A few years ago, a marketing team from a major consumer goods company came to my lab eager to test some new pricing mechanisms using principles of behavioral economics. We decided to start by testing the allure of “free,” a subject my students and I had been studying. I was excited: The company would gain insights into its customers’ decision making, and we’d get useful data for our academic work. The team agreed to create multiple websites with different offers and pricing and then observe how each worked out in terms of appeal, orders, and revenue.
Several months later, right before we were due to go live, we had a meeting about the final details of the experiment—this time with a bigger entourage from marketing. One of the new members noted that because we were extending differing offers, some customers might buy a product that was not ideal for them, spend too much money, or get a worse deal overall than others. He was correct, of course. In any experiment, someone gets the short end of the stick. Take clinical medical trials, I said to the team. When testing chemotherapy treatments, some patients suffer more so that, down the road, others might suffer less. I hoped this put it in perspective. Fortunately, I said, price testing household products requires far less suffering than chemo trials.
But I could tell I was losing them. In a sense, I was impressed. It was a beautiful human sentiment they were conveying: We care about all customers and don’t want to treat any one of them unfairly. A debate ensued among the group: Are we willing to sacrifice some customers “just” to learn how the new pricing approaches work?
They hedged. They asked me what I thought the best approach was. I told them that I was willing to share my intuition but that intuition is a remarkably bad thing to rely on. Only an experiment gives you the evidence you need. In the end, it wasn’t enough to convince them, and they called off the project.
This is a typical case, I’ve found. I’ve often tried to help companies do experiments, and usually I fail spectacularly. I remember one company that was having trouble getting its bonuses right. I suggested they do some experiments, or at least a survey. The HR staff said no, it was a miserable time in the company. Everyone was unhappy, and management didn’t want to add to the trouble by messing with people’s bonuses merely for the sake of learning. But the employees are already unhappy, I thought, and the experiments would have provided evidence for how to make them less so in the years to come. How is that a bad idea?
Companies pay amazing amounts of money to get answers from consultants with overdeveloped confidence in their own intuition. Managers rely on focus groups—a dozen people riffing on something they know little about—to set strategies. And yet, companies won’t experiment to find evidence of the right way forward.
I think this irrational behavior stems from two sources. One is the nature of experiments themselves. As the people at the consumer goods firm pointed out, experiments require short-term losses for long-term gains. Companies (and people) are notoriously bad at making those trade-offs. Second, there’s the false sense of security that heeding experts provides. When we pay consultants, we get an answer from them and not a list of experiments to conduct. We tend to value answers over questions because answers allow us to take action, while questions mean that we need to keep thinking. Never mind that asking good questions and gathering evidence usually guides us to better answers.
Despite the fact that it goes against how business works, experimentation is making headway at some companies. Scott Cook, the founder of Intuit, tells me he’s trying to create a culture of experimentation in which failing is perfectly fine. Whatever happens, he tells his staff, you’re doing right because you’ve created evidence, which is better than anyone’s intuition. He says the organization is buzzing with experiments.
And so is that consumer goods company. A group there is studying consumer psychology and behavioral economics and is amassing evidence that’s impressive by any academic standard. Years after our false start, they’re recognizing the dangers of relying on intuition.
A few weeks ago, the New York Times announced that they would start charging readers for online content in early 2011, and since then the million-dollar question has been: will it work? Will readers fork over the cash to keep reading the Times, or will they go elsewhere?
The main problem of this approach is that over the years of free access, the New York Times has trained its readers for years that the right price (or the Anchor) is $0 – and since this is the starting point it is very hard to change it.
So, should the New York Times give up? The trick with anchoring is that although we are not willing to pay more for the same thing, we are willing to pay more for different things. What this means is that one approach that the New York Times could take is to present us with a new experience so that we don’t associate it with the previous anchor, and are open to new pricing.
Let me explain. Because we’re not very good at figuring out what we are willing to pay for different products and services, the initial prices that new products are presented with can have a long term effect on how much we are willing to pay for them. We basically can’t figure out how much pleasure the New York Times gives us in terms of $ — so we go back and pay the same price we have paid before. This means that getting people to pay for something that was free for a long time will be very challenging, but it also means that if the New York Times were to offer some new service at the same time that they start charging, they might be more likely to pull it off.
