Abhijit Telang introduces the concept of conjoint analysis and shows how you can implement this in R:
We will need to typically transform the problem of utility modeling from its intangible, abstract form to something that is measurable. That is, we wish to assign a numeric value to the perceived utility by the consumer, and we want to measure that accurately and precisely (as much as possible).
This is where survey design comes in, where, as a market researcher, we must design inputs (in the form of questionnaires) to have respondents do the hard work of transforming their qualitative, habitual, perceptual opinions into simplified, summarized aggregate values which are expressed either as a numeric value or on a rank scale.
I tend to shy away from this kind of analysis because it runs a huge risk of trying to turn ordinal utility rankings into cardinal functions.