UPCOMING WEBINAR: Run Research Your Way With AI Skills 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). In Displayr, it is plotted using the Visualization > Exotic > Price Sensitivity Meter feature, which plots the 4 different lines for the different price points: Too cheap, Cheap, Expensive, and Too expensive.
If additional questions about purchasing intent at the cheap and expensive prices are also provided, then the Newton-Miller-Smith (NMS) extension is used to examine how pricing affects demand and revenue:
Requirements
A dataset that has numeric responses to these or similar questions:
- At what price would you consider this PRODUCT/BRAND to be so inexpensive that you would have doubts about its quality? [“Very cheap”]?
- What price would you still feel this PRODUCT/BRAND was inexpensive yet have no doubts as to its quality? [“Cheap”]?
- At what price would you begin to feel this PRODUCT/BRAND is expensive but still worth buying because of its quality? [“Expensive”]?
- 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”]?
Note: The responses can overlap for the questions, such as answering the price for "Very cheap" and "Cheap".
Method
1. From the toolbar or from the right-click menu in the Report tree, click Visualization > Exotic > Price Sensitivity Meter.
2. In Properties , go to Data > Data Source.
3. For Price considered 'Too cheap' - select the corresponding numeric variable.
4. For Price considered 'Cheap' - select the corresponding numeric variable.
5. For Price considered 'Expensive' - select the corresponding numeric variable.
6. For Price considered 'Too Expensive' - select the corresponding numeric variable.
Note: if fewer than 4 of these variables are provided, only the intersections of the variables provided will be shown.
7. By default, the Remove inconsistent prices box has been ticked to remove observations where prices are not supplied in increasing order. Note that responses where adjacent price points have identical values (e.g., the respondent gave the same answer for Expensive and Too expensive) are not removed.
8. To display the Van Westendorp plot, Data > Output > Show should be set to Attitude of respondents. If you instead wish to look at how pricing affects demand and revenue, you can select Likelihood to buy, Revenue, or Likelihood to buy and Revenue.
The following options are required when using the latter settings:
9. For Likelihood of buying at 'cheap' price - select the corresponding numeric variable.
10. For Likelihood of buying at 'expensive' price - select the corresponding numeric variable.
11. Enter the Likelihood scale that maps to the probability of buying the product. The number of values in the list should match the likelihood scores in the data input. That is, if the likelihood to buy is given as a score from 1 to 7, then the likelihood scale should consist of a list of 7 comma-separated values which map each of these scores to a probability.
Optional Method:
1. Create a table of raw values as below (Note: Column names must match exactly):
2. From the toolbar, click Visualization > Exotic > Price Sensitivity Meter.
3. In Properties , go to Data > Data Source.
4. In Data, select the table created above.
Next
How to Extract Data Points from a Price Sensitivity Meter (Van Westendorp Plot)