Katy Milkman: David Gold grew up in Cleveland, Ohio, helping his parents run their general store. They moved to LA when David was a teenager, and by his 30s, he was running the family's liquor store. Gold noticed that whenever he posted a price ending in 99 cents on a slow-moving wine, it sold out. He tested round-number pricing, too, but that didn't work as well. Prices ending in 99 cents brought the magic. He thought, "Wouldn't it be fun to have a store where everything was 99 cents?" So the 99 Cents Only store was born.
Speaker 2: Egg hunting is a lot like deal hunting. So this Easter, 99 your basket …
Speaker 3: … and you do the 99. So really, it's just another day at the 99.
Speaker 4: Or better yet, I can 99 my birthday bash, right?
Katy Milkman: The store opened in 1982 with a line outside the door. Within two years, two more locations opened, and by 1991, there were two dozen. The company never hired a publicity agent. Instead, they relied on word of mouth and humor. They took puns on the number 99 to the max with signs that read, "Open 9:00 to 9:00, 9 days a week" or "99.99% satisfaction or your money back."
Speaker 5: Go 99ers.
It wasn't a business model that could last forever. The chain closed due to the pressures of inflation on their unchangeable prices. But at one point there were over 300 stores located in California, Texas, Arizona, and Nevada. David Gold had tapped into something we all recognize. In this episode, we'll look at why a price or an age or a test score that falls just under a round-number threshold can have an outsized impact. We'll describe a bias that can influence our decisions about the music we buy …
Speaker 6: Copyright infringements aren't slowing down Napster, the song-swapping platform.
Katy Milkman: … how we categorize diamonds …
Speaker 7: Artisans cut top-quality diamonds to optimize brilliance, not carat weight, resulting in remarkable shiny …
Katy Milkman: ... and even the health care we receive. I'm Dr. Katy Milkman, and this is Choiceology, an original podcast from Charles Schwab. It's a show about the psychology and economics behind our decisions. We bring you true and surprising stories about high-stakes choices, and then we examine how these stories connect to the latest research in behavioral science. We do it all to help you make better judgments and avoid costly mistakes.
Melina Palmer: They were scrambling, trying to come up with ways to deter people, which included suing all sorts of people, including 12-year-old kids and grandparents.
Katy Milkman: This is Melina.
Melina Palmer: Hi, my name is Melina Palmer. I'm founder and CEO of The Brainy Business and author of The Truth About Pricing.
Katy Milkman: Melina is remembering the late 1990s and the chaos in the music industry as it made an awkward transition into the early days of digital music.
Melina Palmer: Sites like Napster had popped up where consumers were able to get free music really wherever they wanted. A problem of course being it was stealing, so not good on that side. But from a consumer perspective, you were able to go get whatever songs you wanted for free at any time. The issue, of course, then for the music industry is they were losing a lot of money and really in a free fall.
Katy Milkman: Consumers were ready for digital music, but their options at the time weren't great. They could buy physical CDs and turn those CDs into MP3 files, but that was time consuming, and if you only liked one song off of an album, it was expensive. Peer-to-peer file-sharing sites like Napster were not only illegal but also buggy and full of problems.
Melina Palmer: They would be bad quality, or they were labeled wrong. If you would go to search for a song or an artist, you think it's there, but there are 50 or 60 versions of the same song. You then go and pick one. It takes four minutes. Then you find out that the last four seconds are missing, and you don't have the full song. So it was a really terrible user experience.
Katy Milkman: Consumers wanted something better, an easier way to manage their old and new music. Record labels wanted some level of control back, and, of course, they wanted payment for their artists and song catalogs. In 2003, Steve Jobs was about to solve everybody's problems by solving his own. Apple at the time was relatively small, with around a 3% share in the personal computer market. But iPods were becoming popular. Jobs's idea was to create a complete system that would include the iPod, music management software, and a store to buy music. But first, he needed access to music, and for that Jobs needed the five major music labels to sign on. He proposed that songs could be purchased individually.
Melina Palmer: An executive from Warner had suggested the 99-cent pricing. Jobs ended up working with the Warner executives to come up with the initial pitch. Then when they agreed and signed on and had this 99-cent price, that was then leveraged to go through the rest of the big five music companies and get them to agree one at a time.
