Design Your Customers’ Decisions
There is a vital lesson buried in the August 19, 2009 Jet Blue announcement that they were suspending sales of the $599.00 “All You Can Jet” promotion they’d debuted only seven days before. Any student of Behavioral Economics could have predicted that an “all you can eat” approach would inspire vastly different behavior than if Jet Blue had charged a lower fixed fee plus $1 per mile. Similarly, over a decade ago when AOL switched to a usage-independent flat price, connection time increased four times more than they anticipated.
“All you can eat” is an entirely different price than “very, very cheap.”
Traditional economics says that lowering the marginal price from $2 to $1 should have a similar effect to lowering it from $1 to $0 — but experience and experiments have both shown that the traditional demand curve acts in an odd manner when we reach $0 marginal cost. Jet Blue’s executives should have known better. But the Jet Blue management team is not alone.
Many executives assume their customers are more rational than they really are. For example, most leaders believe in enhancing the options given to customers, but increased choice can actually freeze decision-making by overwhelming the shopper. Excessive options is a key reason that an average of 60% of all online shoppers abandon their purchases mid-stream.
Behavioral Economics is the study of how people really think as opposed to how we think they think. To some of us, who were never fully convinced by the hyper-rational assumptions of neo-classical economics, it is a welcome return to reality. Yet, many firms have such a deep case of rationality-itis that they continue to treat their customers as if they were designed by Adam Smith. In working with Dan Ariely, we’ve begun to apply a set of ideas from Behavioral Economics in real world settings, around four distinct areas: framing, aversion, social context and timing — what we call FAST decision-making designs — and their impact can be significant. Our aim is to make the choice process easier for the customer.
In their famous recommendation engine, Amazon combines framing and social context, which gives the shopper an easy way to traverse millions of possible selections. In our work with clients we have found that it’s possible to increase choice to a higher value and higher-priced product by as much as 10 or 20% by framing the option that is contextualized to them (e.g., “Someone like you also bought this other book.”) This is consistent with Amazon’s belief that their recommendation engine increases the average purchase by 20%.
In our world of information overload, every new choice is an effort — so companies need to give as much thought to the process of choice as to those choices and options themselves. For instance, Dan noticed that the Economist, at one time, showed three options for their potential subscribers: online-only for $59.00, print-only for $125.00, or online and print for $125.00. He designed an experiment, using his students, in which 84% chose the $125.00 for print and online, 0% chose print-only, and only 16% chose online-only. Any rational manager would say the $125.00 offer print-only offer was useless. But when Dan removed the $125.00 print-only offer, 68% of people bought the online product for $59.00 while only 32% shelled out for the $125.00 bundle! In other words, the higher-priced option was chosen less than half as often. By having the decoy of $125.00 for print-only, the customer could make an easy comparison to the other $125.00 offer in which they got online for “free.” Even something as simple as choosing a magazine has enough complexity in it that a decoy choice can radically change buyer behavior.
If Jet Blue had understood the implications of Behavioral Economics, they may have raised the price on their offer — but despite the data that shows the power of designing the decision process, few companies trust Behavioral Economics because stands in the face of much of the economic logic executives were taught in school.
Every manager should remember that in a world of excess choice, an easy place to differentiate is in the careful design of the decision process itself. It is especially powerful in the ever-increasing realm of e-commerce. Few companies have optimized their customer choice process to make the most of the web. Fewer still do regular experiments to find out how their customers really act instead of how they are supposed to act, and they are leaving money on the table because of it. So ask yourself: is your company’s choice process optimal — and do you have data to prove it?
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