An Economist’s Perspective on User Experience Design

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by Eric Schultz

I first studied UX design — and then I studied Economics. To most folks, those two things go together like chocolate and beets. But have you ever had a chocolate beet cupcake? You might be surprised. Looking at your design practice through the lens of economics can also be surprising, refreshing — and even quite tasty.

Still not sold? Think about it this way: Though they approach the problem from different sides of the brain, both disciplines, at their foundations, explore the reasons people do what they do, then use what they learn to make those experiences better. Practice thinking like an economist, and you can add some new tools to your UX and product design toolbox.

Your Attention, Please

But first, let’s get something out of the way. When you think of economics, what comes to mind?

If your answer was something like MONEY MONEY MONEY…

Photo Credit: unsplash.com/@sharonmccutcheon

…we need to talk. The truth is, economics isn’t just about cash. The most straightforward and insightful definition I’ve found is this, from Ludwig von Mises:

“Economics is not about goods and services; it is about human choice and action.”

This encompasses a whole lot more than stock trades and GDP. Choices range from Should I click this advertisement? to Should I donate a kidney? And scarcity extends beyond money and goods to time and attention. Here’s economist Herbert Simon on how information and attention interact to produce complex, dynamic experiences:

“What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”

Complex, dynamic experiences involving information and attention. Sounds a bit like … UX design.

Playing Games

In economics, as in design, choices don’t exist in a vacuum. One tool economists use to study the interaction of multiple choices is game theory, the process of modeling the strategic interaction between two or more players in a situation containing set rules and outcomes. In the Prisoner’s Dilemma, a classic game theory thought experiment, two criminals commit a crime together. They’re apprehended, held in separate rooms, and each given a choice — confess or don’t confess, with rewards and punishments based on a combination of their choices. They can’t communicate or cooperate.

It looks like this from Bob’s perspective:

• If Joe doesn’t confess, I should confess, because I’ll go free, which is a whole lot better than a year in jail.
• If Joe confesses, I should confess, too, because two years in jail is better than three.
• So whatever Joe does, I should confess.

Joe does the same analysis and comes to the same conclusion.

What makes this game so illuminating is that, despite each player trying to pick the best option, together they end up with the worst possible outcome. The influence on the outcome is complex and cumulative.

Well, that was kind of a downer, huh? Good thing you’re a designer — because design approaches the issue from the flip side:

• The designer chooses the game structure.
• Design choices can affect the game’s outcome.

Or to put it another way: As designers, we define our goals — perhaps optimization, fairness, strategy-proofing, whatever — and then devise a mechanism to help achieve them.

Different Rules → Different Behaviors → Different Outcomes

Mechanism design is so influential that it earned Leonid Hurwicz, Eric Maskin, and Roger Myerson a Nobel prize in economics in 2007. If you’re reeeeaaallly into math, look it up.

As for us mere mortals, we can apply the intuitive concepts behind mechanism design to help us understand how different rules can yield different behaviors and outcomes.

Here’s a classic (pre-smartphone) example: The initial per-ride fee gives taxi drivers an incentive to maximize the number of trips per day — and by doing so, to get passengers to their destinations as quickly as possible. But what happens if the per-ride fee was not a factor?

You can see a modern version of this problem in this Uber use case, which shows how the company instituted rules designed to create more affordable rides but ended up with a jump in cancellation rates. (The article doesn’t say so explicitly, but I suspect each cancellation affects the experience of drivers, and so of other potential riders.)

To address the problem, Uber added frequent updates, influencing cancellation behavior — an excellent illustration of how adding a rule can change UX design and influence behavior.

Different Behaviors → Different Outcomes → Different User Experiences

Last week I got a notice that a rare Detroit Techno vinyl I’d been looking for was available on eBay. I clicked through and was asked for the maximum I’d be willing to pay. I entered $50, reasoning that anything higher wasn’t worth it, and anything lower would be a deal.

This was a second-price auction. How this economic model works: If I win I pay the next highest bid — at most $50 or, if no one bids that much, something less. I put in my bid, and wait for the outcome. If I’m outbid, no big deal; it would cost me more than it was worth to me. If I win, I pay what I think the item is worth, or possibly less.

But what if the auction used another economic model? In a first-price auction, for example, you pay what you bid. Sounds simple enough. But imagine how my user experience might have played out in the first-price format. I start bidding low, pay constant attention, and increase my bid every time I’m outbid. My focus shifts from the vinyl to winning. And if I do win? I’m likely to pay more (maybe a lot more) than I’d hoped. Cue buyer’s remorse.

Second-price auction: Bid, then do something else — read a book, write a song, go kayaking. If you get outbid, no worries; maybe next time. If you win, nice.

First-price auction: Bid, get outbid. Bid, get outbid. Repeat. Hey, you won! But you paid a lot more than you should have.

From a social design perspective, the choice of auction type here has a massive effect on the totality of the user experience. This goes beyond how much money a bidder spends or saves to the overall experience of users on the platform — which of course is the goal of all UX design. And that experience has a direct influence on the success or failure of the business as a whole.

Change the Rules, Change the Outcome

Once we start looking at design through the economic lenses of choices, rules, resources, and imperfect information, we can see how they can influence everything from voting mechanisms to organ donation. Here’s a sobering statistic:

There are more than 100,000 people in this country waiting for a kidney transplant, and the median wait time is more than three years.

Now let’s look at how a shift in models could help bring those numbers down.

In many cases, a donor is willing but the donor’s kidney isn’t a match for the recipient. So the medical team seeks out another donor-recipient pair that creates two good matches. Because no one wants to risk non-reciprocation, you’d need four operating rooms and four surgical teams, all available at the same time. And more simultaneous exchanges would quickly make the logistics unsustainable.

Paired donation: Needs to be simultaneous and matching is difficult.

Chained kidney exchange: With one altruistic donor, many non-simultaneous exchanges can occur.

But Alvin Roth (another Nobelist) devised a different set of rules. In a kidney transplant chain, it takes one donor gives to a stranger with nothing guaranteed in return. But the momentum builds from there, with no set endpoint. To date, The University of Alabama at Birmingham’s School of Medicine has the nation’s longest ongoing single-center kidney transplant chain, with more than 101 transplants in five years.

Change the rules and you change the outcome. And that means — well, “a better user experience” doesn’t do it justice.

Go Forth and Change

See what holding up a new lens can do? Now, get out there. Look, observe, and consider the interaction of choices when resources are scarce and information is imperfect — in your design work, and in the world at large. What rules can you apply to improve outcomes? How might you change the game?