Katy Milkman: 99 cents per song became key. Jobs explained to the labels how just below $1.00 was an emotional threshold for people for an impulse purchase. People were more likely to click and buy a song for 99 cents than to buy the same song for $1.00. For anyone else who thought 99 cents was too much, he put this to them.
Melina Palmer: "How many of you had a Starbucks latte this morning?" That's three bucks, which we can now all remember when that was three bucks. To which he said, "That's three songs. How many lattes got sold across the U.S. this morning? A lot. 99 cents is pretty affordable." So this was really paramount in the way that they pitched and talked about how easy it was to just grab a song if you want it when it's just 99 cents.
Katy Milkman: The plan worked. During opening week, the iTunes Store sold 1 million songs. This was at a time when only 2% of computer users and 5% of laptop users owned Apple computers. Once iTunes was made available to people using PCs …
Melina Palmer: PC users added another million songs within just three days. So people were really hungry and excited to get that music, and they started picking it up at a very, very quick escalating pace. It changed our whole experience and the way that we access really all media these days.
Katy Milkman: Melina Palmer is the author of The Truth About Pricing. She's also the host of The Brainy Business podcast. The 99-cents pricing strategy is one of the oldest tricks in the book. It's widely presumed to communicate a bargain, a good deal because, wow, it's just pocket change. It's not even a whole dollar. For the iTunes Store, this approach to pricing helped revolutionize the entire music industry. But falling just below a round number influences more than discount goods. Take diamonds. The price of a diamond is determined by several qualities: its cut, clarity, and color. But there's another factor that significantly influences the value: its carat number, or weight. Slight differences in the carat number can have an outsized influence on the price.
Joshua Freedman: There are discrete price bands that go up sometimes in tenths of a carat, sometimes in half a carat, sometimes in a whole carat. That means that within each band there is a particular baseline price.
Katy Milkman: This is Joshua.
Joshua Freedman: I'm Joshua Freedman. I'm senior analyst at the Rapaport Group. We are a network of companies around the world providing services to the diamond industry.
Katy Milkman: The Rapaport Group publishes a standard price list used by dealers to set diamond prices. For example, there's a price for a diamond in the 1.0 to 1.49 carat range, and another price for a diamond in the 1.5 to 1.9 range, and so on.
Joshua Freedman: The way I've described it in the past is as a side view of a badly built flight of stairs rather than a ramp. So as you go up with size, the price increases, but it doesn't increase consistently as you go up because consumer desire to get the round 1.0 carat or the round 3.0 carat, and just below those round numbers, that's the point where the consumer can get a good deal.
Katy Milkman: Here's the thing. A 2.99-carat diamond is almost identical in weight to a 3.0-carat diamond, and to the naked eye, it sure looks the same. But the price goes up substantially when you hit that 3.0-carat mark. There are cultural and psychological reasons for this.
Joshua Freedman: You don't want to have to explain, well, it's actually a 2.99 carat. You just want to be able to say you've got a 3.0-carat diamond. This is mostly an issue in engagement rings where there are these social expectations going back to the 1930s.
Katy Milkman: We can thank De Beers and a successful ad campaign for inventing the idea of the diamond engagement ring, that and the suggestion that the engagement ring should cost at least a month's salary. Today, the suggestion is even higher. But if your concern is value, it's the oversized diamonds—that is, diamonds at the end of their price brackets, a 0.9- or 1.9- or 2.9-carat diamond—that are the better deal, and not just for your bank account.
Joshua Freedman: Often these diamonds will be better quality. When you're manufacturing a diamond, and when I say manufacturing, I mean cutting or polishing a diamond from the rough, you often have to compromise on something, either on size or on quality. So if you go for that extra size and try and hit the round number, you might have to compromise a bit on the quality. So it will often turn out that those diamonds that are just shy of a round number will actually be the best quality with the best proportions and the best cut quality.
Katy Milkman: So the next time you're in the market for a diamond, consider buying one just under the carat value you're looking for, and then maybe just round up when you're showing off. Alternatively, if you're like me, you'll know you've found exactly the right person to spend the rest of your life with when they propose and tell you the diamond ring they picked was just barely below a round number threshold to outsmart the system. Yes, that's actually how my husband picked my ring, and we've been happily married for nearly 20 years.
