This paper suggests a procedure which analytically ties a model to predict users’ predispositions to purchase different “brands” in a product-market together with a search process to identify optimal new product ideas. Brands, conceptualized as attribute bundles, are located in a prespecified attribute space. The painwise preference judgments of each individual in a representative sample drawn from the population of users are analyzed using the authors’ LINMAP procedure (LINear programming techniques for Multidimensional Analysis of Preferences) to determine his ideal point and salience weights for the attributes of the space. A distance model of choice is postulated for each user and used to predict his probability of choosing nonexisting products. The models developed for each user are tied to methods for searching the product space to find “best” locations for new products. The proposed procedures are discussed and evaluated in the light of relevant conceptual and empirical research. The paper concludes with a discussion of additional applications of the behavioral framework of LINMAP to other marketing decision areas.