Should price cannibalization be avoided or embraced? A multi-method investigation

This paper proposes price cannibalization as a growth strategy despite prior findings that suggests avoiding it. We focus on a multiclass, capacity-constrained pricing problem in which each of the product classes has a price range. Specifically, we examine the effects of price range overlaps and introduce it as a revenue-maximizing pricing strategy. Price cannibalization happens when sales in some product classes decrease due to the existence of overlaps between the price ranges. We employ a multimethod approach. First, we define a Markov decision problem to obtain the revenue-maximizing strategy in a two-class sales scenario. We show that price range overlaps are part of the optimal strategy. Second, we collect multichannel data from a European storage company to examine how price range overlaps impact a customer's purchase decisions. The results show that the existence of price range overlaps leads to cannibalization, but increases spending and improves conversion. Finally, we use simulations to compare several pricing strategies and demonstrate the long-term effects of using price range overlaps in pricing algorithms in complex situations. Our findings suggest that using price range overlaps, though leads to cannibalization, actually helps companies avoid spoilage and early sellouts, leading to better capacity utilization and higher revenue.