Gabor-Granger Pricing Method

The Gabor-Granger pricing method determines the price elasticity of products and services. Developed by two economists, André Gabor and Clive Granger, it has been used since the 1960s. It is particularly useful when:

  • You want to get a directionally correct estimate for willingness to pay for the product.
  • You want to find revenue-optimising price points.
  • All the other components (or attributes) of the product or service are fixed and cannot be changed.
  • You only want to look at your brand or SKU without considering competition.

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Outputs


Price elasticity chart

The price elasticity of demand curve shows customers' willingness to pay for your product at different price points. The steeper the demand curve, the more price-sensitive customers are in relation to your product.


Revenue vs. price chart

The “revenue vs. price” curve helps identify revenue-maximising price points.

For example, this chart below suggests that the revenue-maximising price is around $24.

Flow of Gabor-Granger questions

Each respondent is given a series of almost identical questions such as “Would you buy product X at price Y?”. In each of the several questions, the price shown to a respondent is different: it is adapted based on the respondent's previous answer with the aim to find the maximum price each respondent is willing to pay for a product.

In this example, we have price points from $50 to $170 (incremented by $10):

  1. Respondents are randomly assigned to one price.
  2. If they are willing to pay that price, they are offered a higher (randomly chosen) price.
  3. If they are not willing to pay that price, they are offered a lower (randomly chosen) price.
  4. The algorithm repeats until we find the highest price each respondent is willing to pay.

Flow of Gabor-Granger questions

How it works

You need to specify several price levels (ideally, between 5 and 15 price levels). For example: $10, $20, $30, $40, $50, $60.

Technically speaking, Gabor-Granger is a type of a randomised sequential monadic test where respondents are sequentially given one option at a time in which they will make a decision upon.

When you need to examine product attributes other than price (e.g., design, quality, power) or you also need to look at competitive brands, it would be more appropriate to use conjoint analysis, where price and brand are only two of the attributes among many. Conjoint studies can also provide more precise estimates for total willingness to pay and are less prone to understating the acceptable price by research participants.

There are two biases in the Gabor-Granger methodology which mostly offset each other:

  • Understatement of willingness to pay: Where a price is shown explicitly, respondents can reckon that the purpose of the study is to set a price. They may be tempted to understate their willingness to pay to “game” the company into offering lower prices.
  • Overstatement of purchase intention: While respondents may state a willingness to purchase a product in a survey, real-life purchase decisions will often be swayed by many other factors and will result in a lower level of buying than reported in the test.

On Conjoint.ly, you can add as many Gabor-Granger exercises in a single experiment as you need (to test different products). Gabor-Granger can be used as a separate experiment or an additional question added to conjoint, Van Westendorp (which can supplement the Gabor-Granger with a different take on pricing), or another experiment type. In some cases, a Gabor-Granger exercise is added after conjoint to measure preice sensitivity of extras and paid add-ons to the main product, which composition is optimised through conjoint analysis.

Application in selection of subscription model and pricing

Subscription-based companies often face the problem of choosing not only the price point (i.e. the amount per unit of service), but also business model for their products (i.e. what unit should they charge per?). For example, a video streaming business can charge in a couple of different ways:

  • Fixed amount per month
  • Price per video played

This is a complex decision that involves consideration of recurrence and churn, expected amounts of downloads, cost per download, and many other factors. Gabor-Granger can be used to assess initial adoption rates if one or the other model is offered. The set-up would involve two Gabor-Granger questions: One about the fixed amount per month, the other about price per video played.

Optimal pricing plan pay per video through Gabor-Granger: Question set-up

Optimal pricing plan monthly subscription through Gabor-Granger: Question set-up

By comparing the predicted revenue and profitability based on these two outputs, one can find an optimal pricing plan. You can download an example Excel model to see an example of pricing model selection based on various assumptions.

Optimal pricing plan pay per video: Gabor-Granger outputs

Optimal pricing plan monthly subscription: Gabor-Granger outputs

Choosing an optimal discount amount

Gabor-Granger can also be used to understand consumers' sensitivity to discounts. You can set this up by entering negative monetary amounts. This will reverse the order of the bargaining exercise so that if the respondent is will to buy at $250 discount, the next offer will a higher discount (such as $300).

The chart below shows a drop in number of consumers willing to buy a product when discount is lower than $225. The main output for this exercise would be the number of consumers willing to buy, rather than a revenue-maximising price point.

How much should I discount my product? Finding optimal discount amount using Gabor Granger: Set-up

How much should I discount my product? Finding optimal discount amount using Gabor-Granger: Output