Odd Lots - Corporations Learned The Maximum Amount They Can Charge For a Product

Episode Date: June 3, 2024

What's the price of a hamburger? Well, it depends. Are you making the purchase on the spot? Did you order ahead using an app? Are you a frequent customer of the burger chain? With inflation having surged at the fastest rate in roughly four decades, there's suddenly a lot more interest in how companies figure out the most that they can charge you for a given purchase at that moment in time. As it turns out, much of the economy is becoming like the airline industry, where there is no one price for a good, but rather a complex range of factors that go into what you're willing to pay. Thanks to algorithms, apps, personalized data, and a bevy of ancillary revenues, companies are increasingly learning how to not leave any pennies on the table. So how did this come about? What exactly is happening? And when did everything become gamified? On this episode we speak with Lindsay Owens, executive director of the Groundwork Collaborative, and David Dayen, the executive editor of The American Prospect. The two of them have put together a special episode of the magazine that's all about the world of pricing strategies, the tools companies use, and the industries that exist to help companies figure out what they can charge. We discuss what they learned and the impact this is having on the economy.See omnystudio.com/listener for privacy information.

Bloomberg Audio Studios. Podcasts Radio News. Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Wisenthall. And I'm Tracy Allaway. Tracy, you know what I feel is become a common Twitter conversation that I've seen happen a bunch of times? This could be anything, but go on.

Someone tweets like, oh my God, I just paid like, you know, $14 for a hamburger in at this McDonald's. And then someone else goes, well, actually, you can get it for $3.99 right now if you just use the app. Yes. I've seen this many times. Both of them are not wrong. Right. But it is crazy. First of all, I'm so thrilled that we're finally going to do a price pack architecture episode. That's basically what this is, right? All these different strategies when it comes to how companies are actually pricing their goods. But I feel like McDonald's has become a very, very good example of this particular behavior. And at this point, as you pointed out, it is well known that if you just roll up to a McDonald's and, you know, order at the drive-thru or

in the store, you are going to be paying a higher price than if you used the app and ordered on there. And they have tons of discounts. The discounts are almost gamified at this point. Like, you know, you check in on different days and you can get different things and they're constantly changing. Oh, and also, they have an actual game that if you play, you get loyalty points that turn into discounts. But the thing that I think is so fascinating about all of this is it throws up really interesting questions around fairness. So is it fair that people are paying two different prices, depending on the way that they are actually buying the thing? I think the other thing that's remarkable in all the price conversations is people seem to think that one person paying a higher

price is really unfair. But on the other hand, everyone likes discounts. Like, if the lower price comes in the form of a coupon, people get really excited. It also throws up interesting questions about data privacy. So the reason McDonald's wants you on the app is so that it can collect your data and it gives you a lower price in return for that. And then thirdly, it raises all sorts of interesting macroeconomic questions, right? If companies are becoming more strategic, more differentiated in the way they're pricing their goods, what does that mean for things like inflation? What does it mean for traditional interpretations of the way inflation works?

Is it just, you know, unemployment, supply, demand, that sort of thing? Right. Like companies basically just getting better at figuring out the maximum price they can charge for something. Wait, I have a personal question for you, Tracy. I've never asked you this before. Are you like a points person like when it comes to hotels and airlines and stuff like that? No, I'm not. And I feel like I'm basically too lazy to.

sign up for a lot of things. But I will say McDonald's got me. I do have, I do have the app. And I have, as a result of the app, ended up ordering, like, insane amounts of junk food because I'm just like, oh, I can buy two things of French fries instead of one. So why don't I go ahead and do that? Yeah, I'm so lazy. I am not a points person. I'm not an app person. I've never like been a miles person. It seems like I probably should. I don't travel that much, but probably enough that I should, like track this stuff and have a favorite hotel that I go to in every town or have a favorite airline. All airlines seem the same to me. They all seem sort of various versions of kind of unpleasant, but I'm not like optimized for that at all. But it feels like to some extent what we're talking

about is this sort of widespreadness across many industries of what the airlines have figured out for decades. Absolutely. And also Uber is the classic example with dynamic surge pricing. And you can remember earlier this year when Wendy's mentioned dynamic pricing in its earnings call, the world absolutely went nuts. And then they kind of backwalked on it. But I mean, my argument is like search pricing in fast food is kind of already there, right? You know, the difference in how you're ordering at McDonald's is a variable of how much value you place on your time and your convenience. And so it's kind of already happening.

And I think this is such a fascinating topic for many, many reasons. But I am so, so happy that we are finally doing this one. I am too. I'm going to just lay my cards out on the table right here. It's like, I don't know. I kind of get surge pricing for food. If a bunch of people all jam up at the same time, maybe like raise the prices so people spread it out a little bit.

