Setting prices in a constantly changing environment is hard. Tuck professor Santiago Gallino designed and tested a methodology to make it easier.
When you consider the history of shopping, it’s probably true that consumers have never had it easier than they do today. Want to know if that food processor is any good? You can read hundreds of reviews from experts and regular folks alike. Need an item tomorrow that’s sitting in a warehouse across the country? Just choose overnight shipping on the checkout page. Of course, the convenience of online shopping has been good for retailers as well, since the Internet allows businesses to reach much larger audiences.
But one feature of the modern shopping landscape is more of a mixed blessing: effortless price comparisons. Consumers benefit enormously, because they can find the lowest price with a simple Google search. Gone are the days when people had to drive around, spending half a day looking for the best deal on a TV. At the same time, the ease of comparing prices has made retailing much more competitive, with businesses leapfrogging each other to offer the lowest prices, sometimes to their own detriment. It’s also harder for retailers to know how to price their wares, because the price is always changing online depending on inventory, demand, and competitors’ whims.
Tuck assistant professor Santiago Gallino studies retail operations management and he noticed that pricing has become particularly tricky with the advent of online shopping. Pricing methods vary considerably. Some retailers, such as Amazon, use incredibly sophisticated, sometimes even automated, systems to set prices. Others use simpler heuristics, such as tracking their main competitor’s prices, or letting their experience dictate how to respond to shifts in demand.
Stock-outs are really useful for pricing decisions, and they give a hint of the relevance of a competitor.
In a new working paper titled “Competition-Based Dynamic Pricing in Online Retailing: A Methodology Validated With Field Experiments,” Gallino and co-authors Marshall Fisher of Wharton and Jun Li of the Ross School of Business designed and tested a methodology that any retailer can use to set the optimal price for goods in a category. “What we did in this project was to use pieces of models that were out there to estimate price elasticity and consumer decisions,” Gallino explains, “and also bring in a novel way to account for the instances where retailers observe their competitors experiencing a stock-out.”
The occasion of a stock-out—when a retailer is “out of stock” for a particular item—is something that Gallino and his co-authors focused on because it’s a key piece of publicly available information. Retailers don’t know how many products their competitors sell, or their competitors’ profit margins, but by simply looking at their competitors’ websites they can see when an item is sold out or no longer available. “We find that stock-outs are really useful for pricing decisions, and they give a hint of the relevance of a competitor,” Gallino says. For example, if Target’s sales of baby bottles go up when Walmart is sold out of that item, it’s reasonable for Target to assume that it shares customers with Walmart for the item. On the other hand, if Target’s sales are not affected by Walmart being sold out of baby bottles, then maybe those customers are going somewhere else. The level of competition between retailers, in turn, helps dictate how they should respond to each other’s prices. If Target and Walmart are direct competitors, one should react when the other changes a price. But if they’re not competitors, then they should be less sensitive to what the other is doing.
Relatedly, the authors note that prices can mimic the effects of a stock-out. For instance, if Target prices an item so much higher than does Walmart that it deters customers from buying, then that’s the same as if Target were stocked out, and it will drive sales from Target to Walmart.
The methodology that Gallino and his co-authors built and describe in their paper is designed to help retailers find the right price for each product in a category, given the prices and stock-outs of competitors. It does this by telling retailers three things: the price to set, the level of competition, and the extent to which the category is one where consumers search and compare. And because the methodology involves an algorithm that can be implemented automatically via software, it can be applied to thousands of products simultaneously.
While prices are indeed important to competition, Gallino warns that there are other considerations retailers must keep in mind, especially in the long term. In a highly price-competitive environment, the shopping experience will become more important. Is there convenient parking? Is the website easy to navigate? “Many times retailers are too focused on having the lowest prices, but they don’t put enough effort into the operational experiences that will retain customers,” he says.