Q01
Message
All templates
Offer Clarity, Incentive Fit & Referral Intent Survey
Measures how clearly customers understand promotional offers, how well incentives match their preferences, and their likelihood of referring others — identifying friction points to improve referral rates and conversions.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
19 questions · ~9 min
Q02
Dropdown
When did you last notice a promotional offer or incentive from us?
- Within the last 7 days
- 8–30 days ago
- 1–3 months ago
- More than 3 months ago
- I don't recall
Q03
Opinion Scale
The offer was easy to understand.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q04
Opinion Scale
How appealing was the incentive to you personally?
Scale: 1 – 7
Min:Not at all appealingMax:Extremely appealing
Q05
Opinion Scale
How likely would you be to recommend or share this kind of offer with a friend or colleague?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q06
AI Interview
We'd like to understand more about your experience with our offers. An AI moderator will ask you a couple of brief follow-up questions based on your responses.
Q07
Dropdown
What is your age group?
- Under 18
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
Q08
Message
Thank you for completing this survey — your feedback helps us create better offers for you. Your responses are confidential and will be reported only in aggregate.
Q09
Multiple Choice
Where did you see that offer? (Select all that apply)
- In-app message
- Website banner
- Social media
- Friend or word of mouth
- In-store or on-premise
- SMS / text message
- Other
Q10
Opinion Scale
The terms and conditions of the offer were clear.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q11
Multiple Choice
Which of the following influenced whether the incentive felt like a good fit for you? (Select all that apply)
- Amount or discount size
- Relevance to my needs
- Timing or expiry window
- Required effort or steps
- Terms and conditions
- Trust in the brand
- My previous experience with this company
- Other
Q12
Multiple Choice
If you were to share an offer, which channels would you use? (Select all that apply)
- SMS / text message
- Messaging app (e.g., WhatsApp, iMessage)
- Social media post
- Direct message on social media
- In person
- Copy/paste a link
- Other
Q13
Long Text
Based on your responses in this survey, is there anything else you'd like to share about your experience with our offers or incentives?
Q14
Multiple Choice
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer to self-describe
- Prefer not to say
Q15
Opinion Scale
I knew exactly what steps I needed to take to redeem the offer.
Scale: 1 – 7
Min:Strongly disagreeMax:Strongly agree
Q16
Ranking
Please rank the following factors from most to least important when deciding whether to act on an incentive.
- Amount or discount size
- Relevance to my needs
- Timing or expiry window
- Required effort or steps
- Terms and conditions
- Trust in the brand
Drag to rank
Q17
Multiple Choice
What, if anything, might stop you from sharing an offer like this? (Select all that apply)
- Not confident it's valuable enough to share
- Unsure about the terms or fine print
- Don't want to bother others
- Privacy or security concerns
- It feels too promotional or spammy
- I rarely share offers in general
- Don't know anyone who'd be interested
- Nothing — I'd share it
- Other
Q18
Dropdown
In which region do you currently live?
- Africa
- Asia
- Europe
- North America
- South America
- Oceania
- Middle East
- Prefer not to say
Q19
Long Text
In your own words, what was the offer about?
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.