In this conversation, I will play the role of the devil's advocate who is like, yeah, I'm okay with like, you know, differentiated prices. Joe, this is stupid. It's stupid. I'll tell you why. because surge pricing was supposed to invite more supply into the market. So the idea was that you incentivize more drivers to get out on the street if they can earn more money. You're not going to get that with fast food.

You think there's going to be an immediate supply response in hamburgers? But there could be demand destruction, which I do think is part of the Uber thing, which is that, yeah, you can't really have enough cards if everyone all wants to take a Uber at 1201 new years. Like you have to raise the price such that some people like, I'll take the subway. or whatever. Anyway, enough what I think. We don't have to debate. We don't have to debate this. We really do have two perfect guests to talk about this topic, about how companies are getting better and better at personalized pricing, finding the absolute most they can charge for something at any given moment. We're going to be speaking with Lindsay Owen. She is the executive director

of the Groundwork Collaborative and the author of a forthcoming book called Gouge that will be some time out in the future. And we're going to be speaking with David Dayan. He's a He is the executive editor of the American Prospect magazine. And the American Prospect has a full edition of the magazine coming out on June 3rd that is entirely devoted to the world of pricing and how companies do this and the history. And both of us have read the whole edition. The magazine is fantastic. They've worked together on this. It is a really interesting body of work.

I think it'll be an important thing that a lot of people read. So excited to have Lindsay and David on the show. So thank you so much for coming on Outlots. Thanks for having me. Thanks for having us. Maybe, David, I'll start with you as the editor at the American Prospect doing this whole edition of the magazine on this topic. But both of you come in.

Why is this something, I mean, you know, Tracy and I are both interested in this. But why is this something that is worth an entire magazine? Well, if you look at any poll that is talking to voters coming up in this election, inflation is the number one or right near the number one issue. So we have looked at this for a while. Lindsay, obviously, and her team at Groundwork has done a great job. And they came to me and said, you know, we really want to put something together that looks at pricing kind of in a holistic way.

What we know has happened is that after the pandemic, there was this inflationary episode, and markups and margins for companies went up. And they kind of stayed there even as inflation has eased. So we wanted to try to interrogate why this is happening and whether we've hit sort of a new era where these pricing strategies for a variety of reasons have become more widespread and companies have become more experimental, let's say, in trying to engage in this process of maximizing willingness to pay among their customers. And so we think we've come up with kind of a thesis for this. And then the issue lays out that framing of why this is happening and then looks at all of the strategies that are really being put to bear. You've mentioned some of them in the intro, whether it's surge pricing or dynamic pricing or junk fees or using subscriptions to kind of, we call it the inattention economy, get people to sign up to enough subscriptions so that they forget that they have. them. You know, there's credit pricing, there's price fixing through algorithm that we're seeing

more and more. And then there's this whole kind of next frontier of using digital surveillance and isolating customers enough so that you can personalize prices, which is really kind of where I think a lot of businesses see a lot of opportunity, the idea that my price isn't the same is your price. So, you know, we lay out these strategies. I think it's important to see, you know, what companies are up to. And if it is deemed unfair or deceptive, what government, what role they have to play in maybe doing something about it. So I want to get into everything that you just mentioned, especially the sort of data privacy and algorithmic pricing points. But before we do, I think there's a tendency on this topic when you're talking about the idea of companies maybe driving up their prices, maybe that feeding into inflation.

Lots of people use the word greedflation here. I tend not to do that because the immediate reaction you will get. Joe, you mentioned well-worn Twitter debates. But the immediate thing that happens is, oh, companies didn't get more greedy all of a sudden. They were always greedy. And so people tend to wave this theory away. But could you maybe talk about concrete evidence we have that companies are becoming more sophisticated

when it comes to pricing or more willing to experiment with demand elasticity in recent years? Is there concrete numbers that back that up? Sure. So I think one of the most interesting places to look here to answer your question is actually the burgeoning industry, of algorithmic pricing companies and specialists, right? So, you know, there was just this really interesting report

that dropped last month from the Boston Consulting Group. And the first sentence of the report is retailers are in a new age of pricing, and they need a new set of tools. And when you look through the report, what you see is really the consulting group outlining this new era of pricing and how companies need to increasingly be working with algorithmic data specialists and data service providers to compete. And so there's just this flourishing cottage industry of companies like revionics and

demand tech and others who are basically bundling up competitors' data using sort of surveillance targeting and geo-analytics to take in competitors' data and then spitting out for the retailers' advice and recommendations on how to keep prices higher for faster and longer. And so when I get a question like this, I really just like to go to the quote. from the companies themselves, right? So what are they saying that they're selling? What are they recommending to these companies? And, you know, some of the examples that we have, I think, are quite stark.

