When consumers choose where to shop, they often consider a store’s price image —does the store have a reputation for having lower or higher prices than its competitors? A store’s reputation for lower prices doesn’t happen by chance.
Choosing a pricing strategy is one of the biggest pricing decisions a retailer makes.
In “When is HILO Low? Price Image Formation Based on Frequency versus Depth Pricing Strategies,” a recently published paper in the Journal of Consumer Research, co-authors Ryan Hamilton, associate professor of marketing, Ramnath Chellappa, associate dean and Goizueta term professor of information systems and operations management, and Daniel Sheehan, associate professor of marketing and supply chain at the University of Kentucky’s Gatton College of Business and Economics, explore a gap in existing pricing strategy research. “Our research doesn’t threaten the validity of the previous research,” said Hamilton, “but what it does do is point to the limited generalizability of the previous research.”
This is because previous pricing strategy research used the same research paradigm: It emphasized consumers’ perspectives as they compared prices simultaneously across multiple stores. Hamilton, Chellappa, and Sheehan wondered what would happen if they studied consumers as they compared prices of products within a store, instead of across stores.
When they did so, the authors found that “many of the prominent findings of previous research are reversed,” they wrote. “We propose that when stores’ prices are evaluated one at a time, or in isolation, consumers will rely on the most salient contextual clues available—within-category price information—when forming a price image.” For example, rather than research the price of peanut butter across multiple grocery stores, shoppers often evaluate the price of peanut butter by comparing the prices of the brands on the shelf in front of them.
To illustrate their point, the authors explore two basic pricing strategies: a frequency pricing strategy and a depth pricing strategy. Every Day Low Pricing (EDLP) is a frequency strategy where stores offer small price advantages over their competitors on many items. Walmart employs an EDLP strategy. A common depth strategy is a high-low (HILO) pricing strategy. HILO offers infrequent, but deep, price advantages over competitors. Macy’s utilizes this strategy.
“The conventional wisdom is that EDLP equals low price,” explained Hamilton. But he and his co-authors argue that in a non-theoretical environment, the effectiveness of EDLP strategies is less clear. The trio hypothesized that the context in which consumers encounter prices has important implications. Specifically, that the frequency advantage of EDLP identified in earlier research was limited to those scenarios where customers were able to simultaneously compare prices across multiple stores. In contrast, they argue that a depth advantage, one resulting from HILO pricing, will be more likely when consumers evaluate store prices separately.
“Without simultaneous comparisons across stores, consumers shift from using across-store prices as reference points to using within-category reference prices. As a result of this shift, deep price advantages are easier to evaluate than frequent price advantages and therefore more influential on customers’ formation of price image,” they write.
“Because our theoretical account is based on within-category external reference prices, we predict that a depth store is likely to be evaluated as having a lower price image than a frequency store even when consumers are exposed to the prices of just one store,” they write.
The authors tested their hypothesis using six separate experiments. All but one of the experiments studied national brands commonly found in grocery stores. (The other experiment used televisions.) In the experiments where participants saw store prices simultaneously, the experiment replicated the frequency advantage noted in previous research. But when participants did not have simultaneous price information across stores, the previous findings didn’t hold
“What we found is that if you distance those prices comparisons even a little bit -showing a price on one webpage and then seeing a price on another webpage - that’s enough to completely reverse the findings,” explained Hamilton.
In an isolated setting, “a couple of really low prices” will better communicate a store’s low-price image, said Hamilton. “That’s the big story.”
While excited about the findings of their research, Hamilton is quick to point out the limits of their hypothesis, such as when pricing information isn’t readily available or when the consumer isn’t familiar with the brands of the product they wish to buy. “People want a simple answer that works everywhere, but it’s more nuanced than that,” said Hamilton. “This [hypothesis] is going to work better under certain set of circumstances than others because people process price information differently.”
The insights aren’t only useful for retailers. While using a store’s price image to shop can be efficient from a consumer standpoint, assuming that the prices are low solely because the store has a reputation for low prices isn’t always the case. A retailer’s price image has vulnerabilities. Not everything at Costco is cheaper than it is at Whole Foods. Southwest Airlines may not always be cheaper than Delta Air Lines. “If you’re shopping for things you really care about,” advised Hamilton, “it might be worth doing more across-store price comparisons.”
Chellappa is excited about how the paper addresses gaps in traditional economic models of pricing. “While much research in economics and information systems focuses on the availability of information for price comparison, the cognitive aspect of ‘how’ consumers compare and process such information is only explicated by studies such as ours. Looking at pricing through a behavioral lens, capturing consumers’ real shopping behavior reveals great insights that will be useful for firms,” he said.
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Ryan Hamilton Associate Professor of Marketing
Ramnath K Chellappa Professor of Information Systems & Operations Management; Associate Dean & Academic Director, MS in Business Analytics