31 Pricing Survey Questions: Frameworks, Samples & Best Practices

Gabor-Granger Pricing Method

Why & When to Use

If you need crystal-clear demand curves for specific prices, the Gabor-Granger method is your new best friend. Unlike broader frameworks, this one goes straight to the numbers: you show customers defined price points and ask how likely they are to buy at each. No fluffy hypotheticals—just crisp, real-world options.

This method comes alive when your concept is locked, features are fixed, and you need to know how price tinkering impacts demand. It’s awesome for validating next quarter’s pricing or seeing what a $10 delta really does to conversion rates. If you want to see where revenue maxes out and how elastic your product is, don’t skip Gabor-Granger.

Situations where the Gabor-Granger works its magic:

• Testing reaction to a planned price increase: Don’t anger your best customers—know before you go.
• Narrowing launch price for a finished product: Turn gut feel into something mathematically defensible.
• Measuring elasticity by segment: See who’s price-sensitive and who’ll shrug at a premium.
• Discounting experiments: Quantify where a price cut actually moves the needle.

This method is practical, actionable, and gives you a clear path for plotting revenue forecasts and segmentation strategies.

Five Sample Questions

1. Would you purchase Product X at $49? (Yes/No)

2. If not, would you purchase at $39? (Yes/No)

3. At $59, how likely are you to purchase? (5-point likelihood scale)

4. What is the maximum price you’d still find reasonable for Product X? (Numeric)

5. Which of these prices—$39, $49, $59—best matches what you would expect to pay?

The Gabor-Granger method effectively estimates demand curves and revenue-maximizing price points but may yield biased results due to lack of competitive context. (quirks.com)

Conjoint Analysis for Pricing Optimization

Why & When to Use

Sometimes price isn’t the whole story—features, bundles, and trade-offs rule the day. That’s where conjoint analysis struts in with a swagger. It dives deep into customer psychology to untangle which features push people to open their wallets, and which just pad out the spec sheet. This framework reveals ideal packaging and pricing for complex offerings, bundling dreams, and crowded markets.

Turn to conjoint analysis when you’ve got:

• Multiple product options: Think SaaS tiers, product lines, or service bundles.
• Feature-rich environments: Where “what’s included?” is almost as important as “how much?”
• Competitive markets: Your rival is adding AI, but does anyone really care?
• Prioritizing roadmap investments: Which features will boost willingness to pay most?

This approach turns decision-making into a science. It’s perfect for big launches, competitive repositioning, or just understanding where to squeeze more margin without losing too many fans. Conjoint analysis lights up the dark corners of bundling and positioning, so you stop guessing and start winning.

Five Sample Questions

1. Choose your preferred option among Package A ($29, basic) vs. Package B ($39, pro analytics).

2. Select the bundle you would most likely purchase: Option 1, 2, 3 (varying price/feature combos).

3. How important is 24/7 support when paying $10 extra per month?

4. Which version would you choose if Package C ($49) adds AI insights?

5. Rate your likelihood to purchase Package D at $59 with premium onboarding.

Monadic Price Testing Surveys

Why & When to Use

If you want to avoid the nasty anchoring effect that can warp price perception, monadic surveys offer a pure, distraction-free path. Here, each respondent sees only one price—no side-by-side comparisons, no sneaky clues about what you “really want.” The result? Clean, honest readouts on willingness to buy that slice through the noise.

Monadic testing is your best friend when you:

• Want to run genuine A/B price tests: No polling bias from seeing all possibilities.
• Need discrete, actionable purchase metrics: Each price point gets its own, untainted verdict.
• Are prepping in-market experiments: Go from survey to real-world test seamlessly.
• Operationalize quick learning loops: Launch, survey, learn, repeat.

This approach is incredibly sharp for learning what percentage of your target group will actually buy at a given price, not just what they think they “could” or “might” tolerate. Use it before big launches or for pricing updates where a single number will make or break your rollout. Monadic surveys keep your price tests honest, so you can trust the results (even if they sting a little!).

