Gabor-Granger price calculator
Turn the share of people who would buy at each price into a demand curve, then find the price that earns the most revenue and, if you enter a unit cost, the most profit. Enter your price points, or load a file, and nothing leaves your browser.
The Gabor-Granger method asks whether people would buy at a series of prices; the share saying yes at each price is the demand curve. Multiplying price by that share gives revenue per respondent. In the illustrative table below, revenue peaks at $15.00, and with a unit cost of $8 profit peaks at $20.00.
Waiting for your data
Enter one price per line with the percentage who would buy at it, or try the illustrative sample.
How does the Gabor-Granger calculator work?
In a Gabor-Granger study each respondent is shown a price and asked whether they would buy at it, then is shown other prices. The share who say yes at each price is the demand at that price. Enter those shares (see the survey question bank for the usual question) and the calculator does the rest:
revenue per respondent = price × share who would buyprofit per respondent = (price − unit cost) × share who would buy
The revenue-maximising price is the tested price with the highest revenue per respondent; the profit-maximising price is the tested price with the highest profit per respondent. Only the prices you enter are compared: nothing is estimated between them, so the true best price may lie between two tested prices or beyond the ends. The calculator warns you when the best price is the lowest or highest one you tested.
When demand falls as price rises, a positive unit cost never moves the profit-maximising price below the revenue-maximising price: each sale lost to a higher price costs the margin on it, and a higher price raises that margin.
What is a worked example?
Six prices were tested and the share who said they would buy at each is below (invented numbers for illustration). The unit cost is $8.
| Price | Would buy | Revenue per respondent | Profit per respondent (cost $8) |
|---|---|---|---|
| $5.00 | 82% | $4.10 | −$2.46 |
| $10.00 | 64% | $6.40 | $1.28 |
| $15.00 | 45% | $6.75 | $3.15 |
| $20.00 | 28% | $5.60 | $3.36 |
| $25.00 | 14% | $3.50 | $2.38 |
| $30.00 | 6% | $1.80 | $1.32 |
Revenue per respondent at $15 is 15 × 0.45 = 6.75, higher than at $10 (6.40) or $20 (5.60), so $15 maximises revenue. With the $8 cost, profit at $20 is (20 − 8) × 0.28 = 3.36, higher than at $15 (7 × 0.45 = 3.15) or $25 (17 × 0.14 = 2.38), so $20 maximises profit. A higher price sells to fewer people but earns more on each.
What does a result look like?
This result was produced by loading the illustrative sample into the calculator above. The data are invented for the demonstration and are not real survey results.
Gabor-Granger demand analysis
$15.00 revenue-maximising price
Profit-maximising price: $20.00 (unit cost $8.00)
- Revenue-maximising price
- $15.00: 45.0% would buy, revenue $6.75 per respondent
- Unit cost
- $8.00
- Profit-maximising price
- $20.00: 28.0% would buy, profit $3.36 per respondent
- Prices tested
- 6, from $5.00 to $30.00
- Share who would buy
- Revenue per respondent
- Profit per respondent
- 1Revenue-maximising price, $15.00
- 2Profit-maximising price, $20.00
| Price | Would buy | Revenue per respondent | Profit per respondent |
|---|---|---|---|
| $5.00 | 82.0% | $4.10 | −$2.46 |
| $10.00 | 64.0% | $6.40 | $1.28 |
| $15.00 | 45.0% | $6.75 | $3.15 |
| $20.00 | 28.0% | $5.60 | $3.36 |
| $25.00 | 14.0% | $3.50 | $2.38 |
| $30.00 | 6.0% | $1.80 | $1.32 |
Workingrevenue per respondent = price × share who would buyprofit per respondent = (price − unit cost) × share who would buyOnly the prices you entered are compared; nothing is estimated between them
How to read this
Stated purchase intent overstates what people actually do: not everyone who says they would buy at a price will buy. Read the shares as a ranking of prices, not as forecasts of sales, and test before relying on them.
The best price is the best of the prices you tested. The true optimum may lie between them or beyond them, and costs other than the unit cost, competitors and how the price is presented all change the answer.
When should you not use this calculator?
Take the results as a guide to compare prices, not as a forecast. Do not rely on them alone when:
- You would treat stated intent as sales. People overstate what they will buy. The share saying yes at a price is not the share who will buy it, and the gap varies by product and person. Test before relying on it.
- The price order could sway answers. Showing prices in one fixed order lets the first price anchor later answers. Vary the starting price or the order across respondents.
- The best price is at the edge. If the best price is the lowest or highest you tested, you have not found the peak. Test beyond it.
- Competitors and context matter. The method asks about one product in isolation. It does not know what rivals charge or what buyers compare it with.
- Costs go beyond the unit cost. The profit price counts only the unit cost you enter. Fixed costs, discounts and channel fees are not included.
- The shares are estimates. Each share is a percentage from a sample and carries a margin of error; see the margin of error calculator. Two nearby prices may be indistinguishable.
- Demand rises with price in your data. A demand curve normally falls as price rises. If it does not, check the data, because small samples and noise can produce bumps.
Frequently asked questions
What is the Gabor-Granger method?
It is a survey method for measuring demand at different prices. Respondents are asked whether they would buy a product at a price, and the share saying yes at each price traces a demand curve. It is named after the economists André Gabor and Clive Granger, who studied how consumers think about price limits.
How is it different from Van Westendorp?
Gabor-Granger shows respondents prices and records whether they would buy, which gives a demand curve and lets you compare revenue or profit across prices. Van Westendorp asks respondents to name their own price thresholds, which gives a range of acceptable prices but no demand curve. See the Van Westendorp calculator.
Why can the profit-maximising price differ from the revenue-maximising price?
Revenue ignores cost. When each unit costs something, a higher price earns more on each sale, so the best profit price is at or above the best revenue price when demand falls as price rises. With a unit cost of zero the two are the same.
How many prices should I test?
Enough to show where demand falls away, spread over a plausible range. The calculator needs at least 2, and each price may appear once. Include prices below and above the one you expect to be best, so the best price is not at an edge.
Does the calculator work with percentages or counts?
Percentages. Enter the percentage of respondents who would buy at each price. If you have counts, divide the number who said yes by the number asked.
Is the sample data real?
No. It is invented for this page to show what a result looks like, and it is flagged as illustrative wherever it appears.
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Formulas and references
The standard sources behind the formulas on this page:
- Gabor, A. and Granger, C. W. J. (1966). Price as an indicator of quality: Report on an enquiry. Economica, 33(129), 43-70. doi:10.2307/2552272 checked October 5, 2026
- Jamieson, L. F. and Bass, F. M. (1989). Adjusting stated intention measures to predict trial purchase of new products: A comparison of models and methods. Journal of Marketing Research, 26(3), 336-345. On how stated intent differs from purchase. checked October 5, 2026
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