Gabor Granger Pricing Model Explanation, Survey Template

Gabor Granger is a survey-based research technique used to determine the optimal price for a product or service. A Gabor Granger question asks respondents to evaluate a series of pre-defined price points. The results are used to build a demand curve and determine the revenue-maximizing price point.

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 has all price points 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 part of a more significant research project to build optimal products or services. A preliminary survey for a product study might use a MaxDiff question question to determine which product features are most valuable. The entertainment company in this example could have done preliminary research and found their customers valued unlimited movies the most. Gabor granger is then used to price the updated product.

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 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.

To create a Gabor Granger survey, create a survey and add the Gabor granger question where you want. Each price point you add has an additional input to include extra display text. This extra text is useful to add the current type of the purchase type (gg monthly, per box, per movie etc). You can also edit the wording of the "Yes" and "No" buttons.

We recommend adding no more than 20 price levels. Anything over 20 levels requires more focus from respondents, leading to poor quality data. Price points should be close enough to avoid low-quality data. For example, a streaming service would never need a price range of $5 to $500 per month.

A Gabor Granger should collect at least one hundred (100) responses to obtain meaningful results. If you wanted to segment your data, for example, by gender, you would want to collect at least one hundred (100) responses for both males and females.

An option to reset the display prices is also available for the Gabor Granger question. When a Gabor Granger question is marked as required, the respondent must evaluate all applicable choices. This ensures the highest acceptable price point can be calculated, which marks the question as complete.

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.

The output of a Gabor Granger involves plotting demand and revenue curves. These curves help visualize the price elasticity at each point. The results also include the revenue-maximizing price point and the price elasticity values.

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 of less than 1 is referred to as "inelastic demand," meaning the price had a minimal effect on the demand.
• Inelastic demand - Elasticity of less than 1 is referred to as "inelastic demand" meaning the price had had minimal effect on the demand.
• Unitary elasticity - Elasticity equal to 1. A change in price results in the same 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 takes into account the one responses that would not buy at any point. Finally, column D of the Excel file lists the excepted 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 elastic 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.