Gabor-Granger Pricing Method
Directly ask customers 'Would you buy at this price?' to build a robust demand curve and find your revenue-maximizing price point.
Survey Configuration
Enter parameters and run simulation to view demand curves
Analyzing the Demand Curve
The goal is to find the peak of the blue 'Total Revenue' curve, not necessarily the highest 'Buy Probability'.
Revenue Optimization
The highest point on the blue shaded area is your revenue-maximizing price. Pricing higher than this loses too much volume; pricing lower leaves money on the table.
Elasticity Zones
Steep drops in the pink line (Buy Probability) indicate high sensitivity. Flat sections indicate customers don't care about small price changes in that range.
The Drop-off Cliff
Look for the price point where the pink line crashes (e.g., crossing $100). This is a psychological barrier you should stay under.
Execution Steps
Define your price range (Min and Max) and the step intervals ($10, $50, $90...).
Set your sample size (number of survey respondents).
Click 'Run Simulation' to generate a demand curve based on typical market elasticity.
Analyze the 'Optimal Price' where Revenue peaks, even if purchase probability drops.
Pro Strategy
- Gabor-Granger works best for established products where customers have a reference price.
- For completely new innovations, use Van Westendorp instead.
- The 'Optimal Price' shown here assumes zero marginal cost. Use the Margin Calculator to factor in COGS.
Core Concepts
Willingness to Pay (WTP)
The maximum price at which a consumer will definitely buy one unit of a product.
The Revenue Paradox
Often, your best price is NOT the one that converts the most users. It is the one that balances volume with margin.
Price Thresholds
Specific price points (e.g., $49 vs $50) where demand drops disproportionately due to psychological barriers.
What is Gabor-Granger Pricing Method?
The Gabor-Granger method is a pricing research technique used to determine the price elasticity of products and services. It involves asking potential customers the likelihood of their purchasing a product at different price points.
Best For
- • Optimizing the price of an existing product.
- • Determining the revenue-maximizing price point for a new launch with established competitors.
- • Measuring price elasticity to forecast sales drops if you raise prices.
Limitations
- • Respondents may overstate willingness to pay (Hypothetical Bias).
- • Does not account for competitive offers shown side-by-side.
- • Assumes the product features are fixed (doesn't trade off features vs price).
Alternative Methods
Van Westendorp
Better for finding psychological price ranges/thresholds.
Conjoint Analysis
Better for trading off features against price.
Monadic Testing
Showing only one price to each respondent (A/B testing) to avoid bias.
Industry Applications
See how this methodology generates real revenue uplift in different sectors.
SaaS Enterprise Tier Repricing
Company wanted to raise enterprise seat price from $49 to $79 but feared churn.
Conducted Gabor-Granger survey with 300 current admins.
Consumer Electronics Launch
Launching a new noise-canceling headphone. Competitors were $300.
Surveyed 1,000 audiophiles.
Digital Subscription Service
Newspaper wanted to introduce a paywall.
Tested price points from $5/mo to $25/mo.