You can go through just a couple of them. You know, companies recommending, quote, faster lasting implementation of price increases, recommending that they can help companies ferret out when they inadvertently keep prices, quote, too low for too long, help folks, quote, more quickly react to competitors' pricing, and also ensure that their price hikes, quote, stick, right? And so what you're seeing is a sort of cottage industry of companies

who's really pushing retailers to go higher, faster, and for longer on prices. And I think that really matches what Dave mentioned up top, which is that, you know, the sort of age of cost cutting has maybe hit bone. And now we're in this sort of age of recoupment and where revenue maximization and pricing is really critical to the game. And big data and new technology. has really allowed this pricing to go high-tech

and these new strategies to really flourish. And so I don't like to make too many predictions, but my instinct here is that this is really the very, very beginning of this new era of pricing. And I think, you know, the amount of online shopping that folks did during COVID-19 has obviously allowed folks to collect more and more data on consumers. And I think we're just really at the tip of the iceberg here.

We're just sort of starting to see these strategies unleashed across industries. As a journalist, I really like data and I like companies that gather data and publish data on their corporate blogs about what's happening with this. And it's been certainly nice over the last several years to see more of them. Talk about, though, like how this data is actually used. Because one of the themes that comes up in this edition of the magazine is that when the data is out there in public, then companies can see more quickly, oh, we're actually underpricing or actually everyone else is charging more, and we can see this more easily than perhaps in the past when companies were trying to get comp data. Talk about the sort of like the role that

data aggregators have and maybe the specific industries that use this data to get better at pushing price. Yeah, I mean, I think we can talk about it in a couple different ways. The first is this use of what has been called algorithmic price fixing. So we see these aggregators that have arisen, and it's not a very new thing, actually. The airline industry has this thing called ATP Co, the airline tariff publishing company. And it's been around since I believe the, since deregulation in the 1980s. And they collect real-time data on every fair that's been published in the U.S. and around the world. And all the companies who subscribe to ATP Co can look at that and know when to adjust their prices in real time. The Justice Department actually looked at this

as a collusion operation, but they allowed it to go forward in the 1990s. Some of this data is proprietary. There's a lawsuit right now active between the Justice Department and a company called Agristats, which has also been around for quite a while. And this company collects real-time proprietary data from all of the meatpacking producers in a given market, whether it's pork or poultry or chicken or turkey. And they put all this data in these giant books and they give them out to these various competitors, which now have basically a setup of everything that their competitors are doing, including their price, including their supply, including every single thing part of their market. And now they can know that, oh, I can

probably raise my price because I'm under price relative to my competitor, but I won't lose market share because my competitor is charging more for this product. And it has the tendency to ratchet prices upward. We've also seen this in rental markets with a company like Real Page, which again, goes out to landlords in a particular area, collects all of their pricing data, all of their supply data, distributes it broadly among these competitors. and allows them to raise their prices in tandem throughout the market. We know that price fixing has been kind of a bedrock of antitrust legislation. If you have evidence that three people, executives, have gone into a room and said,

we're going to raise our price by X amount of dollars, then the Justice Department will step in and they will put a lawsuit on those various people and put them in jail potentially. If you do it through an algorithm, which is the way that Real Page and some of these other organizations operate, it's sort of more of an open question as to what the legal system will take from that and actually look at prosecuting it. But there's no real difference between algorithmic price collusion and in-person price collusion. And so that is one of the ways by distributing, aggregating that data across an entire industry, and allowing those companies to have a window into that pricing.

That's one way that this gets done. We can talk about the other way, which actually interacts with the McDonald's app, which we wrote about pretty extensively in this series. Go for it. So the McDonald's app is put together by a company called Plexure. And Plexure works with IKEA. They work with 7-Eleven. They work with White Castle.

And the reason, as you correctly said, Tracy, that McDonald's gives discounts on the app is because they want to get on your phone. They want to get on your phone and be able to figure out what you're doing on that phone, where you are at particular times of day, what your food preferences are, what your ordering habits are, potentially what you're using to pay for those things and your financial behaviors through that. They're aggregating a bunch of data about you. And we had one of the slides from this presentation. that Plecture put together that shows how they are using this data. And one of the things that they were using to make predictions

about what people would be willing to pay was their payday. So you can imagine how you can use this. If the app knows that you get paid every other Friday, it might give you a $3 McMuffin on Thursday, but when Friday you have some money in your pocket, it might raise it to $4, right? If it knows that it's cold out, it might raise the price of hot coffee. If it knows it's hot out, it might raise the price of the McFlurry.

