Discrete choice experiments (DCEs) are a sampling technique used to collect data and derive demand curves for product attributes. Common in retail, they apply anywhere there are many distinct products at different prices — and they’re a powerful tool for revenue management and optimization.
What a DCE is
A DCE helps you understand how customers make choices and lets you test and optimize prices, packages, and bundles. It’s also called “stated preference,” because respondents state their preferences rather than having them inferred from behavior. It presents a set of hypothetical choices between products or services, each shown multiple times, with order varied so respondents can’t game it. You can run one on your own site or through an academic-grade platform like SurveyEngine.
The advantages
- Concrete scenarios — customers imagine themselves actually using your product under specific conditions, not answering abstract questions.
- More reliable — picturing a specific scenario yields more accurate data than general survey or focus-group questions.
- Fast and cheap — you can run one with as few as 10 customers, no weeks of recruiting.
Originally developed by economists to study consumer behavior through controlled experiments, DCEs can point toward the price that maximizes revenue and profit, within the limits of stated preference — letting you test scenarios quickly before making changes that affect your bottom line.
Stated preference vs. revealed preference
A DCE measures stated preference: what people say they would choose. Quibble applies the same discrete choice theory to revealed preference instead, estimating choice from what shoppers actually did, using searches that ended in a purchase (Bookable Search™). The method is a multinomial logit; the difference is the data. See How optimization models work.