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A respondent says yes to a price in a survey. A commercial team multiplies that share by the market size and calls the result demand. The arithmetic is easy. The jump from an answer to a transaction is the hard part.
Gabor-Granger pricing research is a stated-intent protocol that tests purchase or acceptance responses at declared price points. It produces a structured research signal. It does not directly observe a market price, realized revenue, or a binding willingness-to-pay fact.
The conjoint article owns the boundary between stated preference and demand in multi-attribute choice. This page owns the simpler price-point sequence and the validation needed before a price curve is used for a commercial decision.
How does the method work?
Declare the research object before asking the first question:
- Define the offer, buyer unit, context, currency, and price basis.
- Choose price points and the order or randomization rule.
- Ask the same binary or scaled purchase-intent question at each point.
- Preserve respondent eligibility, prior exposure, and missing responses.
- Summarize the share selecting the stated response at each price.
- Treat the resulting curve as intent under the prompt, not observed demand.
- Validate the point price with choice, budget, channel, capacity, and transaction evidence.
The response rule matters. “Would consider,” “likely to buy,” and “would authorize” are not the same event. A price point without a unit or buying context is not a reproducible observation.
What does research contribute?
Urban, Weinberg, and Hauser examine premarket forecasting for really-new products and show why forecasting requires more than a simple direct question about purchase. Aydin, Kwong, Ji, and Law review market-demand estimation methods for new-product development and distinguish direct survey approaches from indirect choice approaches (Urban et al., 1996; Aydin et al., 2014).
These sources do not evaluate a single current Gabor-Granger implementation. They support the method boundary: a stated response is an input to a forecast or pricing decision, not the transaction itself. A direct, version-checked Gabor-Granger source is not yet held in the local evidence library, so the procedural description below is an author method description and this pair remains draft-only pending acquisition.
What does a stated-intent curve look like?
The chart is synthetic. It shows the share selecting a declared “would buy” response at five prices. It is not a demand curve, a market share estimate, a price recommendation, or a calibrated probability.
Figure 1The synthetic Gabor-Granger intent curve
The curve describes stated responses under a prompt. It does not reveal the market-clearing price or realized revenue.
Source: Author's synthetic illustration bounded by Urban et al. (1996) and Aydin et al. (2014); all values are illustrative stated-intent shares.
The downward shape is not the finding. The finding is that the shape has a declared question, sample, offer, price basis, and response rule. Change any of those and the curve represents a different research object.
Which mistakes make the curve look stronger than it is?
- Intent substitution: a likely-buy answer is reported as a purchase.
- Price-basis drift: respondents see a monthly price while the model uses annual revenue.
- Context omission: procurement, implementation, switching, tax, or service costs are absent.
- Order effect: later prices are interpreted relative to earlier anchors.
- Sample leakage: respondents who cannot buy are included without an eligibility rule.
- Market-size multiplication: an intent share is multiplied by TAM without adoption, access, capacity, or budget constraints.
An intentional design can address some of these issues. It cannot make a stated answer an observed transaction by labeling it “demand.”
How should a team use the result?
- Report the exact question and response scale.
- Show the price basis and tested sequence.
- Segment by eligible buyer and decision context.
- Preserve nonresponse and “cannot assess” states.
- Compare the stated curve with observed choice, quote response, pilot conversion, or transaction data when those objects become available.
- State which decision the curve informs: price screen, offer design, sample selection, or next research.
Do not select a price by finding the highest stated share. The decision may optimize revenue, margin, contribution, adoption, access, or learning. The objective must be declared separately.
What is Gabor-Granger pricing research not?
It is not a market price, a guaranteed demand forecast, a willingness-to-pay fact, or proof that respondents can or will transact. It is not interchangeable with revealed preference, conjoint choice, price elasticity, or observed revenue.
Use Gabor-Granger as a structured stated-intent signal. Keep the response, the forecast, the commercial decision, and the later transaction as separate objects until the evidence connects them.
The revealed-preference article draws the boundary between stated acceptance and observed choice under constraints.
References
- Aydin, R., Kwong, C. K., Ji, P., & Law, H. M. C. (2014). Market demand estimation for new product development by using fuzzy modeling and discrete choice analysis. Neurocomputing, 142, 136-146. DOI
- Urban, G. L., Weinberg, B. D., & Hauser, J. R. (1996). Premarket forecasting of really-new products. Journal of Marketing, 60(1), 47-60. DOI