Often, Plexure combines this data that's within the app, like what they call first-party data, with additional data about you through what is called an identity graph that aggregates both, you know, stuff you're doing on the app with your email, with your email, with your, your social media, with your browser, with your subscriptions, with your other app downloads, with your travel history, with your retail history, all of these other things. And the predictive power of that is such that you can pinpoint what you're going to buy maybe before you even know, and therefore you can target prices accordingly. So I think we're at the beginning of this where they're trying to discount things and get people on the app and

get people used to ordering on the app. But what that has the effect of doing is isolating the consumer. If you're buying through an app, there is no public price. There's just a price for you. And there are other ways that, you know, through online commerce or through deals that are done through a smart TV, where the customer is isolated and doesn't really know what other people are paying for the same product. Because what personalized pricing has always run into is is this sense of unfairness. And if it's very apparent that I paid $3 and the guy behind me in line paid $4, I'm going to be mad about that if I'm the guy paying $4.

Why did I pay more than the other guy? But if you don't know, if it's through your television, if it's through your phone, if it's through your web browser, and you don't have any idea what the other person paid, you're just not going to know to be upset, right? So I think that is the frontier that we are in many ways moving toward. And it's fascinating and maybe, you know, to some people, dystopian reality. I was literally about to use that word.

Oh, sorry. I just wanted to add, I think it's just this really interesting period in history as well, because, of course, this is sort of where we started, right? You know, people haggled. There was no set price for a good. You went to the bazaar. You went to the market. And, you know, they took a look at you and maybe looked at your share.

shoes. And depending on what they ate for breakfast that morning, they decided what to charge you. And in the United States context, you know, there were a few people who didn't think that was right. You know, the Quakers in Philadelphia felt that this type of price discrimination violated their religious principles that sort of every man was equal under God. And John Wanamaker, the Philadelphia department store owner, similarly had concerns about this. And, and by the way, a business case in a large department store, you know, haggling takes a little time, Like you want to move people through, like pick up your scarf, pick up your lipstick, get in line and check out. And he started the price tag, right?

His sort of credo was one price and goods returnable. He also sort of invented the money back guarantee and allowed folks to start returning goods that they weren't satisfied with. And so, you know, for a long time we've lived in a world throughout all of the 20th century where there was by and large one price for goods. You know, that was sometimes discounted, sometimes marked up. But, you know, you went into the supermarket or the department store. And, you know, unless you got there on the wrong day before the sale, like you paid the same amount as your friend did for the same good. And we're really in some ways returning to the bizarre or the marketplace

because of new technologies that are enabling companies to more aggressively tailor price discrimination. So this raises points about fairness and also privacy, data privacy specifically. And David, you mentioned the. word dystopian there. And I was thinking back to, I used to cover the banks at the FT. And I wrote a piece back in 2015 about exactly this theme. So the idea of financial companies using new types of data, new technology to basically build proxy profiles of their customers. And I remember I was out in San Francisco. I was talking to this new startup lender. They don't exist anymore. So I think I can tell the story, but they were talking about the types of data that they could collect from their

customers. And I really think people don't understand the extent of what is available to companies, but they were talking about how if someone was applying for a loan on their website, they could use a sort of slider to decide what amount of money they were asking for. So anything from, I don't know, $100 to like $10,000, something like that. And the company could track how fast they were moving that slider. And it was supposed to be an indication of how sort of, what's the word, impulsive the customer was. So if you move the slider really fast, you're probably not a very good credit risk. But if you're sort of like considerate or you immediately move it to one point and leave it there, maybe you're a better risk. And then in addition to that, when it comes to finances

and extending credit, there are obviously protected classes out there. So, you know, race, gender, I think age as well, that companies are not allowed to discriminate against. But when you have all this data, you can basically build proxy profiles of people. And there are certain indicators of whether or not someone is white or black, depending on like what type of browser they're using, what type of phone, where they are, et cetera, et cetera. How does our current legal system view some of this personalized pricing? What's that discussion like at the moment? Yeah, I mean, I talked to Lena Kahn for this issue.

She is the chair of the Federal Trade Commission. And, you know, she said that there was one point in which this idea of personalized pricing or what, you know, some people that I talked to called surveillance pricing, that it was just sort of a theoretical exercise. It was something that economists liked to take a look at to see what. whether it created surplus value or not. And now we're reaching this kind of terrifying reality where actually you collect enough data that you can do it.

One of the more disturbing things that we saw in this, in going through the research for this issue, was this study out in Belgium where they looked at Uber prices and they took two people in the same place going to the same destination. and it noticed that it charged more if the individual's phone battery was low. And what the surmise is is that that's a proxy for you're desperate.

You need a ride pretty much right now because your battery is going to run out. And so we can charge you more on that point. And I talked to a University of Chicago economist that said, well, that might be a proxy for it's late in the night. but that's not the way that they designed the experiment. It was two people at the very same time. One had 84% on their battery and one had 12%. And the 12% person was charged more from the same location going to the same place. So this kind of stuff just wasn't available a while ago.