Five Sample Questions

1. Product X is available for $45. How likely are you to buy it today? (7-point scale)

2. Does this price feel too high, too low, or about right?

3. What concerns, if any, would stop you from purchasing at $45?

4. How much value do you feel you receive at this price? (1–10 scale)

5. Would you recommend Product X to a friend at $45? (NPS format)

Monadic price testing, by exposing respondents to only one price point, effectively eliminates bias and provides clear insights into price sensitivity. (pricingsolutions.com)

Brand–Price Trade-Off (BPTO) Surveys

Why & When to Use

When the competitive heat is on, you need to know if your brand can hold its ground at higher prices or if customers jump ship for a rival deal. That’s what brand–price trade-off surveys are built for. They put actual purchase choice in front of customers, comparing brands across real (sometimes hypothetical) prices and feature mixes.

Reach for BPTO surveys when:

• Testing price changes in a competitive market: Will your loyal base pay more if you increase prices?
• Evaluating market share risks: How much could you lose to a cheaper new entrant?
• Planning for perks, bundles, or promos: See if free shipping or a new feature sways the decision.

BPTO is unbeatable for modeling share shift scenarios—if Brand A goes up, who wins the defectors? If Brand B adds a feature, does it make a dent? It brings razor-sharp clarity to launch strategies, repositioning, and defending your turf.

Five Sample Questions

1. Choose one: Brand A at $29, Brand B at $25, or Brand C at $27.

2. If Brand A increased to $35, which would you buy?

3. At what price would Brand B become your preferred choice over Brand A?

4. Assume Brand C adds free shipping. Which option do you choose now?

5. How much more are you willing to pay for your current brand versus alternatives?

B2B Willingness-to-Pay (WTP) Surveys

Why & When to Use

Selling to businesses is a whole different ballgame—budgets, ROI hurdles, and buying committees galore. B2B willingness-to-pay surveys meet buyers where they live, by speaking their language: investment, returns, risk trade-offs, and procurement red tape.

This survey type shines brightest when:

• Dealing with enterprise deals: Buyers care deeply about proven ROI.
• Navigating multi-stakeholder sales: Different budget holders, sign-off thresholds, and procurement quirks.
• Testing various pricing models: Per-seat, usage-based, or annual flat rates.
• Sizing upsell or cross-sell potential: See what extra value is worth to your biggest accounts.

B2B WTP questions help you set credible list prices and negotiate confidently by revealing real-world budget ceilings, procurement pain points, and cost/benefit calculus of target accounts.

Five Sample Questions

1. What annual budget could you allocate for a solution that saves 10% in operating costs?

2. At $15,000 per year, how compelling is the ROI for your organization?

3. What pricing model aligns with your procurement policies? (Per-seat, usage, flat rate)

4. What price ceiling would require executive sign-off?

5. How much would you expect to invest to achieve a 3x ROI within 12 months?

Best Practices & Common Pitfalls (Dos and Don’ts)

Getting your pricing survey right is part art, part science. The secrets to great results are hiding in the details, so follow these dos and avoid these classic stumbling blocks to keep your survey data squeaky clean.

Do:

• Segment your audience so you spot differences in price perception by customer type or region.

• Pretest your questions to make sure people actually interpret them as intended.

• Randomize price points or presentation order to minimize bias.

• Contextualize the value proposition—don’t make respondents guess what your product does.

• Pair quantitative questions with open-ended follow-ups for richer insights.

Don’t:

• Lead with the price you hope to hear—keep things unbiased.

• Mix different pricing frameworks in a single survey—that breaks data comparability.

• Ignore localization or currency differences—context matters for clarity.

• Overload with too many price/feature combinations—decision fatigue is real.

• Forget to backtest survey data with real market experiments—paper promises don’t always turn into real dollars!

Each of these steps keeps your pricing survey sharp, relevant, and actionable. Remember: the smallest details can make or break the insights you get!

Conclusion & Next Steps for Running High-Impact Pricing Surveys

Every stage in your product life cycle calls for a different pricing survey strategy—from rough concepts with Van Westendorp to razor-sharp BPTO for mature products. The right tool plugs you into real customer perceptions and gives you confidence to set, shift, or defend your prices. Use a simple rule: if you want elasticity, choose Gabor-Granger or Monadic; for feature trade-offs, go with Conjoint; for competitive battles, BPTO wins. Always run surveys, test your results in the wild, and iterate your way to a price people love—and pay. The market never stands still, and neither should your pricing insights!