1. A conjoint analysis method, comprising: (a) presenting a set of hypothetical products to a potential consumer, wherein each of the hypothetical products comprises N hypothetical features, and each of the N hypothetical features has at least two levels; (b) instructing the consumer to perform any task that is designed to elicit from the consumer information pertaining to the consumer's preference for each of the hypothetical products, whereby, as a result of the consumer performing the task, an observation for each hypothetical product is obtained, wherein each observation includes at least one data point that reflects the user's preference for the hypothetical product corresponding to the observation; (c) selecting a subset of the observations to use as a training sample; (d) selecting a subset of the observations to use as a rule selection sample; (e) forming one or more TABS using each observation included in the training sample; (f) selecting a rule from a set of rules; (g) selecting an observation from the rule selection sample; (h) predicting the consumer's preference for the hypothetical product corresponding to the observation selected from the rule selection sample using the one or more TABs, the selected rule, and the N hypothetical features of said hypothetical product for which the prediction is being made; and (i) determining the accuracy of the prediction by comparing the prediction to the observation selected from the rule selection sample.