Find an optimal price for your product.
Select a survey tool and an audience sample of 50 people using a cross-section covering your audience’s most common demographics and preferences.
Recipients should represent your ideal customers as closely as possible. While you can ask questions manually, survey tools like Qualtrics and QuestionPro offer pre-built question sequences and reports for common analyses like Gabor-Granger.
Use your best judgment to start with the lowest possible price point and move in equal increments to the highest possible point. For example, you can start with your lowest possible price point as your per-unit product cost or the break even point for selling a single unit of your product.
The sentence should have enough details to allow your respondents to realistically estimate how much they might want to pay for it. For example, a description for a project management platform could be A new way to manage products for organizations between 10 and 50 employees that dynamically tracks resources spent on each project.
In your first question, ask how willing the reader would be to buy the product at a reasonable price point on a scale of 1-5, without defining the exact price point.
Define 1 as low, and 5 as high likelihood to buy for your audience. This question screens out any respondents who are not interested in the product regardless of price, and would skew the data.
Most major survey platforms, such as SurveyMonkey and Google Surveys, let you mark the first survey question as a screening question that removes irrelevant respondents. In the form settings of your survey platform, specify which answers would screen out recipients, automatically sending them to the final screen instead of letting them proceed through the rest of the survey questions.
This question will only appear for respondents who answered 3, 4, or 5 in the first question, since anyone who entered a 1 or 2 in the screening question has been eliminated from the survey pool.
Ask how likely the reader would be to buy at the point one level below your medium price, if they answered 1 or 2 to the medium price point.
You can set up conditional logic for follow-up questions in most survey tools. This ensures that only respondents who answered negatively to the medium price point will receive questions about price alternatives.
Ask how likely they would be to buy at the point one level above your medium price, if they answered 4 or 5 to the medium price point.
Use the same conditional logic you used for negative responses to only show this question if respondents answered positively to the medium price point.
Repeat the process using the same criteria on both sides until you’ve reached the minimum and maximum points on your scale.
Using conditional logic, you can climb up and down your pre-defined price points until you’ve reached both ends of the scale. At each price point, fewer respondents will answer positively or negatively and advance to the next question.
End the survey for anyone changing their response pattern as they climb up or down the scale. For example, someone responding with 5 or very likely to buy to the medium price point but with 1 or very unlikely to buy to the next-higher price point should not begin to receive lower price points again, but move to the end of the survey.
Analyze the results by plotting a demand equation to choose your optimal price point based on the best compromise between customers willing to pay, and a reasonable price that allows you to turn a profit on each product sale.
Plot a demand equation by mapping each price point on the x-axis and the percentage of customers willing to pay at that price point on the y-axis. Survey tools like Qualtrics and QuestionPro can plot this equation for you.