The Influence of Competitor Prices on Price Sensitivity: A Bayesian Pricing Strategy in E-Commerce

Pricing is a cornerstone in almost every business. Increased price pressure, due to better informed customers online, enhances the need for a sophisticated understanding of price effects. In this paper, we add to existing pricing literature by thoroughly studying effects of competitor prices on price sensitivity of customers in e-commerce. We test our hypothesis that price sensitivity increases as the price approaches the competitor median price. We employ a hierarchical Bayes model, which allows non-linear effects, to test our hypothesis. Furthermore, the model is used to forecast sales and we propose a pricing strategy, based on prices that are optimized by our model. We test the performance of our pricing strategy in a field experiment, implementing our prices in an e-commerce store. We find a high increase in price sensitivity if a product is the cheapest in the market and a linear increase in price sensitivity if the price relative to the market increases. Furthermore, we find that our model is not useful for forecasting and our field experiment results in a 10% sales growth for relatively cheap products, but a 14% decrease in sales for relatively expensive products.