Preference-rank translation is a mathematical technique used by marketers to convert stated preferences into purchase probabilities, that is, into an estimate of actual buying behaviour.
It takes survey data on consumers’ preferences and converts it into actual purchase probabilities.
A survey might ask a question using a ranking scale such as : A marketing researcher will re-specify the numerical values during codification.
Next, the researcher uses a data reduction technique like factor analysis to obtain aggregate scores.
To convert these aggregate rankings into purchase probabilities, each category (in this case, each product) will be weighted with a translation coefficient.