Pricing Survey Questions for a Complete Offer Test

Pricing survey questions are useful when the buyer knows exactly what the price includes. A question about a $15 pack means little if one person imagines six cans, another imagines twelve and a third expects a subscription discount.

For an independent-group offer test, show each person one complete offer at one assigned price. Ask about understanding and stated buying before asking them to explain the price. The instrument below gives you a practical starting point; our pricing research methods guide helps choose a different design when the uncertainty is a price range, a price ladder or a bundle tradeoff.

Fix the pack before assigning the price

Lumen is the hypothetical sparkling-tea example used in our pricing research guide. This proposed questionnaire has no collected responses. Its two test cards differ only in the displayed price.

Screen for the intended category and shopping situation before showing the card. If the business wants to learn about a specific buyer group, plan that group’s evidence rather than hoping it will appear in a broad sample.

For a human independent-group comparison, define allocation and valid responses per group in advance. The sample-size worksheet separates estimating one share from planning the difference between groups. Generated response counts need a separate model-validation assessment.

Six questions for the assigned offer

Use the same question wording and response options in both groups. Keep the price displayed with the offer so a memory error does not become an apparent preference.

1. What does the person think they would receive?

In your own words, what would you get for the price shown?

Use an open response. Check pack quantity, the one-off purchase and any assumed promotion. Record misunderstandings before correcting them. If the card is revised, identify it as a new version rather than merging corrected and first-exposure answers.

2. What is their stated buying intention?

At the price and terms shown, how likely would you be to buy this six-pack on your next grocery visit?

Offer: definitely would; probably would; might or might not; probably would not; definitely would not. Provide a separate “this shopping situation does not apply to me” response and review eligibility. Define the actual buying window if “next grocery visit” is too open for the decision.

3. What explains that intention?

What is the main reason for your answer?

Use an open response linked to the intent rating and assigned price. A concern about the drink itself is different from a concern about the pack cost. Keep that distinction when deciding whether to change the product, price or audience.

4. How does the price compare with the buyer’s usual reference?

Compared with what you would normally spend on a comparable pack, how does this price seem?

Offer: much higher; somewhat higher; about the same; somewhat lower; much lower. Keep “I do not normally buy a comparable pack” and “I do not know” separate.

This measures a reported price comparison. It does not verify the current shelf price of another product. If the actual competitive offer matters, collect or supply that offer separately with its pack, price, channel and date.

5. What would be bought instead?

If this six-pack were not available, what would you most likely buy on that visit?

Use an open response and allow no drink purchase. The answer helps identify the alternative to investigate. It is not an observed substitution rate or evidence that a higher-priced pack creates additional category spending.

6. What remains unresolved before purchase?

What else would you need to know before deciding whether to buy the offer shown?

Use an open response. Missing sweetness information calls for a clearer card. Wanting a smaller pack calls for another offer. A lack of local stock calls for an availability check. Keep these actions separate instead of labeling every hesitation “too expensive.”

Read the price groups with their answer bases

Report the full intent distribution for each assigned price. If the positive share combines “definitely” and “probably,” show that definition and the valid eligible denominator beside it. Keep inapplicable, missing and failed-exposure states visible rather than treating them as rejection or quietly dropping them.

Do not call a response gap price elasticity from observed sales. The study compares stated intention under shown prices. Nor does multiplying a price by an intent share turn the result into a revenue forecast. The existing pricing guide shows how to compare that response index with contribution assumptions while keeping actual selling for a pilot.

If each person sees several prices, use a design intended for that exposure, such as Gabor-Granger, and account for the earlier prices they have seen. If features or packs change with price, a conjoint design may address that tradeoff more directly. The questionnaire here keeps one complete offer at one assigned price.

Choose the next market test with the economics visible

A lower price can attract more stated interest while leaving less contribution per sale. Use the business’s actual costs, margin requirement and operational constraints to choose which price deserves a real selling test. Record those inputs as business assumptions rather than survey findings.

For a simulated study, inspect our product and pricing validation comparisons and agree which audience, offer and response measure the evidence supports. A human pilot can then test actual availability, paid conversion and repeat buying under the chosen terms.

Plan a Sapien price comparison around the complete pack, the alternatives buyers already have and the costs the selected price has to cover.