Fuel and Friction: Five Behavioral Economics Lessons for Product Managers

You’ve probably come across Dan Ariely’s “Predictably Irrational” in an airport, or heard him on an episode of Freakonomoics Radio, or, most recently, caught him on HBO’s “Bad Blood.” Well, when I got to see Ariely present live on stage at Pendomonium last week, it was nothing short of a celebrity sighting. Turns out he’s just like us, if “us” is a group of product managers trying to affect behavioral change. Which was probably a good description of about 800 of the people in the audience.

Ariely discussed the ideas of fuel and friction as the two driving forces in closing the gap between the behavior you see and the behavior you desire. What does this mean for product managers? Reduce friction, pour on the fuel, and voilá — your KPIs are all shooting up. 

Small Friction Matters

Ariely discussed an experiment he was leading for a mail-in pharmacy that wanted to encourage customers to switch to generic drugs. The company sent letters to its entire customer base, encouraging them to switch. Doing so would save the customers money, but would also require them to return a signed form. That’s a lot of friction. You’re asking them to switch AND you’re asking them to mail something back? Think again. 

Is it that people love paying more for branded drugs? No. They just really prefer doing nothing to doing something. Even when offered free prescriptions for six months, people didn’t switch. If money wouldn’t change the equation, what would? The solution was ultimately a “forced choice.” The threat of stopping people’s prescriptions was the only thing that made them switch. 

When you design systems and product architecture, keep in mind that the “big prize” may not be as effective as removing friction or forcing the hand of the user. 

Experiment, Experiment, Experiment

Fuel is more complex than friction because friction is something you can study, analyze, and react to. Accelerating desired behavior, meanwhile, requires more experimentation. The generic drug study was a good example of how the biases of the company led them to assume that simply handing out free drugs would change their customers’ behavior. But a good PM knows that your own ideas can easily get in your way. 

In another experiment led by Ariely’s team of researchers, they were trying to encourage saving amongst the poorest residents of the Kibera slum in Kenya. Saving money when you’re barely making enough to get by is difficult, of course, which is why the answer is not immediately apparent to policymakers. In this case, the researchers tried no less than seven experiments to test hypotheses around how to affect such radical behavioral change. 

Meet Your Users

Designing the experiments for the Kibera residents required really understanding their everyday life. Grad students hailing from well-to-do research universities would not be able to design the right kinds of experiments from the comfort of their air-conditioned labs. However, spending time and interacting with the people they were trying to help ultimately led them to an unexpected solution. 

The researchers tried more obvious solutions like savings matches, simple reminders, and loss-aversion tactics. But then they also devised a mechanism that would text parents a reminder that was worded as if it came from their own children. This particular method worked better than matching savings, and as well as the loss-aversion tactic. Ultimately, however, the incentive that worked best came from an unexpected source. Those who saved the most received a physical coin. It wasn’t of any financial value, but it signified to others in the community that the individual was being a responsible breadwinner. 

When trying to understand your users, it’s not enough to observe them from a distance. You want to go out and spend time actually understanding their motivations and how your product fits into their life. Simply watching how they interact inside your product is important, but it only tells a part of the story.

Symbolism and Naming

The coin example in the Kibera study highlights the importance of why symbols are important motivators in people’s decision making. The coin had no financial value, but it had social clout. And it was a way for people to compare themselves to those around them, not unlike a checkmark next to your Twitter account. 

Ariely suggested that paying attention to things requires naming what’s important. He was involved in a government project in Israel that culminated in a decision to automatically open a college savings account for every child the moment they’re born. Opposition to the move tried to argue that simply reducing college costs would be much more valuable. However, his research ultimately showed that simply having the account made parents who wouldn’t normally think about college start thinking about it. A “college savings” account is superior, he argues, to actually saving on college. The symbolism of owning such an account can make all the difference. 

Make It Seem Like Hard Work

The final piece of advice Ariely shared with the audience had to do with creating an experience that removes friction but highlights pain. How is that good for your users? Well, our satisfaction — and willingness to pay for a good or service — is a function of how much work is done for us. He pointed out that (some) people are perfectly willing to pay $6 for a cup of coffee if they watch the barista pour over a funnel for several minutes. Or they’ll pay extra for dinner if it’s consumed in front of an open kitchen where all the work that goes into the meal is right there for you to see. 

Ariely pointed out that digital industries are actually terrible at this — we don’t typically show the magic behind the product we built. He did highlight one digital experience that mimics the open kitchen well: Kayak, the travel search engine, uses a small delay to show you all the sources they’re scouring for you. Could they display it more quickly? Probably. But by delaying the result they give users the impression that the algorithm is working “harder.” I don’t know about your algorithms, but I’ve yet to meet one that is interested in working “more” or “less.”

Economists have come a long way from studying the homo economicus to studying real subjects whose decision-making processes and behaviors aren’t always rational. Product managers are probably closer to understanding that than the economists of yore, but these are still helpful reminders to not let supposed common sense get in the way of building products that serve users in their own element.