When the leaves start to change colors in autumn, they signal to fashion-minded shoppers to begin their search for the perfect new fall coat. But for some buyers, price trumps being the first to wear this year’s trends; and it is these consumers who ultimately wait, before parting with their cash, for retailers to slash prices. Retailers, of course, for their part want as many shoppers as possible to make their purchases before prices are decreased.
When it comes to buying and selling goods with a limited life cycle—such as fashion apparel, concert tickets, and holiday merchandise—shoppers and retailers face different dilemmas. Shoppers must decide whether to buy early in the season at a higher price or later in the season after a markdown. Buying later poses a trade-off because while the product will be cheaper, shoppers will have less time to use it. Meanwhile, sellers must decide how much to order, how to get the shoppers to buy at higher prices, and when and by how much to mark products down.
Lakshman Krishnamurthi, a professor of marketing at the Kellogg School of Management, sought to better understand these dual dilemmas by studying actual sales data from a national specialty apparel retailer. Krishnamurthi, along with his student Gonca Soysal, now a professor at the University of Texas at Dallas, gained some key insights by analyzing two years’ worth of data on the sales and inventory levels of hundreds of products, such as coats.
They designed a structural model that accounts for a shopper’s expectations and buying behavior based on patterns that emerged from the data. Their model assumes that consumers know the current prices of products, and have a sense of the stocking levels, letting them form expectations about future prices and availability.