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Create “Choosing” (Not “Shopping”) Experiences

August 4, 2011

On a recent, gorgeous day in New York City I walked from Bergdorf Goodman at 59th Street & 5th Avenue past Cartier on 52nd street and continued down 5th Avenue for over a mile. Because I was preparing for a speech I was scheduled to deliver to the Global Retail Marketing Association, I was paying particular attention to the stores and the shopping experiences they created — from the posh ambiance of Bergdorf’s with its $4,000 blue blazers to Diesel’s inexplicable ad line: “Smart has the brains, but stupid has the balls.”

My conclusion: The shopping experience at every store along this route was pretty much the same. The only difference was how much each merchant was willing to cut its prices: by 20%, 40%, or even 75%. None of them had created a choosing process — in which customers’ actions are guided by known principles of behavioral economics that help them make a purchase, not just look around. Instead, the retailers had simply stuffed the shelves, windows, and hallways with option after option after option, driving more shopping and less choosing.

There are many ways a merchant can create a choosing — not just a shopping — experience. For example we know from extensive research in the online realm (and from common sense) that ratings and popularity drive increases in sales. Yet nowhere in the stores could customers find reviews or any information about which items were most popular.

Products tend to move more quickly when people talk about them. Oddly, information exchange seems to presage choice, and stores can facilitate this in simple ways (imagine a souvenir store that told customers what most out-of-town” tourists buy) or in a more sophisticated fashion (e.g., displaying customers’ online reviews near products in stores — something Best Buy reportedly is considering.)

In addition, retailers could employ any number of other behavioral economics techniques that make it easier for people to choose. One of my favorites, which I’ve written about before, is the decoy effect in which you make it easy for a customer to get a deal. In my previous post, I noted that when the Economist magazine had three offers ($59 for online only, $125 for print only, and $125 for both), 84% of purchasers chose the print-and-online option because they got the online for “free.” Nobody bought the $125 print-only option, and 16% went for the online-only offer. This meant that the “average basket” of the population of Economist shoppers was just over $114 (84% of $125 + 16% of $59).

When the print-only choice was removed, 68% of purchasers chose the $59 option, only 32% went for the print-and-online bundle, and the average basket was approximately $80 (32% of $125 + 68% of $59). So when the decoy was added, the average sale increased from $80 to $114 dollars.

Likewise, any merchant who might be considering a 20% off sale on a $500 suit could instead offer $500 for the suit, $100 for a shirt, and $500 for the shirt and the suit. More people would be likely to buy the combo for $500, and it’s also likely that most of those people would have gone only for the shirt if the bundled deal wasn’t offered. This technique could help merchants in their eternal quest to increase the average sale per customer.

The growing popularity of mobile devices like iPhones, Android phones, and iPads makes helping consumers choose, not just shop, even more important for retailers. That’s because these gizmos allow consumers shopping in a store to consider many other options outside the store. Since we know that increased choice tends to freeze decision making, the result will be consumers who shop more and more and choose less and less.

With all this in mind, ask yourself: Is your sales process increasing choosing behavior or simply fomenting increased shopping? If your answer is the latter, you need to start designing a customer-choosing process.

John Sviokla

John Sviokla is vice chairman of Diamond Management & Technology Consultants, Inc. He is a former professor at Harvard Business School in marketing, MIS, and decision sciences. You can read his previous blog posts for HBR.org here.

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From → Customers, Marketing

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