And one question is what the legal system is going to do about this in terms of court cases. Talking about the algorithmic surge pricing that I mentioned, there was a court case over a company called Rainmaker, which was working with Las Vegas hotels, and once again, aggregating prices, showing these particular casino hotels a picture of the market so that they could raise their prices. And the judge threw out the case because he said, well, they were only recommending certain prices. They weren't mandating it, even though the statistics that Rainmaker even submitted, say that 90% of the time the recommendation is taken and that they strongly encourage people to take the recommendation, otherwise they cut them off the service. So how the legal system is going to

react here is an open question. But lawmakers and policymakers do have tools here. There are tools against unfair and deceptive practices that the FTC has and also, you know, agencies like the Department of Transportation has with respect to the airlines, there are other various anti-price gouging tools and things of that nature. And there are also antitrust tools because the one secret sauce here is market power. The idea that you can just sort of willy-nilly raise your prices in a competitive market, that's going to create a situation where a competitor is going to undercut you because they know that you're charging too much and the market will sort of rebalance itself. If you have a tremendous amount of market power and therefore pricing power,

you have the ability to continue this without kind of worrying about whether your customers will go away. You've created a moat around your business. So that's a key facet of this as well. If competition policy moves towards a place where these markets suddenly have more choices for customers, then these pricing strategies lose a little bit of their power. One thing I would just add is, I think we're really in a new legal frontier when it comes to personalized pricing and price discrimination and protection of protected classes. As you point out, any set of pricing that relies in whole or in part on geography in the United States, given the extraordinary segregation in the United States by geography,

is ultimately going to have a racial bias intended or unintended, right? And so, you know, there have been some really interesting studies. There was a study of Uber and Lyft rides in Chicago, and they looked at like over 100 million rides, I believe. And what they showed is that, you know, if either the destination or the pickup point had a higher percentage of non-white residents, low-income residents or low-income residents, you saw higher fares. Now, of course, supply and demand can play a large role in that. But these overlays around geography are going to be interesting to consider. And the next thing I would just say on this point is, you know, when you think about surge pricing, right, and you think, okay, well, in an area, you know, where there's sort of less supply, you might want to ration by price, if you're in a low-income area where there's only one store and there's not a lot of competition, surge pricing is going to hit that space harder because there's just going to be low supply. and that's likely to be a low-income area, a minority, or a black or brown area as well.

And so I think the overlay of sort of the geography of concentration in the United States, the geography of segregation in the United States, and personalized pricing is absolutely going to create some winners and losers. And I think the question is whether or not existing law is up to the task or whether or not new laws will be required to protect consumers from discriminatory practices and tracing. You know, I mentioned, by the way, that I play devil's advocate here, and I would just say, if my battery on my phone was about to die, I'm fine with paying a few extra dollars to get the car over the other guy. I'm just going to throw that out there. But actually, Lindsay, I want to follow up on this point because you're leading to something that I was going to ask about, which is that, you know, one of the things we're sort of talking about is a time tax, right? Like some people are going to just roll up to the McDonald's, and some people are going to take the time. to download an app and put in their data.

I am not one of those people. I'm not very well organized, et cetera, but I probably in theory, if I really cared, like, would have, you know, the time to, like, set all these things up and do the miles and everything. Talk to us about, like, the disparate impact

of basically, yes, there are better prices out there if you're willing to jump over these hurdles and take that time and be fully just, like, aware of all of the different availability. It seems, like, difficult to me because I'm disorganized, but basically, like, targeting different sets of populations based on how informed they are and the capacity that they

have to deal with all of these different rewards programs and things like that. Yeah, I don't even have airline points because I'm too disorganized to keep up with accounts for Delta and American and things like that. So I hear you 100% on that point. Look, I think it's a really interesting question, right? There is this temptation to sort of figure out how you can hack personalized pricing or use a VPN to get around dark patterns or how can I beat AI and get a good discount. But I think really what the issue that we put out of the prospect shows is that increasingly in almost every area of your life, right, if you look at your household budget and the rental

market where Real Page is helping landlords fix prices in the grocery store for your family vacation, where you're having to deal with algorithmic price fixing in both airline costs as well as hotels, you're up against the machine here. right? And I honestly don't know that even consumers with considerable time are able to coupon clip their way out of this one, right? I mean, imagine a world in which you hear from your friend that there's a discount on, I don't know, Cheerios. I'm buying a lot of those for my toddler right now at the Kroger down the street. But, you know, they've installed electronic price tags on the shelves. You know, by the time you get in your car and drive up to the Kroger, like the price of Cheerios has already changed, right?

