On the benefit of developing customer profile analysis to implement personalized pricing in a supply chain

Abstract

Purpose – The advanced technology enables retailers to develop customer profile analysis (CPA) to implement personalized pricing. However, considering the efficiency of developing CPA, the benefit to different retailers of implementing more precise personalized pricing remains unclear. Thus, this essay aimed to investigate the impact of efficiency on participants’ strategies and profits in the supply chain. Design/methodology/approach – A two-stage game model was introduced in the presence of a manufacturer who sets his wholesale price and a retailer that decides her CPA strategy. The equilibrium results were generated by backward induction. Findings – Most retailers are willing to develop the highest CPA to implement perfect personalized pricing, but those inefficient retailers with high production costs would like to determine a middle CPA to implement bounded personalized pricing. The retailers’ profits may decrease with the efficiency of developing CPA when the efficiency is middle. In this case, as the efficiency improves, the manufacturer increases the wholesale price, resulting in lower demand and thus lower profits. Moreover, define a Pareto Improvement (PI) strategy as one that benefits both manufacturers and retailers. Therefore, uniform pricing is a PI when the unit cost is high and the efficiency is low; personalized pricing is a PI when the unit cost is low and the efficiency is low or high; otherwise, there is no PI. Originality/value – This study is the first that investigates how the retailer develops CPA to implement personalized pricing on a comprehensive spectrum, which can provide practical insights for retailers with different efficiencies.

Keywords

• Customer profile analysis (CPA)
• Pricing strategy
• Personalized pricing
• Uniform pricing
• Game theory