So far we've been focused on how our heightened attention to leftmost digits in a number and our under-attention to the ones farther right affects our perception of value and pricing. But our tendency to focus on numbers on the left also shows up when life is on the line.
Bapu Jena: My name is Bapu Jena. I'm an economist, physician, and professor at Harvard Medical School. Medicine is interesting in that a lot of the decisions that are made ultimately rely either explicitly or implicitly on numbers. One measurement that we look at for kidney function is something called the creatinine. If you have a creatinine of 1.9, that's considered to be elevated, not normal. If you have a creatinine of 2.0, that's also considered to be elevated. But you might imagine that when a doctor sees a creatinine of 1.9, they may be less concerned about it than if it's 2.0, even though those numbers are pretty much the same and they reflect similar amounts of kidney dysfunction. But when they see the 2.0, they might react a little bit more aggressively and say, "All right, well, I need to perform a kidney ultrasound. I need to work up this problem a little bit more."
Katy Milkman: Doctors have to make a lot of quick decisions with the data in front of them, including data about a patient's age.
Bapu Jena: Imagine you're a doctor, so you're working in the emergency department. The nurse comes to you and says, "There's a new patient who just arrived who has chest pain." There's a lot of things that would be going through your head as to what could be causing chest pain. But a key thing to think about is, "Is this person having a heart attack?" So you go into that room, you ask them some questions about their chest pain: When did it start? How does it feel? What makes it better or worse? Then you start to formulate an idea of whether or not this person could be having a heart attack. Then you look for things like, "Does this person have high blood pressure, diabetes, high cholesterol?" Those are risk factors for a heart attack.
The other thing you might consider is, "What this person's age? Is this person 40 years old, 50 years old, 70 years old?" The older people are, the more likely they are to have heart disease, and heart disease, meaning blockages or narrowing of the heart vessels, is ultimately what will cause someone to have a heart attack. So those are the things you're thinking about.
If you see someone who's 79 years old, and you see someone who's 80 years old, you might think of these two people as being more different than they actually are. They're really only separated in age by at most a year. But the person who's 79 might feel like they're in their quote-unquote "70s" to your mind, and the person who's 80 years old might feel like they're in their quote-unquote "80s." The older these people are, the more likely you are to think, "All right, this person might have a heart attack." Moreover, once you diagnose a heart attack, what do you do about it? Do you do a surgery? Do you just watch them? The older someone is, the less likely you are to want to crack open their chest and do a cardiac bypass surgery. So if someone is in their quote-unquote "80s," you might not want to do that, but you might feel more comfortable in doing that if they're in their quote-unquote "70s." If you look at studies, that's what we see.
Katy Milkman: Bapu and his colleagues looked at Medicare beneficiaries, people who are typically above the age of 65 in the United States and who were coming into the hospital for a heart attack. They found that patients aged 79 and 50 weeks were 20% more likely to receive cardiac bypass surgery than a heart attack patient aged 80 and two weeks. That's a huge difference for two patients who are just four weeks apart in age.
Cardiac bypass surgery is a major procedure, not something doctors suggest lightly. But here, Bapu and team found that doctors were more likely to suggest the surgery for someone in their very late 70s than someone in their very early 80s, even if those people were born weeks apart. Why? Well, if you're in your 80s, you're an octogenarian, too old to make it through that tough surgery, right? But if you're still in your 70s, well, that feels young enough to take it. Of course, though, that's a bias. Focusing too much on the leftmost digit of a person's age being a seven or an eight, instead of appreciating that a 79-year-old who turns 80 next week is not meaningfully younger than someone who turned 80 last week.
Bapu Jena: One takeaway from this is that if you change the way the information is presented or you make doctors aware of the issue, it could potentially save lives.
Katy Milkman: Bapu Jena is an economist, physician, and professor at Harvard Medical School. He was also the host of the podcast Freakonomics, M.D. and is the co-author of the book Random Acts of Medicine. You can find a link to his book and Melina Palmer's book The Truth About Pricing in the show notes and at schwab.com/podcast.
