Products Cannibalization and Synergy Estimation via MaxDiff Data

• Activity Number: 180
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Marketing
• Author(s): Stan S. Lipovetsky and Michael W. Conklin*+
• Companies: GfK and GfK
• Keywords: MaxDiff ; conditional choice probability ; product cannibalization and synergy ; Shapley value ; key driver analysis

Abstract

Maximum Difference (MaxDiff) modeling is widely used for finding probabilities of choice among multiple items. We apply data and results of MaxDiff to solving another problem - of finding the products cannibalization and synergy. For each product we estimate its probability to be chosen as the best one within all the data, and also conditionally to each other product's presence or absence. For a given product, each other one behaves as a catalyzer or inhibitor of choice of the product in consideration. Constructing the entire matrix of such relations for all the products, we compare its symmetrical elements for each pair of products. This shows which of the pairs of products are mutually synergic, or complementary, so their chances to be chosen as the best ones are higher in the presence of each other. In other cases, the products can be of negative impact of one onto another, so one is a cannibalizer of another; or both products suppress each other. Various estimations on a real marketing data are considered, including the relative risk, t-statistics, and Shapley value for key driver analysis. Synergy relations among the products can also solve the bundle optimization problem for subsets of the products.