Gabor-Granger Pricing
Also known as: Gabor-Granger, Gabor-Granger Technique, Direct Price-Response Method, Purchase-Intent Pricing
The Gabor-Granger method is a direct pricing-research technique that estimates a product's demand curve by asking respondents whether they would buy it at each of several price points. Developed by economists André Gabor and Clive Granger in the 1960s through surveys of how consumers perceive and react to prices, it asks a simple question, would you purchase at this price?, across a ladder of prices, usually presented in random order. Aggregating the share of people willing to buy at each price traces a stated demand curve, from which the analyst computes expected revenue at every price and identifies the price that maximizes it. Because it focuses on a single product rather than competitive trade-offs, Gabor-Granger is fast, intuitive, and well suited to setting or testing a price for an existing or clearly defined offering. It also yields a straightforward estimate of price elasticity. Its directness is both its appeal and its main weakness, since asking about price in isolation can prime respondents and overstate price sensitivity.
Key highlights
- Fast, intuitive, and inexpensive, producing a demand curve and revenue-maximizing price from a short survey.
- Directly estimates price elasticity across the tested range, highlighting where demand is most and least sensitive.
- Requires no complex experimental design, making it accessible for confirming or testing the price of a single product.
- Easily combined with cost data to move from revenue maximization to profit maximization.
Intuition
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How it works
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When to use it
Use Gabor-Granger when you need a quick, direct read on the price-response curve and revenue-maximizing price for a single, clearly defined product or service, especially for an existing offering or a concept that respondents can evaluate on its own. It is well suited to confirming a planned price, testing a price increase, or comparing a few price scenarios with a modest survey. It is poorly suited when pricing depends on competitive context and brand trade-offs, in which case brand-price trade-off or choice-based conjoint better reflect how customers actually choose, and when the product is novel enough that direct purchase-intent is unreliable. Because it elicits price in isolation, it should be read as directional and ideally triangulated with conjoint or revealed-preference evidence.
Strengths & limitations
- Fast, intuitive, and inexpensive, producing a demand curve and revenue-maximizing price from a short survey.
- Directly estimates price elasticity across the tested range, highlighting where demand is most and least sensitive.
- Requires no complex experimental design, making it accessible for confirming or testing the price of a single product.
- Easily combined with cost data to move from revenue maximization to profit maximization.
- Asks about price in isolation, which primes price consciousness and tends to overstate true price sensitivity.
- Ignores competitive context and brand trade-offs, so it does not reflect how customers choose among alternatives.
- Stated purchase intent overstates actual purchasing, so absolute acceptance levels are unreliable.
- Conclusions are only as good as the price range tested; a poorly chosen range can hide the true optimum.
Common pitfalls
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Applications
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Frequently asked
How does Gabor-Granger differ from Van Westendorp?
Both are direct, survey-based pricing methods, but they ask different questions. Gabor-Granger asks a yes/no purchase-intent question at each of several specific prices, producing a demand curve, revenue-maximizing price, and elasticity. Van Westendorp asks four open-ended questions about prices that seem too cheap, cheap, expensive, and too expensive, and from the cumulative distributions infers an optimal price point and a range of acceptable prices rather than a demand curve. Gabor-Granger is better for finding a revenue or profit optimum at concrete price points, while Van Westendorp maps perceived price boundaries; the two are often used together for a fuller picture.
Why does the method tend to overstate price sensitivity?
Gabor-Granger draws respondents' attention to price repeatedly and in isolation from the competitive and contextual cues that accompany real purchases. This priming makes people behave as more deliberate, price-focused shoppers than they typically are, so stated demand falls off more steeply with price than real demand would, inflating the estimated elasticity. As pricing-research guides note, the absolute acceptance figures and elasticities should therefore be read as directional and relative rather than literal, and conclusions are stronger when cross-checked against choice-based conjoint or actual sales data, where price competes with other attributes.
Can Gabor-Granger find the profit-maximizing price, not just revenue?
Yes. The core output is a stated demand curve, acceptance share at each price, from which revenue at each price is price times share. If unit cost information is available, expected profit at each price is the demand share times the margin (price minus cost), and the price maximizing that product is the profit-maximizing price. Because profit usually peaks at a higher price than revenue, this distinction matters managerially. The same caveats apply, intention-inflated demand and isolated price framing, so the profit optimum is best treated as guidance and validated against richer methods or market evidence.
Sources
- 1.Gabor, A., & Granger, C. W. J. (1966). Price as an Indicator of Quality: Report on an Enquiry. Economica, 33(129), 43-70.
- 2.Orme, B. K. (2020). Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research (4th ed.). Madison, WI: Research Publishers LLC.ISBN 9780972729772
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Cite this page
ScholarGate. (2026, June 23). Gabor-Granger Pricing. ScholarGate. https://scholargate.app/marketing-research/gabor-granger-pricing