What we see in pricing and in doctors' offices and emergency rooms is that we tend to overweight the importance of the leftmost digit of a number. It's a phenomenon called left-digit bias. My next guest, Devin Pope, is a professor of behavioral science and economics at the Booth School of Business at the University of Chicago. The research I invited him to discuss today on left-digit bias happens to primarily feature cars, what we pay for them, and what we pay to ride in them. Hi, Devin. Welcome back to the show.
Devin Pope: Thank you. It's good to be here.
Katy Milkman: I was hoping we could start with a definition. Could you just tell us what left-digit bias is?
Devin Pope: Yes. When people are looking at a number, especially if the number is large, it can be very hard to process. We see lots of numbers in our lives. So the human mind, as you've discussed on your show many times, likes to be efficient, and sometimes we'll use simple rules of thumb or heuristics to make it easy. One of the things that we do when we see numbers is we focus mostly on the leftmost digit. It tends to be the part of the number that's most informative. If it's a $2-and-something item versus an $8-and-something item, it's good to know that left digit, and so we tend to do that. But that can, as we'll discuss, create some interesting issues.
Katy Milkman: Could you tell us a little bit about the project you worked on with Lyft to implement 99-cent pricing and what you learned from that?
Devin Pope: It started when my co-authors and I recognized that Uber and Lyft were offering a lot of people a ride that was just over a dollar value. For example, I literally got a ride offer from Uber for $14.02 one day. I had been studying left-digit bias for other projects and things, and it seemed like a very strange offer to make. They should be offering me a ride for either $13.99, because I'd be way more likely to accept that, or it might as well offer $14.99 and capture some more value, and I probably won't think of $14.99 and $14.02 as very different. So I sent a note and buddied up with John List, who's an economist here at Chicago who at the time was the chief economist at Lyft.
Katy Milkman: He's a former Choiceology guest, too, I should say.
Devin Pope: Nice, a good choice. We decided, along with Greg Sun and Ian Muir, to go ahead and write a paper about this.
Katy Milkman: Yeah, tell me about the paper. I love this paper.
Devin Pope: What we did next is we started with historical data at Lyft. We grabbed 600 million observations from 2019.
Katy Milkman: Just a little bit of data.
Devin Pope: Yeah, and looked at the prices that were offered to consumers for those potential rides. We verified that they weren't doing any sort of left-digit bias pricing. They were just as likely to offer that $14.02 ride as a $13.98 ride. Then we were really interested in knowing whether people were more likely to accept rides that were just under the dollar value versus just over the dollar value, and we find super strong evidence of this. So you're about one to two percentage points less likely to accept the ride as soon as you hop over that next dollar value, suggesting that Lyft was leaving a lot of money on the table by pricing a lot of rides at just over dollar values.
Katy Milkman: Yeah, I love that finding. I think what I remember is that you estimated the magnitude of the effect is something like Lyft was losing $160 million a year by ignoring this in their pricing. Am I remembering that right?
Devin Pope: That's right.
Katy Milkman: Does it surprise you that that was such a big amount of money they were leaving on the table?
Devin Pope: It surprised them, and it was certainly of interest to them and Uber and every other rideshare company that has now changed their pricing because of this paper. I think one thing that makes it surprising is that one could argue that Lyft and Uber and other rideshare apps are some of the most sophisticated pricing algorithms that we have on the planet. They're incredibly dynamic. They adjust based on supply and demand factors. There's different prices across different geographies at different times of day. So it's an incredibly sophisticated pricing system. Yet they were ignoring a very simple psychological thing that's been around actually a long time.
Katy Milkman: I know that after you did that analysis of the historical data, you did an experiment. Could you talk a little bit about that experiment and why that was the next follow-up step after you'd figured this out?
Devin Pope: John, more than me, went to the Lyft team and showed them our analysis using historical data and argued that they were leaving a lot of money on the table by not adopting a 99-cent pricing type strategy or something at least that approximates that. They weren't totally convinced, to be honest. They were super interested. We were claiming that this was the most profitable, potential change in their app that they had ever done. It was a really big deal. But they were worried. The thing they were most worried about is that it's possible if all of the prices that you see on Lyft or Uber end in 99 cents, the app can start to maybe feel gimmicky or cheap. They were worried about some of the long-run reputation costs that might come from implementing this.