And so I think this is not a space where even folks with sort of like a lot of time, you know, who used to sit down and get the Sunday papers and pull together three sets of coupons and organize them in a book and go to three stores to get three different deals, you know, even that is starting to look a little quaint and antiquated in a space with real-time pricing and in a space where there are companies using, you know, predictive AI to move prices, you know, instantaneously, right? I just don't know that the consumer is going to win this one. I think we ultimately have to decide which pieces of this we're not happy to deal with,

but we think they're legal, which pieces of this are illegal and we should go ahead and enforce the law. And then honestly, which pieces of these items are unfair and we just don't like it. And maybe if enough of us are focused on how unfair they are, we'll see the next wantemaker coming back in and saying, hey, guys, Like, I have the ability to use dynamic pricing, but like, you know, what you get when you come to Lindsay's store is like one freaking price. It may not be the lowest price, but like, I promise you, you and your neighbor will pay the same price, right? So I think there are a number of ways that this unfolds. But, you know, I think that some of it is absolutely already illegal.

Some of it probably should be illegal. And some of it is just maybe unfair and uncomfortable. And I think it's okay for consumers to think things. are unfair that are legal. That's an opinion and a belief and a value we can all hold, and we can try to push for shopping to look different. Right. And also, I mean, it's pretty obvious to me that if you are, you know, a poor single mother working two jobs, you are going to have less time to try to game the system. And so you're not going to be able to find the types of deals that maybe other people with oodles of spare time can find. But there's another aspect of unfairness here

which we haven't really discussed just yet, which is in addition to seeing different prices. And actually, I would love to know why it seems that like people that are coded as poor by algorithms often end up being charged higher prices. So I'd love to ask you that, first of all. But then secondly, it feels like all these proxy profiles of customers where you can see their past behavior, you can see certain demographic info, that also feeds into advertising, right? So the world that a poor person might live in based on the ads that they are seeing around them is very different to the world that a wealthier person is seeing. So the poor person is probably going to see things for payday lenders or, you know, buy now, pay later type stuff. And the wealthy person is going to see ads for, I don't know, brokerage accounts or luxury waterfront property.

And that ends up feeling very unfair to me as well and perhaps exacerbating inequality problem that. we currently have. Yeah, I mean, the first really comprehensive study on why this phenomenon of poor Americans paying more happens was published in 1963. So this is nothing really new. And we see it in some of these personalized attitudes. There was a story several years ago about staples on their online products offering different prices in different geolocations based on the IP address. and the areas that saw the discount prices had higher average income. And, you know, ability to pay and willingness to pay are two different things. And I think that's an important concept to know here.

Because sometimes they get conflated. Sometimes economists say, well, actually, personalized pricing is a great thing because poor people will be able to access goods that if there was one fixed price, they wouldn't be able to access. And they're making an assumption that it's, all based on ability to pay, that the way that a personalized price will go is that you'll be charged more as you go up the income ladder. But that's not really how it works. You know, it could be desperation as Joe just assented to that causes your higher price. It could be other

factors like this being a basic necessity that determines the higher price. And so the willingness to pay is calculated under a number of different. factors. It could be that the algorithm knows that you only have an hour between jobs or while you're going to school to grab some lunch. And so they're going to send you or serve you an offer that is more in that time of day when they know that you have to eat and you're out and about and that's where you're going to spend your dollar. So there are a whole number of ways where this does not look like you just pay more if you have more, you know, resources. Willingness to pay is a very different concept.

One interesting thing about the staple study that Dave mentioned that I think raises an important sort of macro point about this entire world of pricing strategies and tactics is that, you know, corporate concentration and consolidation undergirds it all and facilitates and accelerates it all. And so the reason that rich people who could afford to pay more for things at Staples, right? I mean, as a percentage of your budget office supplies is not large if you're wealthy. The reason they were getting better deals is because there were more

competitors to Staples in wealthier geographies, right? Whereas lower income folks were paying more at Staples because Staples knew they had them over a barrel, right? And so the corporate concentration overlay is key here. And it is key in one other way as well, which is really featured prominent in the issue, which is that increasingly the business case for mergers is data. So, you know, we highlight the example of Walmart buying Vizio. Why is Walmart buying a TV company? Well, they're not buying a TV company. It's a smart TV manufacturer masquerading as a media company, right?

They're buying streaming data so that they can pipe Walmart advertisements into your home, and so they also can collect data on sort of what you're watching and what you're clicking on. Similarly, in the piece, you know, there's considerable speculation that one of the major motivations for the Kroger Albertson's merger is the consumer data. And, you know, the grocers are making just as much money selling your data to the highest bidder as they are on selling you Cheerios, right? And so I think the data, the value of the data for companies and the interlay with consolidation, both as a motivator for consolidation, but also as something that you can just do more aggressively. if you aren't worried about competition is a key piece of why pricing looks different today. That's really interesting about the Kroger Albertsons. It's come up a few times because now, of course, with AI, like all these companies are just desperate to get any fresh data.

