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Home CX Consumer Insights

Pricing Research with Monadic Price Testing

How much should I charge for my product or service? This question has a direct impact on your bottom line and ability to stay in business. There are several survey-based methods for testing the market’s perception of price. Monadic price testing is one such method. Other popular pricing research methods include the Van Westendorp Price Sensitivity Meter, and its variants.

In monadic price testing, the respondent sees one price and is asked to state his or her purchase intention at that price point. This design is accepted as being the purest means for measuring price sensitivity, as the respondent is not given the opportunity to re-think their decision.

With that said this design requires the ability to reach a large number of respondents. For every price point tested there should be 100+ responses. If you are testing 5 – 8 price points then this means 500 – 800 completes. If you are testing prices across key market segments, then those segments need to be considered as well.

As has been said many times before – randomness is next to godliness. The same applies with monadic price testing. In order to minimize the potential for bias participants should be randomly assigned to price groups.

This can be done manually. If your online survey platform does not support randomization, then you can divide your sample a priori into groups with each group exposed to one price. This will require multiple versions of your questionnaire each with its own link. If your survey tool supports randomization then one questionnaire version will suffice.

Your purchase intent question should be of standard format. For example: “At the price of research questions listed below how likely are you to purchase this product?” There are several options for scaling with 5, 7 or 9 point intention scales anchored by “Not at all likely” to “Extremely likely” being common. As the researcher you will need to decide what your cutoff point is for considering a respondent to be a likely purchaser. Top-two box (e.g. scores of 8 and 9 on the nine point scale) are often used as a proxy.

Price    T2 Box Percentage
$150    25%
$175    28%
$200    35%
$225    45%
$250    37%
$275    29%

The table above indicates the optimal perceived price is $225 with an acceptable range of $200 – $250. Either side of this range and the price may be thought to be too inexpensive or too expensive. If you are employing a segmentation scheme or comparing customers versus prospects then the distributions may vary across these groups.

Monadic price testing provides a relatively pure means for assessing price sensitivity. It is useful for scenarios where the features and benefits are fixed. Scenarios, where the researcher is looking to create an ideal product or service, will benefit from conjoint analysis.

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Greg Timpany
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