User generated content in the form of customer reviews, blogs or tweets is an emerging and rich source of data for marketers. Topic models have been successfully applied to such data, demonstrating that empirical text analysis benefits greatly from a latent variable approach which summarizes...

We examine the nature of best-worst data for modeling consumer preferences and predicting their choices. We show that, contrary to the assumption of widely used models, the best and worst responses do not originate from the same data-generating process. We propose a sequential evaluation model...

Distributional assumptions for random utility models play an important role in relating observed product attributes to choice probabilities. Choice probabilities derived with independent errors have the IIA property, which often does not match consumer behavior and leads to inaccurate source of...

A common theme in the marketing literature is the acquisition and retention of customers as they trade-up from inexpensive, introductory offerings to those of higher quality. Standard models of choice, however, apply to narrowly defined categories for which assumptions of...

The identification of optimal product and package designs is challenged when attributes and their levels interact. Firms recognize this by testing trial products and designs prior to launch where the effects of interactions are revealed. A difficulty in conducting analysis for product design is...

Conjoint analysis is a survey-based method used to measure consumer preferences and predict demand for products that may not yet exist in the marketplace. The most frequently used form of conjoint analysis involves having respondents choose from among a relatively small set of offerings with...