And people have legitimately made the case. Actually, Kroger's is an AI play because it just has so much unique data that no one else has. So that makes a lot of sense. I have one more big question, which is, you know, I started, we mentioned in the intro, the one industry that has been doing this forever, or it seems like, is the airline industry. And both of you mentioned some of these third-party consultants that are sort of bringing some of those practices to other industries. Can you talk a little bit about that further? How direct or how bright is the line between what the airlines have been doing with frequent flyer miles for decades? And then that sort of migrating over through consultants, et cetera, into other industries realizing

that they can more or less do the same thing. Well, it's really interesting because we had, you know, a number of different authors write these different pieces. And, you know, I was the editor and they all came in. And it seemed like every single piece went back to the airlines initially as kind of the originator of a lot of these strategies. There is a consultant called Idea Works Company. And they've been around for a while. The guy who runs it is named Jay Sorenson. And for one of these articles, we actually talked to.

them. And it's not only that Ideal Works Company presents these reports and research, mostly about junk fees or about ancillary revenue is what they call it. They even pulled this thing called an ancillary revenue master class, which literally is a junk fee boot camp that explains, they bring in executives and they tell them, here is how you can raise money by adding different various fees onto things that used to be bundled with the ticket fare. And so now we have baggage fees and we have change fees and we have fees if you want a better seat with more leg room. And all of this comes from sort of the brainchild of Idea Works company, which sends these reports that cheerlead when ancillary revenue numbers go up, it's become a huge business for the

airlines to unbundle their tickets and add all of these extra fees, basically making your situation in air travel miserable unless you pay your way out of it. And so we've seen that there. We see it an algorithmic price fixing. And all of these strategies started with the airlines, or at least some of them, but they've migrated. They've moved on. Like in the junk fee example, one of my favorite things in the issue, there's this company called suburban propane. Obviously, they sell propane to various people, whether they use it in camping or whatever they use it in. And they have a fee schedule on their website. And I'm just going to read what the fees are. They have a safety practices and training fee, a tank rental fee, a transportation fuel fee, a restocking fee, a tank pickup fee,

a minimum monthly purchase fee, a system leak test fee, a reconnect fee, a will call fee, a forklift minimum delivery fee, a diagnostic fee, an installation fee, an early termination fee, an emergency special delivery fee, a late fee, a return check fee, and a meter account maintenance fee. And I'd like to say that was an outlier, but I'm not sure it is. We are seeing these add-on fees in all sorts of industries. It originated in the airlines, and now it's gone every. And you see the Biden administration actually taking this up as a cause. The term junk fee was kind of invented or coined by Rohit Chopra, who's the director of the Consumer

Financial Protection Bureau. And they're trying to attack this issue. The Federal Trade Commission has put out a kind of ban on junk fees, which is more of a disclosure rule saying you have to do all upfront pricing. and the CFPB has tried to ban or cap credit card late fees, for example. We're seeing now kind of a politics being created out of these different pricing strategies and an attempted pushback on them. I have just one more question, which is going back to the introduction and the conversation

between myself and Joe and the implications that this has for macroeconomics. If we think that companies are becoming more sophisticated in their pricing, if we think that we're seeing, I guess, late stage capitalism meet a technological revolution that creates the ability to have more sophisticated pricing, what does that mean for inflation? If maybe prices become more about data and algorithms rather than a function of supply demand or the Phillips curve. How do economists and central bankers actually handle that particular problem? I think it's a terrific question, and I'm not sure it's one that the central bank really is willing to handle just yet.

You know, one of the things we put in our introduction is this colloquy between Sherrod Brown, who's the chair of the Senate Banking Committee, and Jay Powell when he was doing a semi-annual report. And Sherrod Brown was asking Powell about these. pricing strategies. And Powell seemed very, very uncomfortable. He didn't really want to talk about it. He said, well, you know, search pricing, maybe it works out. Even for the consumer, it doesn't have an inflation impact because if they're not that many people in the store, you get lower price. And if there are people in the store, you get a higher price. But what he ended up on was saying

that pricing is incredibly important and we have to give companies the freedom to do it. So he really sort of disassociated himself from this issue. And I think it's a fascinating question that you raised, Tracy, that if we see supply and demand and the usual kind of reasons for pricing become a little bit less, I'm not saying it's going to be completely less, but a little bit less of a factor. And we see sort of pricing get a little bit unmoored from those traditional factors. then what does that mean for how the central bank operates? And I think our answer, and Lindsay can speak to this more,

