A multidimensional clustering on Fuzzy metrics to classify CPG pricing and price promotion strategies: the case of pasta in Italy

Abstract

While retailers compete along many dimensions, pricing strategy is clearly one of the most important drivers to increase sales especially in the field of Consumer Packaged Goods (CPG). Previous studies reveal that the classification of pricing and price promotion strategies has a complexity that may not be reduced to a binary choice between high reliance on price promotions (HiLo) and every-day-low-price (EDLP) approach. This paper suggests a fuzzy and multidimensional framework for analyzing price promotion strategies in the CPG market over time and geographical areas. A dataset of weekly prices and price promotions for pasta brands across different retailers and geographical areas in Italy has been used. Retailers’ promotion strategies are classified according to five dimensions: price level, price variability, price promotion frequency, price promotion intensity and price promotion variability. Membership functions have been designed to transform those metrics into fuzzy measures. We obtained nine groups which identify different pricing and price promotion strategies and described their distribution across brands, retailers and geographical areas.