Conjoint Analysis: Willingness to Pay

Frequently asked for

We see a specific request for willingness to pay (WTP) in nearly every RFP related to conjoint analysis. Companies want to know how much they can charge if they include new or innovative features.

Unfortunately WTP is poorly defined.  Companies may want an understanding of how people are willing to part with for new features, but never do define exactly what that means. Because it is poorly defined it also poorly executed.

WTP redefined

In order for WTP to be useful to decision makers, it must be defined. Here's our unique definition:

"Willingness to Pay is defined as the change in the revenue optimizing price point when the feature is included. It is product, feature and scenario specific. It provides a dollar amount that could be optimally charged when the new feature is added. It carries with it the new Units, Revenue and Profit numbers for the product at the optimized price point."

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This new method can be very informative when the change in optimal price is plotted against the change in units. As in the image below.

You'll see that each feature has a difference in the optimal price point as well as the change in units at the new price point. Feature levels in the upper right will have the biggest impact on revenue (also marked by bubble size).

Willingness to Pay: Conjoint

Alternatively, it can also be useful top plot the value against the marginal cost for delivering the feature.

Compared to the old way

The old method, used in practice, wasn't as useful for decision makers.

The idea was to record the products share, change the feature, then adjust the price (up or down) until you get back to the original share number. The amount you had to change the price was then labeled the WTP for the feature. The problem is, that is not WTP - it is called an indifference price point.

Stick with the new method - it's much better.

Author - Jake Lee

Jake is the founder or Red Analytics. He has been working in Marketing Science and Advanced Analytics since 2005. His top interest is in using data/analytics to help managers make better decisions. He has primarily focused on custom market segmentation and discrete choice (conjoint analysis, choice-based conjoint) modeling. He frequently presents new ideas at the Advanced Research Technique Forum (ART) and the Sawtooth Software Conference. When not working, he likes grilling cheeseburgers in the backyard.