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Late at night, after a concert or party or other social event, have you ever thought to yourself, “I would give anything for a piece of pizza/burger/pint of orange chicken right now!”? That’s the kind of attitude that makes sellers of such food options salivate, because it means that as a consumer, your price sensitivity has been overwhelmed by your need, or at least your powerful desire, for a tasty snack.

If you, like most consumers, express varying willingness to pay for the same foods, then naturally, the providers should be charging different prices. But how can they know precisely when you will be most willing to pay more, or alternatively, when you can be attracted by lower prices? Emerging trends in the restaurant industry, supported by advanced technologies and big data gathered through digital ordering channels, suggest some promising options for implementing dynamic pricing strategies effectively, in ways that benefit both restaurant operators and their customers.

Consumers’ increasing reliance on digital ordering and delivery options has led to a vast increase in the amount of information available, about who wants to eat what and when, as well as how much they are willing to pay for it. If data indicate, for example, that stay-at-home parents are clicking through quickly and repeatedly to order coffee that will be ready as they make their run to drop off the kids at school, coffee shops likely can raise prices a bit and still keep them happy. By tracking entertainment options and scheduled end times, pizza shops right next to a concert venue could add $1 per slice at the moment the show lets out, probably without disturbing hungry music fans in the least.

But dynamic pricing is not just about raising prices. Restaurants can track when their capacities are being underused, such that they are not making as much profit as they could from their ovens, staffers, and inventory, such as during mid-afternoon hours. At those times, they can and perhaps should offer deep discounts on particularly popular menu items to encourage consumers to consider eating their lunch a little later. In so doing, they can optimize their labor strategy (e.g., ensure servers have enough tables to make a living wage), spread their delivery services out to reduce long waits during busy times, avoid unused equipment capacity, and appeal to consumers who might have been dying for a steak but felt unable to pay full price. This general idea underlies the concept of happy hours, but with advanced data analysis capabilities, restaurants can shift their pricing more precisely to draw in more consumers.

The software applied to design dynamic pricing strategies continues to improve in its predictive ability and accuracy, based of course on ever-growing amounts of data. The software designers also rely on insights gained in other markets that are successfully using dynamic pricing, such as ride-sharing services. In turn, one provider suggested to a sports arena client that it should tout a discounted price for food and drinks ordered while the game was playing, rather than between periods. With such an approach, the service provider allows consumers to select the price they prefer: Are they willing to miss a few plays to save a few cents, or are they willing to pay more for the ability to watch every pass, block, and shot attempt?

But companies also need to take care with frequency and visibility of constant price changes, due to the often communal consumption setting that takes place in restaurants. If a consumer pays a certain price for a Chipotle bowl, then hears the person behind them in line order the same thing but get charged a higher price, Chipotle is likely to find itself subject to some anger and frustration. If a consumer visits the same storefront nearly every day to grab dinner but must pay different prices every time they visit, they might not return. Thus, restaurants need to make the rationale for distinct prices clear. People will pay more if they’re hungry for the offering, as long as they know what they need to pay and why.

Discussion Questions:

  1. In addition to previous purchases, what kinds of data might restaurants gather and use to define their dynamic pricing strategies?
  2. How can restaurants learn which consumer segments they should target with dynamic prices?
  3. Ride-sharing services already use dynamic pricing, and restaurants are starting to adopt it. Can you name any other industries that might leverage this pricing tactic effectively?

Sources: Sherri Kimes, “Is It Time for Dynamic Pricing in the Restaurant Industry?” QSR Magazine, October 25, 2022; Tom Ryan, “Will Dynamic Pricing Work for Restaurants?” Retail Wire, November 4, 2022; Tom Kaiser, “Juicer Says Dynamic Pricing Aids Labor, Delivery Cost Pressures,” Food on Demand, August 18, 2022