More retailers are testing how customers respond to price increases in real time—with the results often giving them the green light to go higher.
Say a soda manufacturer is facing a steep rise in costs. Say the company decides to raise the price of a 12-pack to recoup those costs. Rather than doing a Hail Mary and hoping the price increase doesn’t dent sales, the retailer selling that soda tests a few different price points. In a couple of stores, the price goes up by ten cents. Elsewhere it goes up by a quarter. Maybe it lowers the price in a few stores, too.
Then it waits to see what happens. If demand remains little changed at the highest price point, it may decide to roll out that new price across thousands of stores.
Welcome to the world of real-time price testing. More retailers are experimenting with price fluctuations to determine how high they can go before turning off customers and losing sales — and where they need to keep prices low.
“Everything is a test all the time,” said David Moran, cofounder and chairman of Eversight Labs, which provides the technology to test pricing and promotions in real-time to consumer product companies and retailers like Coca-Cola, Hershey, Neutrogena, Walgreens and JCPenney.
While companies have always been able to run small tests before rolling out price changes, advancements in technology now allow them to run tests in a handful of locations and then optimize prices for each item in their product portfolio across thousands of stores.
That type of real-time data comes in handy at a time when consumer behavior has become so difficult to predict, amid a global pandemic and inflation at a 40-year high. Typically, companies look at how customers have responded to price increases in the past and try to infer how they’ll respond in the future. They want to be careful not to raise prices so sharply that sales nose-dive. However, data from years past isn’t terribly helpful.
“Historical data is irrelevant right now,” said Farla Efros, managing director of HRC Retail Advisory at Accenture.
According to historical data, consumers should have reacted more negatively to price increases. However, the consumer products companies that make snacks, drinks, cleaning supplies and other household staples have been saying that consumers have largely been more accepting of price increases than they expected. Last month, Procter & Gamble said elasticities—which measure how much demand for a product falls when prices go up—were still 20% to 30% better than historical data suggested.
“Despite all the jawboning that consumer demand is softening or consumers are going to snap back, we’re not seeing that in the data,” said Moran. “It’s a bit of a puzzler.”
Moran has an eagle eye’s point of view. He helps set prices and promotions for some of the largest companies in the world, which do over $80 billion in revenue in total. When he began noticing last summer that prices were going up and consumers didn’t seem to mind, he wondered if there was something wrong with the data or the company’s algorithms.
He assigned a team of “very expensive” Silicon Valley data scientists to investigate, throwing so much manpower at the task that it added up to several years of full-time work in a matter of months. He then hand-inspected every single elasticity result for a grocery store client to better understand what was going on.
His conclusion? “It’s not the algorithms that are failing. I’ve checked to the nth degree,” said Moran. “What’s happened is the consumer has changed.”
If consumers continue to show they’re willing to buy the same items even as the price increases, that essentially gives the companies watching in real time permission to charge more. If customers balk at price increases, a company may decide to hold off on raising the price.
Some retailers have noted that a portion of their customers, particularly those who are lower-income, are beginning to feel pinched by inflation and are adjusting their spending. For example, Walmart noted that some customers were switching from whole gallons of milk to half gallons, and buying more private-label versions of lunch meat and bacon.
Eversight’s technology can take that into account. Based on the feedback it gets in stores, it may suggest lowering the price on necessities like milk and bread, where consumers are more sensitive to price changes. It has also been recommending to many companies that they lower the price of private-label products, to keep them affordable, while raising the price on the brand-name version.
Adoption of real-time data is accelerating, helping fuel a 62% rise in sales at Eversight last year. Companies that use its technology can typically grow their revenue by 1% to 3% and gross margin by 2% to 5%, Moran said.
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