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).
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. Go to Visualization > Exotic > Price Sensitivity Meter
2. In the object inspector go to the Data Source tab.
3. For Price considered 'Too cheap' - select corresponding numeric variable
4. For Price considered 'Cheap' - select corresponding numeric variable
5. For Price considered 'Expensive' - select corresponding numeric variable
6. For Price considered 'Too Expensive' - select corresponding numeric variable
OPTIONAL METHOD:
1. Create a table of raw values as below (Note: Column names must match exactly)
2. Go to Visualization > Exotic > Price Sensitivity Meter
3. In the object inspector go to the Data Source tab.
4. In Output in 'Pages', select the table created above
Additional Details
Select the Remove inconsistent prices box 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.
Next
How to Use the Gabor-Granger Method in Displayr
Comments
0 comments
Article is closed for comments.