It’s a strategy that Starbucks founder Howard Shultz put to good effect. Before he came along, consumers were used to paying much less for coffee from spots like Dunkin’ Donuts. So to incite us to shell out more for his coffee, he worked hard to separate Starbucks from other coffee shops. He designed it to feel like a continental coffeehouse, putting in showcases with croissants, displaying french presses, and coming up with exotic drink and size names. He redefined the coffee experience, and by doing so, convinced us to pay more.
The Times could try to take on a similar approach …
A few weeks ago Reebok unveiled a walking shoe purported to tone muscles to a greater extent than your average sneaker. All you had to do was slip on a pair of EasyTone and the rest would take care of itself.
Exercise without exercise? Great!
Considering the abracadabra-like quality of the shoe, it’s no surprise that it’s been selling like hotcakes. The question of course is “ does it work”?
According to a recent New York Times article on the topic, Reebok has accumulated “15,000 hours’ worth of wear-test data from shoe users who say they notice the difference.” (The company also quotes a study as support, but it’s one they commissioned themselves and only carries a sample size of five.) The two women quoted in the article further echo this sentiment.
Reebok’s head of advanced innovation (and EasyTone mastermind), Bill McInnis, says the shoe works because it offers the kind of imbalance that you get with stability balls at the gym. Unlike other sneakers, which are made flat with comfort in mind, the EasyTone is purposely outfitted with air-filled toe-and-heal “balance pods” in order to simulate the muscle engagement required to walk through sand. With every step, air shifts from one pod to the other, causing the person’s foot to sink and forcing their leg and backside muscles into a workout.
But as the Times article proposes at the end (without explicitly using the term), the shoe’s success could instead come from the placebo effect. Thanks to Reebok’s marketing efforts, buyers pick up the shoes already convinced of their success, a mind frame that may then cause them to walk faster or harder or longer, thereby producing the expected workout – just not for the expected reason.
And there are some reasons to suspect this kind of placebo effect: In a paper by Alia Crum and Ellen Langer. Titled “Mind-Set Matters: Exercise and the Placebo Effect.” In their research they told some maids working in hotels that the work they do (cleaning hotel rooms) is good exercise and satisfies the Surgeon General’s recommendations for an active lifestyle. Other maids were not given this information. 4 weeks later, the informed group perceived themselves to be getting significantly more exercise than before, their weight was lower and they even showed a decrease in blood pressure, body fat, waist-to-hip ratio, and body mass index.
So, maybe exercise affects health are part placebo?
P.S. If you’ve had the opportunity to try the shoe, leave a comment and let us know what you thought.
Consider some of illusion at the bottom of the demo page (click here to see it).
The two middle color patches look as if they are different, but in fact they are exactly the same. What is gong on here? How can it be that we see wrong? How can it be that eve after we are shown that these two patches are identical we still can’t see them accurately?
It is because our brain is wired in a particular ways and this wiring, while very good for some things, is not perfect — and it makes us susceptible to certain errors and mistakes. Moreover, because these mistakes are a part of us, we are fooled by them in predictable and consistent ways over and over.
Now, vision is our best system. We have lots of practice with it (we see many hours in the day and for many years) and more of our brain is dedicated to vision than to any other activities. So consider this — if we make mistakes in vision, what is the chance that we would not make mistakes in other domains? Particularly in domains which are more complex (dealing with insurance, money, etc.), and ones in which we have less practice? Domains such as decision making and economic reasoning?
Not very high I think — and this is why we have lots of decision illusions. The predictable, repeated mistakes we all make in our financial, medical, and other daily decisions.
Motivating people is an extremely difficult and delicate task as anyone who’s ever taught, managed, collaborated with or given birth to someone knows. In business, as opposed to say, child-rearing, the debate is slightly less daunting, though not always much clearer. For instance, offering incentives to employees for improved performance is a fairly common approach to encouraging higher sales —though surprisingly unproven by data.
