probed
- Relies on demographic segmentation after the fact rather than real-time adaptive questioning
- Paid plans required for advanced features; Team plans range from $25-$75/user/month which adds up fast
Typeform
Top Customer Satisfaction Survey Questions & TemplateTypeform emphasizes a conversational, one-question-at-a-time interface designed to feel like a conversation rather than a form. Their CSAT template has good UX advice around avoiding bias and question timing, but ultimately all branching is pre-defined—there's no intelligent adaptation based on responses.
What it does well
- Beautiful conversational UI that asks one question at a time, boosting completion rates
- Strong guidance on avoiding biased language and proper survey timing
- 300+ integrations with tools like Slack, HubSpot, and Google Sheets
Where it falls short
- No AI follow-up capability—branching logic must be manually pre-configured for every path
- No prompt or model transparency; the 'conversational' feel is purely visual, not intelligent
- Limited methodological rigor—templates are light on proper academic scale construction
SurveySparrow
FREE Customer Satisfaction Survey TemplateSurveySparrow's CSAT template features a chat-like interface and claims 40% higher response rates. It includes recurring survey scheduling, multi-channel distribution, and conditional logic. However, its AI capabilities are limited to text analytics on collected responses rather than intelligent in-survey probing.
What it does well
- Chat-like conversational interface with claimed 40% higher response rates
- Recurring survey scheduling for automated pulse checks over time
- Conditional logic with skip/display rules to reduce survey fatigue
Where it falls short
- AI features limited to post-collection text analytics (CogniVue)—no in-survey AI follow-ups
- No transparency into how their AI text analytics models work or what prompts drive analysis
- Template questions are generic and not tailored to specific CX touchpoints like chatbot handoffs or checkout friction
Jotform
Online Shopping SurveyJotform's online shopping survey template is a basic form-builder approach—fully customizable with drag-and-drop, 100+ integrations, and free to use. It's functional but lacks any CX-specific methodology, AI capabilities, or sophisticated survey design principles.
What it does well
- Completely free with no-code drag-and-drop customization
- 100+ integrations including Google Drive, Dropbox, and Airtable
- Report Builder tool for analyzing responses visually
Where it falls short
- No AI-powered follow-ups or intelligent branching—purely static form fields
- No built-in CSAT scoring, CES calculation, or CX-specific methodology
- Generic shopping survey questions with no academic rigor or validated scale construction
Qualtrics
Customer Retention Survey Best PracticesQualtrics offers enterprise-grade CX measurement with advanced features like Predict iQ for churn prediction and conversational analytics. Their approach is the most sophisticated among competitors, but it comes at enterprise pricing that's prohibitive for academics and small teams, and their AI operates as a black box.
What it does well
- Predict iQ can analyze research data to predict which customers are about to churn
- Conversational analytics for understanding emotion, effort, intent and sentiment at scale
- Enterprise-grade action planning and closed-loop ticketing based on survey triggers
Where it falls short
- Enterprise pricing is prohibitive for academics, startups, and small CX teams
- AI analytics operate as a black box—no visibility into prompts, models, or logic flows
- Templates are gated behind sales conversations; no free self-serve template access for most CX use cases
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.