Abstract:

In an earlier technical report1, we discussed product portfolio optimization. In that report, products were placed: a) In the absence of competition and existing brands, b) in the presence of competition, and c) in the presence of competition while minimizing cannibalization of existing brands. The last two cases involved optimizing the probability of first choice among multiple alternatives. The design of an optimum portfolio depends on the availability of certain information about the location of existing products (your own and your competitors') along with the location of individual ideal points. This information can be obtained from modeling liking data using a probabilistic, individual ideal point model called Landscape Segmentation Analysis (LSA). In this report, we discuss the application of LSA in a dynamic exercise involving two competitors with existing brands, and their efforts to optimally place new products on the market to maximize first choice.