Gabor Granger Pricing Method: Guide and Examples

Overview: Gabor Granger is a survey-based pricing technique used to identify the highest price customers are willing to pay for a product or service. Respondents are shown a series of price points and asked if they would purchase at each. The results generate a demand curve and measure price elasticity, enabling businesses to identify the revenue-maximizing price.

Getting Started: Launch a Gabor Granger pricing survey in seconds with this template. Analyze responses instantly to identify key price points. Consulting services are available to help optimize your study and gather additional feedback for your project or service.

Below is an example of a Gabor Granger question as it would appear in a survey. Price points are listed on the left, and respondents select their answer using buttons on the right. This layout makes it simple to evaluate each price point one at a time and ensures clean, consistent data collection.

A Gabor Granger question will first display a random price. If a respondent clicks “No,” a lower price is shown. If the respondent instead clicks “Yes,” then the system will show a higher price. This process repeats until the largest purchase point is identified. To illustrate the concept, here is a full example:

1. The initial price is $50; the respondent marks “Yes”
2. $100 is shown, respondent marks “No”
3. $90 is shown, respondent marks “Yes” – The question is now complete, $90 is the highest price point.

Here is another example for a respondent who will only purchase the product at a low price:

1. The initial price is $50; the respondent marks “No”
2. $20 is shown, respondent marks “Yes”
3. $30 is shown, respondent marks “No” - The question is complete, and $20 is the highest price point.

The SurveyKing platform uses random sequencing to display prices. Some systems use sequential pricing. For example, with the sequential pricing, if a respondent is first shown $50 the next set of prices would be $60, $70, $80 etc. Random sequencing increases the variability of prices shown to respondents, which helps improve the validity of your data.

To create a Gabor Granger survey, add a Gabor Granger question to your survey where appropriate. You can add optional display text for each price point you include, which helps specify the purchase type (e.g., per month, per box, per movie). You can also customize the wording of the "Yes" and "No" buttons to match your brand's voice or the context of your survey.

We recommend limiting your survey to no more than 20 price points. Too many options can lead to respondent fatigue and unreliable data. Price points should also be realistic and closely spaced. Extreme ranges, such as $5 to $500 for a monthly streaming service, for example, will not yield valuable insights.

To produce statistically meaningful results, aim for at least 100 total responses. If you plan to segment your data, for instance, by gender, you should collect at least 100 responses per segment.

Additional features can be enabled, including the ability to reset the display order of prices, which helps reduce bias. The question can also be configured to be required, ensuring each respondent evaluates all applicable price points and allowing for the accurate calculation of the highest price they'd be willing to pay.

You can also add supporting questions to a Gabor-Granger survey, such as multiple-choice or rating scales, to collect supplemental data alongside price sensitivity. For instance, a rating scale on purchase likelihood, brand trust, or feature importance can help explain why specific price points are more effective than others. This context is valuable because while the Gabor Granger method identifies willingness to pay, supplemental questions reveal the customer attitudes and motivations that drive those choices.

• Streaming Service Example - If we updated our streaming service to include unlimited movies, would you purchase at the following price points?
• Software / SaaS Example - If this software included advanced analytics and 24/7 support, would you consider subscribing at the following monthly prices?
• Food & Beverage Example - If this new organic energy drink were available in stores near you, would you purchase it at the following prices?
• Retail / Apparel Example - If this jacket were available in your preferred style and size, would you purchase it at the following price points?
• Training / Education Example - If this online course provided certification upon completion, would you enroll at the following prices?

Gabor Granger is primarily used in pricing research to answer these three questions:

1. Can the price of a product be increased without affecting sales (demand)
2. At what price point does the demand start to decline drastically
3. What is the price that results in the largest expected revenue

Gabor Granger is ideal for pricing studies that fit into these categories:

1. You have an established product and need to optimize for a proposed price increase.
2. You're an established company looking to update an existing product and are researching a new price on the improved product.
3. The product being researched is priced under $25. At this price, Van Westendorp becomes too cumbersome for respondents.

An entertainment company could use the above Gabor Granger example to determine how an update to their streaming service would impact demand and revenue. As the price increases, demand will fall. The price at which demand will drastically fall will drive the cost-benefit analysis for the upgrade. The company also needs to find the price that will maximize revenue.

If the entertainment company asked for a suggested price using a simple input box, respondents would likely enter a low dollar figure, limiting the revenue potential. However, by forcing respondents to evaluate specific price points, the company can find the price elasticity, plot the demand curve, and find the price point to maximize revenue.

Gabor Granger is often used as part of a broader research project to optimize a product or service. A preliminary survey might use a MaxDiff question to identify the most valued features. After discovering that unlimited movies ranked highest, the entertainment company can then use Gabor Granger to determine the optimal price for the upgraded offering.

At SurveyKing, insights from Gabor Granger and other pricing models are frequently integrated into our fractional CRO (Chief Revenue Officer) consulting projects. These engagements extend beyond data collection to apply survey results directly to financial planning and revenue optimization. We help organizations model pricing scenarios, forecast adoption and profit impact, and evaluate potential new offerings before launch. By combining survey analytics with strategic revenue design, our CRO services turn research into actionable business growth.