For that reason, along with other things, they wanted to run an experiment. So within a couple of months, they were able to roll out a large experiment with all of the platforms, 21 million riders on Lyft. 50% were put in a control group, and others were put in these different treatment groups. Part of the experiment was to see if someone kept seeing 99-cent pricing over and over, would they maybe stop showing up to the app because they felt it was gimmicky or something like that?
The results of that experiment were that when someone saw a 99-cent price, they were more likely to accept the ride, just like we had shown, but they were also actually more likely to show up to the app again sooner. They remembered their experience as being a pretty cheap, good option. So we were actually underestimating how much money they were leaving on the table because they could not only get more rides accepted, but also people would be more loyal to the app, at least in the medium term. They are still testing really long-term holdout samples, because maybe after three years, you eventually get sick of those 99-cent numbers. That's why they ran the experiment before actually implementing.
Katy Milkman: That's great. I love experiments. I'm curious if you could talk a little bit about places we see this bias or you think this bias matters. Besides the market for diamond rings and getting into an Uber or a Lyft, where else does left-digit bias matter?
Devin Pope: The most obvious application is in pricing. You see this anytime you walk into a grocery store or you buy gasoline, and now you see it on Uber and Lyft and other places as well. But in addition to prices, I think this is something that is super universal. Anytime you're looking at a number, you can fall prey to left-digit bias.
One paper that Justin Sydnor and Nicola Lacetera and I wrote together was about how people process the odometer values on used cars. Again, it's a big number. You're shopping for a car. There's lots to pay attention to. We find that, for example, cars that are just under a round value, that have, say, 69,000 miles on them sell for a lot more than cars that have 70,000 miles. You see that at every 10,000-mile mark. So that would be another example. But I think it goes beyond just odometer values. You would probably see it on a car that gets 30 miles per gallon probably sells better than a car that gets 29 miles per gallon because that just feels like a lot more miles per gallon to people.
Katy Milkman: I love that. If you were to step back from the specific examples we've been talking about, what advice would you offer to people so they could avoid making bad decisions as a result of left-digit bias?
Devin Pope: That's a really good question. The truth is is I probably actually wouldn't worry about it too much. Take the Lyft example. We find that Lyft is able to make an extra 25 cents on average per ride that they do. So if they're doing a billion rides a year or something, that's where you can get these numbers of a couple hundred million dollars of profit extra per year. Now, for an individual, though, it's only 25 cents, 25 cents per ride. We have to pay attention to a lot of numbers in our lives, and it's not obvious to me that paying attention to all of those numbers actually is the right thing to do. I think using shortcuts makes sense.
In fact, I'll go even further. If you're really interested and want to go all the way to Section 6 of our paper that we wrote, you'll read about what's called consumer welfare. Clearly, this idea is something that made Lyft a lot of money. Did it hurt consumers? The answer is is we don't know. It's not clear whether consumers were helped or hurt. The intuition is is that perhaps they actually were not accepting Lyft rides enough because of their left-digit bias, and we were actually helping them get more in line with an optimal package of consumption that they were doing in their lives. So it's a little bit unintuitive, I think. But for the individual consumer, if everyone is pricing at 99 cents, it's actually smart and OK to start to ignore anything except the left digit.
Katy Milkman: I love that, as an economist, you're thinking about the world as in an equilibrium. But since you showed that the most sophisticated pricing algorithm in the world wasn't incorporating left-digit bias, my guess is that even with this amazing paper you've written, which now has Lyft and Uber in line, there's still lots of places, mom-and-pop shops, where this isn't being incorporated, and we are encountering pricing that doesn't factor in left-digit bias.
Devin Pope: Yes.
Katy Milkman: Still, I take your point that we shouldn't sweat the small stuff. Who cares if you're leaving 25 cents on the table when you take a taxi ride or buy toilet paper? But I will say I messed up when buying a house with left-digit bias in a negotiation, which is to this day one of the most humiliating things in my past. We were outbid by someone who knew we were going to pick a round number and picked a little above a round number. I'm like, "God, I played that game in game theory. How did I mess that up?" But I did, right? I like the house I got, confirmation bias and all that. So I do think there are places where we make big decisions and left-digit bias matters.
