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:
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.
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.
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):
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:
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.
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:
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.
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.
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.