Depending on the type of pricing research you’re conducting, the way you phrase your Gabor Granger question may vary. Below are some common Gabor Granger pricing question examples you can use or customize to fit your product or service.

• Generic - Would you purchase [product/service] at $[price]?
• SaaS - Would you purchase access to our premium analytics dashboard at $39/month?
• Streaming Service - Would you pay $15/month for unlimited streaming and offline downloads?
• E-commerce - Would you buy this personalized skincare bundle at $45?
• Fitness App- Would you subscribe for $10/month to access all workouts and meal plans?
• Online Course - Would you pay $149 for full lifetime access to this training program?

Gabor Granger and Van Westendorp are the most common methods to determine product prices. Generally, Van Westendorp is used for the new product offerings, and Gabor Granger is used for established products.

Gabor Granger is used to build a demand curve and find the revenue-maximizing price. Van Westendorp is typically used to get a range of acceptable prices or to answer the question, "What range prices will the market accept".

Each project has unique needs. Below are some scenarios where each pricing method could be used. This information also appears in the Van Westendorp help article.

• An online newspaper researching a monthly subscription - The price will likely be less than $20 a month, meaning Van Westendorp would be too cumbersome. Readers might be willing to pay $1 a month, meaning the “too cheap” curve in Van Westendorp would supply invalid data.
• An established real estate company exploring a rent increase - The company wonders if certain upgrades will justify a rent increase. Finding a new revenue-maximizing point and plotting the demand curve will help guide this decision.
• A newer but established SaaS company focused on smaller clients. Generally, SaaS products focused on smaller clients have prices that are less than $100 USD a month. A small range of prices means Van Westendorp could be too packaged together. Being established, the company should focus on maximizing revenue. The company can send separate Gabor Granger surveys to users in specific tier packages to maximize the revenue of each tier.

• An established clothing company looking for feedback on their prices. Van Westendorp’s "Too cheap would question the quality" price point is key here. Clothing is one area where perception matters. Too low of a price means brand reputation will suffer.
• An established SaaS company focused on large enterprise clients and offering a new product. Large organizations will shy away from products with too low of a cost because they fear the quality can adversely impact their day-to-day operations. The too cheap curve would help the company limit negative brand perception.
• A brand new SaaS company looking to understand the market dynamics. Too low of a price means the company won’t get enough exposure, and too low means people will question the quality. A Gabor granger study can be used down the road once the user base has grown and more features added.

Gabor Granger results show demand and revenue curves that highlight price elasticity and identify the revenue-maximizing price. In Gabor Granger analysis, plotting these curves is the key step for understanding how customers respond at different price points.

If a respondent selects “No” for the lowest price point, the system logs it as “Would not purchase”—a crucial data point that some platforms overlook. Including this ensures more accurate demand curves and pricing insights.

This curve is built by plotting the cumulative percentage of respondents who are willing to purchase at each price point. A sharp decline from one point to another means the price elasticity is very high. The lowest price point would consider respondents who would not purchase, meaning the lowest price will not always have a cumulative percentage of 100%.

The revenue curve maps expected revenue based on the number of respondents willing to purchase at each price point. Each point is calculated by taking the price point multiplied by the respondent's willingness to buy.

This is the price point that would result in the highest total revenue. For elastic products, demand will usually fall sharply after this point.

Price elastic measures how price changes will affect demand; the same concept is also used in economics. Elasticity can be grouped into three categories:

• Elastic demand - Elasticity greater than 1. A small change in price leads to a larger change in demand.
• Inelastic demand - Elasticity less than 1. Changes in price have a relatively small effect on demand.
• Unitary elasticity - Elasticity equal to 1. A change in price results in a proportional change in demand.

Price elasticity for any two price points can be calculated using the following formula. Price elasticity is always displayed as a positive number, meaning you take the absolute value of the below equation.

Price elasticity = % change in the quantity demanded / % change in the price

Below is the output of a mock survey using the streaming service sample question. This Excel file contains all the respondent data and calculations for various metrics so you can follow along. This mock study had 20 responses.

On the "Output Tables" tab of the Excel file, column C has the cumulative percentage of respondents willing to purchase at each point. You'll notice the formulas take into account the one response that would not buy at any point. Finally, column D of the Excel file lists the expected revenue of each price point. In this mock study, the $40 price point results in the highest revenue, meaning $40 is the revenue-maximizing price.

The results will also include a summary table with all price points in ascending order. The table includes:

• Respondent counts at each price point.
• Total cumulative demand.
• Cumulative demand percentages.
• Expected revenue.
• The price elasticity for each price point (starting with the second-lowest point).

Specific projects require analyzing the Gabor Granger output for two different categories, such as gender. Unique to SurveyKing is the ability to create a Gabor Granger segment report. Be sure that your survey includes a multiple-choice question to capture the categories you are studying. Ideally, you would include this question before the Gabor Granger question. The segment report will generate separate price curves and summary tables for each category.