Devin Pope: I think you're exactly right. The reason why this is important, for Lyft, is they're doing so much volume, and it's a little tiny bit times a really big number. You're right though. As a consumer, you might want to be a little careful when you're making a really big purchase that involves a number. A diamond or a house or something like that could be in that camp. Yeah, you might be able to save a fair bit by being a little careful in those cases.
Katy Milkman: Or get the house in the first place.
Devin Pope: Yes, exactly.
Katy Milkman: Yeah, OK. Devin, this is so helpful. I'm curious if you do anything differently or think about anything differently after doing all this research on left-digit bias in your own life. Has it led you to shop differently, or are you not sweating the small stuff?
Devin Pope: Yeah, I try not to sweat it too much. I think it makes me notice … or let me share one thing that is interesting. Here is what Uber is doing right now with their pricing. I just pulled up my activity. Let me just read you the prices for my last, say, 10 rides. I took a ride for $28.95, $31.93, $44.96, $31.95, $5.93, $31.96, etc. So what they're doing is they're not pricing at the 99-cent mark. They're pricing it somewhere between 90 cents and 98 cents is what it appears that they're doing. I've never talked to Uber or anything, but it's very clear from just my activity level alone what they're doing.
My guess is there's basically no consumer out there that has ever noticed this. Now, I notice it every time I take an Uber ride because every single time I'm looking at those digits, and it's somewhere in the 90-something range, I'm like, "They're trying to capture a little of extra value from each customer," and then I don't worry about it. Yeah, so I walk around noticing left-digit bias all over the place, and then I just try to convince myself to focus on the things that maybe matter the most.
Katy Milkman: Devin, I so appreciate you taking the time to talk to me today. Thank you for doing this. It was really interesting.
Devin Pope: Thank you, Katy. It was fun to be here.
Katy Milkman: Devin Pope is the Steven G. Rothmeier Professor of Behavioral Science and Economics at the Booth School of Business at the University of Chicago. You can find links to his research on left-digit bias in the show notes and at schwab.com/podcast.
Any major purchase can be fraught with emotional and psychological pitfalls. For tips on navigating the especially tricky decision-making process of car buying, check out the recent Financial Decoder episode "Are You Making One of These Car Buying Mistakes?" You can find it at schwab.com/FinancialDecoder, or just search for Financial Decoder in your podcast app.
Left-digit bias is a bias to look out for when you're making a big purchase. If you're buying an engagement ring, a used car, a house, or making another large outlay, then what we've shared today could help you get a real deal. You can get a bargain on a ring if you're willing to buy that 1.99-carat diamond instead of insisting on 2.0 carats. You can get a bargain on a car if you opt for 80,000 miles in the odometer instead of trying to stay below that round number. If you're in a bidding war for a house and get just one final bid, for goodness sakes, bid just above a round number that other bidders are likely to select.
You might also think about this bias if you find yourself getting important medical advice and have just celebrated a round number birthday. Consider asking your doctor if they think someone a few years younger or older might be advised to pursue a different course of treatment. If the answer is yes, keep that option on the table. Or maybe you've taken an important test, say the SAT or the GRE, and gotten a score just below a round number, say 1390. It might be useful to retake the test and aim to bump yourself above 1400 so you can benefit from left-digit bias. But when you're making small decisions, like whether to buy a new song or hop in an Uber or Lyft, Devin's advice is spot on: Don't sweat it.
You've been listening to Choiceology, an original podcast from Charles Schwab. If you've enjoyed the show, we'd be really grateful if you'd leave us a review on Apple Podcasts, a comment or a rating on Spotify or YouTube, or feedback wherever you listen. You can also follow us for free in your favorite podcasting app. If you want more of the kinds of insights we bring you on Choiceology about how to improve your decisions, you can order my book, How to Change, or sign up for my monthly newsletter, Milkman Delivers, on Substack. Next time I'll speak with Berkeley Haas professor Ellen Evers about a clever life hack designed to help you move on from difficult or painful events while getting more joy from positive surprises. I'm Dr. Katy Milkman. Talk to you soon.
Speaker 12: For important disclosures, see the show notes or visit schwab.com/podcast.