For the most part, the effectiveness of incentives is supported by intuition and some anecdotal evidence. Wouldn’t everyone work at least a little harder for a $100 bill on top of their usual paycheck? Certainly it can’t hurt. But one important open question is whether monetary or tangible (spa retreat, ipod, dinner for two, etc) rewards more efficacious motivators?
Those who advocate for monetary incentives claim they have the greatest appeal given that the winners can do anything with them; what if someone needs an ipod like they need another hole in their head? On the other side, those in favor of tangible incentives argued that money lacks the emotional appeal of, say, a weekend for two at a romantic country inn or swank hotel. But either way, there was nothing to back up either camp.
Thankfully, there is some data on this debate. A few years ago Goodyear Tire & Rubber Company decided to test which method was more successful in an effort to improve sales of a new line of Aquatred tires. Their plan was simple and elegant: first they ranked their 60 retail districts according to previous sales, then divided them into two groups of equal performance and assigned one group to receive monetary incentives and the other to receive tangible incentives of equal value to the first group.
The results were very interesting; it turned out that the tangible-reward group increased sales by 46% more than the monetary-reward group. They also improved in terms of the mix of products sold by 37%. One explanation, and it seems to me a fairly good one, is that we can visualize tangible rewards (imagine yourself on a Hawaiian beach), which creates an emotional response. Money, on the other hand, is not accompanied by images as often (aside from maybe Scrooge McDuck swimming in piles of it), and lacks the emotional pull that tangible rewards have, so they’re less effective in motivating employees. I guess it’s called “cold, hard cash” rather than “future beach vacation cash” for a reason.
In a follow-up to the much acclaimed “Pinch of Saffron” , this latest Predictably Irrational Short Story is a thrilling Wall Street tale of overpricing CDOs, again written by one of my Behavioral Economics students, Andrew Holmberg. It’s entitled, “Fixed Income”, and you can find it here.
I pleased to announce a new series of short fictional stories written by Duke undergraduate students who took my Behavioral Economics class this last spring.
I will post another one of these stories twice a month for the next few months.
The first story is called “A Pinch of Saffron,” which is about a business executive who redesigns her mother’s traditional Indian restaurant to monetize on people’s irrationalities. You can download it here.
“For the great majority of mankind are satisfied with appearances, as though they were realities, and are more often influenced by the things that ‘seem’ than by those that ‘are.'”
-16th-century Italian politician Niccolo Machiavelli
It’s something we come across regularly: presentation trumps content. Often what matters is not what we know, or what we have done, but rather how we spin it. It’s why cover letters are so important, and why the peripheral route to persuasion – one of advertising’s biggest weapons – works.
Now, Don Moore of Carnegie Mellon University demonstrated yet another way that we are heavily influenced by delivery — We tend to seek advice from experts who exhibit the most confidence – even when we know they haven’t been particularly accurate in the past.
In his experiment, Don had volunteers guess the weight of people in photographs, and paid them for their correct answers. But before each guess, the volunteers were asked to choose one of four advice-givers (also volunteers) from whom to buy advice. Each advice-giver submitted their weight guess in percentage form, with some advisers spreading out their advice over multiple weight ranges. So, one advisor might have said that there was a 70% chance that the person’s weight was 170-179 pounds, a 15% chance that it was 160-169, and a 15% chance that it was 180-189. A more confident advisor, however, would have put all his eggs in one basket and said there was a 100% chance that the weight was within the 170-179 range.
Now here’s the really important part: in each round, before they chose their adviser, volunteers got to see each adviser’s percentage spread, but not the associated weight ranges. (See this really handy chart for more on the set-up.)
What did Moore find? Volunteers were more likely to buy advice from confident advisers (such as the 100% adviser from above) than those who spread out their percentages. What’s more, this tendency led advisors to make their advice more and more precise in subsequent rounds – but not more accurate.
These findings are troublesome. Because though confidence and accuracy sometimes go hand-in-hand, they don’t necessarily do so. And when we want confident advisors, some will exaggerate to give us what we want. Maybe this is why so many pundits on TV for example exaggerate their certainty?