01 Jun 2018
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The Evolution of Modern Pricing Models

Associate Professor Thales Teixeira and Assistant Professor Donald Ngwe on the impact of e-commerce on pricing—and why firms should make online discounts harder to find

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image by John Ritter

From Uber’s surge pricing to dynamic ticket pricing, it seems there’s been more awareness of pricing models and pricing strategy in recent years. What’s driving that interest?

Thales Teixeira: We need to go back before the businesses started paying attention to pricing models—we need to go back to when consumers started paying attention to pricing online. The internet becomes widespread starting in 1994, and suddenly you can know the price of something with very minimal effort. And so companies needed to compete by lowering prices, and they started losing money. There have been two big avenues that companies have pursued since then. One is dynamic pricing, which entails varying the price according to certain conditions. The airlines, for instance, started charging higher and sometimes lower prices as you got closer to the flight. And the second is price discrimination, where companies have various prices at the same time for different customers, depending on everything from geography to browsing history.

Donald Ngwe: This has always been the best-case scenario for any seller, but it hadn’t been implemented until recently because of a few constraints. One, in brick-and-mortar stores, you can’t change shelf prices that frequently. With e-commerce, that cost disappears, and nowadays with better algorithms, it becomes even easier to change prices as often as possible. Another constraint has been how consumers react. The consumer belief that changing prices is unfair has been eroded. Now consumers almost expect prices to be different every time they check, which opens up more opportunity for prices to oscillate and vary according to consumer.

In a recent case study, you question the notion that always making purchasing easier for consumers is necessarily beneficial for e-commerce vendors. What led you to make that argument?

TT: Amazon has been a leader in the idea of reducing friction in shopping. One click, you’ve bought your books. So other companies also wanted to reduce the effort for customers while, in parallel, reducing prices. And this has led to a pervasive problem: Virtually all e-commerce companies are losing money. So when we started working on a case with Zalora—a Southeast Asian fashion e-commerce company led by Paulo Campos (MBA 2010)—we thought about deliberately employing a strategy where we made transactions easier for users who were willing to pay more. If users want to pay less, we’ll make it just slightly harder. That is the idea behind employing “search frictions.”

DN: You can think of this approach—of identifying who cares less about price as well as delivering a higher price—as achievable by two means: One, you can go really high tech, with algorithms behind the scenes that post prices at very high frequencies, or you can go the route that we took in collaboration with Zalora, which was to approach the problem by designing the online store in such a way that everyone saw exactly the same prices as well as the same assortment. However, certain cheaper items required some extra clicks and scrolls to discover.

TT: In the end, we were able to increase Zalora’s gross margins by up to 31 percent in some experimental conditions—and it did not require any change in prices or product assortment. And since the experiment required virtually no investment or additional cost—apart from minor website design changes—it can be done by almost any e-commerce business, with significant impact to the bottom line.

How can what we’re learning about e-commerce pricing models impact how we think about brick-and-mortar pricing models?

DN: It all boils down to customer insights—and then choosing your offline strategy to conform to what you’re learning from your consumers online. But I think the answer is that incremental adjustments to the in-store strategy are probably not sufficient. What’s most likely required is a larger overhaul of the business model that goes beyond applying online insights offline to a more defined integration of those two buying environments.

TT: Some retailers have different prices online and offline, but if you go to a physical store and ask for the online price, they’ll match it. This is Best Buy’s model. There are some retailers that have higher prices offline and lower prices online—about a 5 to 10 percent difference—because online is more price competitive. Some have it the other way around, charging more online because they’re offering more convenience to the customer, and they have this added cost of shipping. Walmart does this.

My opinion is that you have to really think about online and offline as different businesses with some degree of overlapping customers. They all talk about integration, but even if you have the same products and the same customers, the behavior of the customers is so vastly different that having the same policy often doesn’t make sense. It’s very much like you’re selling a certain type of product in Japan and China: different markets with different competitors and different price structures. Just having one global policy is not the right way to do it. Different value delivered requires different value-capturing policies.

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Class of MBA 2010, Section H

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