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Gabor-Granger Pricing: How to Test Exact Price Points Before You Launch
Tuhin Bhuyan · 23 January 2026 · 7 min read
Van Westendorp gives you a safe range. Gabor-Granger helps you choose a specific price point inside that range by estimating demand and expected revenue at each tested price.
What Is Gabor-Granger Pricing?
Gabor-Granger is a pricing research method that measures purchase intent at specific prices.
Instead of asking for one "ideal" number, it asks people whether they would buy at a sequence of price points.
That gives you an estimated demand curve.
In plain terms: you test real candidate prices, then estimate how many people would buy at each one. Multiply expected demand by price, and you get a revenue comparison before shipping the change.
This is why teams often pair it with Van Westendorp. Van Westendorp finds the acceptable range. Gabor-Granger helps pick the exact point that best matches your business goal.
How the Method Works
The setup is simple. You present a product context, show a price, and ask whether the respondent would buy at that price. Then you repeat with other prices.
- Define the price ladder. Pick 5 to 8 realistic prices to test.
- Ask purchase intent consistently. Keep wording the same across prices.
- Collect enough responses. Aim for at least 100, and more if you plan to segment.
- Calculate acceptance per price. This is your demand estimate by price point.
If you segment by role, plan, or company size, you often find different optimal prices per segment. That can inform packaging or plan boundaries, not just one global number.
How to Read Gabor-Granger Results
Start with three views: acceptance rate by price, estimated demand curve, and estimated revenue by price. The "best" price depends on what you optimize for.
- Max conversion: choose a lower price where acceptance is highest.
- Max revenue: choose the peak of the revenue curve.
- Market entry: choose a lower-friction price to accelerate adoption.
- Positioning: choose a higher price if premium signal matters and demand supports it.
Don't treat one chart as final truth. Check confidence bands, segment behavior, and consistency with other signals like trial-to-paid conversion and churn.
When to Use It (and When Not To)
Use Gabor-Granger when you need to choose an exact price point from realistic options. It's especially useful before launch, before annual repricing, or when introducing a new tier.
Don't use it alone for positioning strategy. It tells you demand at tested prices, but it doesn't fully capture brand perception or competitive reactions.
Pair it with Van Westendorp when you need both a range and a point estimate.
Mistakes That Distort Your Pricing Data
- Testing unrealistic prices. If prices are disconnected from market reality, outputs are unusable.
- Weak product context. If respondents don't understand value, intent answers are noisy.
- Small samples. Tiny datasets make curves unstable and over-sensitive to outliers.
- No segmentation. A blended average can hide a high-value segment willing to pay more.
How to Run a Gabor-Granger Study
You can run Gabor-Granger with spreadsheets, but analysis gets messy quickly when you add segments and multiple tested prices. That's where teams lose time and confidence.
SenseFolks PricePoint supports Gabor-Granger and Van Westendorp in one flow. You set up the survey, embed it where pricing intent is highest, and review demand and pricing outputs on your insights dashboard.
- Add your website to SenseFolks.
- Create a PricePoint survey and choose Gabor-Granger.
- Set your candidate price ladder based on realistic market bounds.
- Embed the survey on pricing and upgrade moments.
- Compare demand and revenue outputs and choose your target price.
References
- Gabor, A., & Granger, C. W. J. (1966) . Price as an Indicator of Quality. Foundational work for direct purchase-intent pricing research.
- Van Westendorp, P. H. (1976) . Price Sensitivity Meter method, often paired with Gabor-Granger for practical pricing decisions.
Choose prices with demand data
Run a PricePoint survey and compare expected demand across tested price points.