The price sensitivity meter is a set of survey questions that are used to work out how to set prices for products. It does so based on a concept of what price most people regard as being reasonable (as opposed to what price will maximize profits, which is the framework more commonly used when setting prices).

The price sensitivity meter questions

The price sensitivity meter (PSM) typically asks four questions:

  1. At what price would you consider this PRODUCT/BRAND to be so inexpensive that you would have doubts about its quality? [“Very cheap”]?
  2. What price would you still feel this PRODUCT/BRAND was inexpensive yet have no doubts as to its quality? [“Cheap”]?
  3. At what price would you begin to feel this PRODUCT/BRAND is expensive but still worth buying because of its quality? [“Expensive”]?
  4. And, at what price would you feel that the PRODUCT/BRAND is so expensive that regardless of its quality it is not worth buying? [“Very expensive”]?

Worked example

The following table shows data from a sample of 26 respondents asked to evaluate a brand of chewing gum.

Price Sensitivity Meter table

Interpreting a price sensitivity meter

There are many different approaches to interpreting PSM data. The classic approach is shown in the price sensitivity meter plot, below. The horizontal axis shows prices in the range of $0.00 to $8.00. This is the range of prices given by respondents when answering the four questions.

Reading from left to right, the first series plotted is the Less than “Very cheap” series (Q1. from the PSM). This shows the proportion of the sample to nominate that price or lower as being Very Cheap. As no respondents gave a Very cheap answer of less than $0, for $0 the line is at 0%. One of the respondents (4%) gave an answer less than 10 cents, 8% gave an answer less than 20 cents, and so on.  All the samples nominated Very cheap prices of less than or equal to $2.10. The Less than “Cheap” curve is computed in the same way.

The More than “Expensive” curve, by contrast, shows the proportion of the sample that gave equal or higher answers. 100% of the sample indicated that their idea of Expensive was above $0, whereas 54% nominated a price greater than or equal to $2.00, and so on.

Price Sensitivity Meter

Pros and cons of price sensitivity meters

The traditional interpretation of PSM data is concerned with where the different curves intersect. In our example above, we can see four such points. If the price selected is between our Point of Marginal Cheapness ($1.10) and Optimum Price Point ($1.50), people will interpret the products as being good value for money. A price between $1.50 and the Indifference Price Point ($2.00) will be seen as expensive, causing some sticker shock. Prices between $2.00 and $2.10 will be seen as premium while anything above that will be viewed as poor value for money. Thus, the price of gum should be in the range of $1.10 and $2.10, according to this price sensitivity meter.

Someone experienced with the pricing of confectionery might quickly come to the conclusion that the PSM has limited value. The PSM traditionally offers a large range of possible prices, making it too broad and non-specific to help with pricing. Therefore, most researchers do not use this "classical" approach, instead choosing to use the data from the PSM to construct demand curves.

One approach to creating demand curves from PSM data is to treat the “Expensive” or “Very expensive” data as if it were stated willingness to pay (WTP) data (i.e., assuming that people will buy at prices less than these amounts).

The main benefit of the price sensitivity meter is its simplicity. There is no evidence to suggest that it is as accurate as more sophisticated methods such as conjoint and choice modeling.


We've implemented an entirely automated approach to analyzing price sensitivity meter data in Displayr and Q:

  • In Q: Insert > Marketing > Price Sensitivity Meter
  • in Displayr: Insert > More > Marketing > Price Sensitivity Meter

An example of the output is shown below. Note that this is back-to-front relative to the example above. This changes nothing of the interpretation, but tends to be a bit easier on the brain.

Find out more about market research terminology with our "What is" series and market research section on or blog!