No, Walsh isnt a philosopher. Indeed, as a trained scientist (a meteorologist, to be precise), his answers are anything but theoretical. But it certainly is about perception.
The temperature where people start feeling cold—and start acting cold—varies sharply across the United States and certainly globally. And yet until recently, retailers made buying decisions based on fixed—and usually incorrect—assumptions about how consumers react to weather.
"If you live in Seattle—where it rains an awful lot—your behavior on a rainy day is very different than if you lived in sunny L.A.," said Walsh, the senior vice president for client services at Planalytics, in Wayne, Pa.
Another Walsh example is how Americans react to three inches of snow. In some neutral parts of the country, schools are closed and traffic is delayed. In Buffalo, N.Y., thats considered flurries and no one notices. "You get three inches in Atlanta, and thats Armageddon," he said.
Many huge global retailers—including Bloomingdales, 7-Eleven, Kmart, JCPenney, PetSmart and The Home Depot—pay Walshs company to analyze weather patterns and customer buying patterns and predict likely buying patterns.
"More and more companies are looking at this information very carefully, trying to get an understanding why their customers do what they do," Walsh said. "What is the weather in Buffalo, and how warm does it have to get before people start buying shorts versus how cold does it have to get in Orlando before people start buying sweatshirts? Theres no voodoo about this. Its pure statistics."
Planalytics clients run the gamut, from retailers worried about seasonal clothing to convenience stores that have to know what cold/hot weather items to keep on hand to companies that fill ATMs with cash, who need to project the absolute minimal amount of money they need to keep the machines happy.
Not only do retailers have to understand that 45 degrees Fahrenheit is viewed as quite warm in New Hampshire in February and brutally cold anytime in Los Angeles, but they also have to reject historical retail data when projecting likely sales demand.
"The problem that were solving is that, by and large, retailers use last years sales to predict this years season," Walsh said. "When you forecast using last years sales, that only works if you believe that this years weather will be exactly the same as last year."
These projections go beyond the obvious. In weather perceived as bitter cold, consumers avoid large shopping malls. But those who do make it are committed and are extremely likely to make purchases. When the weather is perceived as nice and comfortable, a lot more consumers go to the mall, but they are more likely to be tire-kickers and browsers, Walsh said. Few people feel like browsing during a blizzard.
Walshs company typically delivers a seven-day immediate weather and buying pattern prediction report for each client, focusing on appropriate geographies. But they also deliver an 11-month prediction, which Walsh says is accurate about 75 percent of the time. The reports are delivered on the Web and are usually dumped right into Excel spreadsheets.