Discount and Promotion Sensitivity Survey
Measures how deal-driven your customers really are: what triggers a discount-motivated purchase, whether frequent promotions erode brand perception, and how willing shoppers are to pay full price. An AI follow-up reconstructs the last purchase decision they made under a discount to separate genuine price sensitivity from habit.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
In the last 3 months, how often did you buy from (Replace with your brand/category) only because it was discounted?
- Never — I don't wait for sales
- Rarely, once or twice
- About half the time
- Most of the time
- Almost always
Which of these promotion types have gotten you to buy in the last 3 months? Select all that apply.
- Percent-off discount
- Buy-one-get-one (BOGO)
- Free shipping threshold
- Loyalty/points reward
- Flash sale / limited-time deal
- Bundle deal
- First-time customer discount
Thinking about promotions in general, which of these matter most to you, and which matter least?
- Percent-off discount
- Buy-one-get-one (BOGO)
- Free shipping threshold
- Loyalty/points reward
- Flash sale / limited-time deal
- Bundle deal
- First-time customer discount
What's the smallest discount that would actually change your decision to buy something you were already considering?
- Any discount at all
- Less than 10% off
- 10–20% off
- 20–30% off
- 30% or more off
- Discount size doesn't matter to me
If (Replace with your brand) never ran a sale again, how willing would you be to keep buying it at full price?
How much do you agree with each statement?
- Frequent discounts make me think a brand is lower quality
- I actively wait for a sale before purchasing something I want
- I'd stay loyal to a brand I like even without discounts
- Constant sales make me trust the regular price less
- A discount makes me buy sooner than I otherwise would have
You have 100 points to distribute across what actually drives your purchase decision for (Replace with your category). Allocate more points to what matters more.
- Price / discount available
- Brand reputation
- Product quality
- Convenience / availability
- Reviews or recommendations
Reconstruct the respondent's most recent purchase from (Replace with your brand/category) that involved a discount: what the deal was, whether they would have bought anyway without it, and how much time passed between seeing the promo and buying. If they said discounts don't matter to them, probe whether that holds for an actual recent purchase or is aspirational self-image. If they flagged quality concerns from frequent discounting, ask for a specific example.
What is your age range?
- Under 18
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65 or older
- Prefer not to say
Which best describes your household income?
- Under $30,000
- $30,000–$59,999
- $60,000–$99,999
- $100,000–$149,999
- $150,000 or more
- Prefer not to say
That's everything — thank you! Your responses will help us decide when and how much to discount without training customers to only buy on sale.
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
- Includes an AI follow-up interview block that reconstructs the respondent's actual last discount-driven purchase, separating genuine price sensitivity from habitual deal-seeking rather than relying on hypothetical self-report.
- Combines quantitative trade-off methods (best-worst trade-off, point-allocation) with attitudinal measures (matrix, rating-scale) so you get both stated priorities and a forced-tradeoff ranking of what really drives purchase decisions.
- Asks for the smallest discount threshold that would change a buying decision, giving a concrete pricing lever instead of vague sensitivity scores.
- Automated per-response quality scoring and an auto-generated report mean the open-ended AI follow-up data is usable without manual coding.
SurveySparrow
Price Sensitivity Questionnaire TemplateA fielding-ready questionnaire template focused on price sensitivity, likely covering standard willingness-to-pay style questions. It's a static question set built for quick deployment rather than a discount-behavior deep dive. No mention of adaptive follow-up or purchase reconstruction.
What it does well
- Ready-to-use price sensitivity template
- Part of a broader survey platform with distribution and reporting tools
- Likely supports standard question types (scales, multiple choice) for quick setup
Where it falls short
- No adaptive AI follow-up to reconstruct a specific past purchase decision
- No published per-response quality scoring or prompt transparency
- Static questionnaire format can't probe deeper into individual respondent reasoning
Typeform
Price Sensitivity Survey TemplateA conversational-style form template aimed at gauging price sensitivity, benefiting from Typeform's polished UX and completion rates. It's a fixed question flow, not an AI-driven interview, so all respondents get the same static prompts. Good for quick directional signal, less suited to distinguishing habit from true sensitivity.
What it does well
- Clean, high-completion-rate form design
- Easy to customize and brand
- Simple setup for standard price sensitivity questions (e.g., Van Westendorp-style)
Where it falls short
- No adaptive follow-up questions based on individual answers
- No voice AI interview or guided task/screen-share option
- Lacks automated quality scoring or transparent prompt methodology for open text responses
Frequently asked questions
What questions are in the “Discount and Promotion Sensitivity Survey” template?
The template includes 12 ready-to-use questions, starting with: “Thanks for taking a few minutes to share how sales and discounts affect your shopping decisions. Your responses are comp…” · “In the last 3 months, how often did you buy from (Replace with your brand/category) only because it was discounted?” · “Which of these promotion types have gotten you to buy in the last 3 months? Select all that apply.”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 12 questions in about 7 minutes.
Can I customize this template?
Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.
Is this template free to use?
Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
Related templates
More studies on similar topics.
Price Increase Reaction & Churn Risk Study
Measures how customers react to an upcoming or recent price increase — their acceptance thresholds, likelihood to churn, need to re-justify the value, and preferences for how the change is communicated. An AI follow-up digs into the specific reasoning behind each customer's churn risk score, surfacing what would actually change their mind versus what they say in the closed-ended scales.
View templatePrice Sensitivity & Willingness-to-Pay Survey
Maps how a target market perceives a product or service's price using the four classic price-sensitivity questions, then layers in purchase intent, feature value trade-offs, and a budget allocation exercise. An AI follow-up interview digs into the reasoning behind each respondent's expensive/cheap thresholds so pricing teams get the numbers and the 'why' behind them.
View templateOnline Purchasing Habits and Decision Drivers Survey
Measures how often people shop online, what actually drives a buy-or-abandon decision, and where friction shows up in checkout, delivery, and returns. An AI follow-up interview reconstructs a real recent purchase (or near-purchase) moment instead of relying on generic satisfaction ratings, making it useful for e-commerce and retail teams diagnosing drop-off.
View templateGasoline Buying Habits and Price Sensitivity Survey
Measures how often people buy gasoline, what drives their choice of station, and how they perceive fair versus unfair pump prices — for retailers, fuel brands, and pricing teams. An AI follow-up interview digs into the gap between stated price sensitivity and what actually makes drivers switch or stay loyal.
View templateSupermarket Shopping Attitudes and Habits Survey
Captures how shoppers choose, evaluate, and switch between grocery stores and channels — price sensitivity, loyalty behavior, and channel mix — for retail and CPG researchers. An AI follow-up interview digs into the real story behind a shopper's most recent store choice or channel switch, beyond what a closed question can capture.
View templatePrice Sensitivity & Willingness-to-Pay Assessment
Measures price fairness perceptions, value-for-money judgments, and maximum willingness to pay among recent price-exposed prospects and customers. Ideal for pricing optimization, launch pricing validation, and competitive positioning research.
View template