is that it has to mean that we need more of a whole-of-government approach to these particular issues. And for many years, we've kind of outsourced any question about inflation to the central bank and to monetary policy. And I think policymakers have to understand that that might not do the whole job anymore and that there are other factors, and there are other agencies that can be brought to bear here. Yeah, policymakers are going to have to actually study individual firm behavior,

industry-level behavior, really start to get up to speed on new pricing strategies and tactics if they really want to understand what's going on in the economy. I think for many Americans, part of the reason why, you know, we haven't seen folks applauding inflation headed back to 2% is because the word inflation doesn't really capture everything, people are experiencing in this economy, right? Sure, inflation is a piece of it, but there's also just like plain old price gouging. There's also junk fees. There's also dynamic pricing. All of these different ways people are experiencing the economy when it comes to pricing

sort of isn't captured, I think, fully with the word inflation. I think it's why people are so unhappy with the economy today. There's a lot underlying the shift. You know, of course, these techniques preceded inflation, but they do seem to have been unleashed. yeast and hypercharged during this period of high inflation. And it'll be interesting to see sort of what happens in the future. But it sure seems like the genies out of the bottle here. And I think we're just going to see more of this type of activity rather than less. And I think that's why you're seeing this burgeoning sort of cottage industry of pricing data firms, right?

I mean, the handful of CEOs who thought they were just selling groceries, you know, need a firm to help them realize they're actually supposed to be selling data. And they need a firm to help them think through how to maximize. pricing in a world where cost cutting is hit bone and shareholders expect more and more returns. Like there's got to be a revenue play too, right? And a revenue play is going to be in part a pricing play. So I think we're in a new world here when it comes to pricing and the Federal Reserve is not known for being nimble or fast moving or particularly innovative when it comes to thinking about the economy. They've been sort of running a same playbook for a long time here, right? So I think

only time will tell whether or not they catch up. By the way, I checked out the sample two-day agenda of the Idea Works company Ancillary Revenue Masterclass, and it really is a boot camp on charging more. 10-15 coffee break, 10-30, top 10-10 things you need to know about ancillary revenue in airlines, 11, ancillary revenue boosts the bottom line, 12-lunch. It's really amazing. David and Lindsay, that was so fantastic. Really appreciate you both coming on Odd Lots.

Everyone should check out the June 3rd edition of the American Prospect. Really fascinating stuff on a range of topics. Great chatting with both of you. Thanks a lot. Thanks for having us. Tracy, I thought that was fantastic and there was a lot there. Actually, I thought Lindsay's point at the very end, I thought was a really great one because obviously people don't like higher prices.

And the inflation data, probably for better or worse, captures the general rise in prices over the last several years and the disinflation over the last couple of years. But then this idea that there's something else out there that's really annoying, maybe is a sort of polite way to put it, or like aggravating about this economy and this sort of psychological tax and feeling that to get the optimal price, you have to like download an app and all of this stuff that I think sort of compounds the aggravation of higher prices themselves. No, absolutely. And also just the point about, well, the genie's kind of out of the bottle. And maybe we are moving from an age in which it was all about driving costs. lower and building factories in places like China or Vietnam or wherever in order to lower your cost of production. But the thing that we saw from the pandemic was that A, you have supply chain issues and so that production facility can close. And then B, you can also make money by raising your

prices and selling less of your stuff. And this has been an ongoing theme on AllBlots. and we spoke with Samuel Rines about this, of course. And you can see the strategy going back to Lindsay's point at the beginning of the conversation on the earnings calls. This is something that CEOs very openly discuss and talk about. Totally. By the way, our producer Kale came through the reference, the 1967 book, The Poor Pay More by David Keplovitz, looks really interesting. And it hadn't really clicked to me David's point,

which is that there is sort of ability to pay. And yes, you know, the race, which in theory and practice have the ability to pay more, but then the sort of willingness to pay about like, okay, you're in a desperate situation. You need this. Or as Lindsay's point, like, you may only have in your area one competitor or wherever it is. And so the idea that ability to pay

is the only measure by which a company would set a price is clearly wrong for some reasons that are obvious once you hear them. I think that's such an important distinction. And then the other thing I would just tack on to that is going back to the advertising points. So, you know, depending on whatever proxy profile, the Algo is building about you, all the prices that you're seeing, all the offerings might be very different to someone who is better well off. And so you never even, maybe if you're living in a certain zip code and you have certain

demographics attached to you or certain buying patterns or certain credit scores or whatever, maybe you never even get ads for brokerage services, right? And so the idea of building wealth through the stock market is just something that you never encounter. And so all of that inequality becomes sort of codified. God, I'm depressing myself as I talk. Joe, this is depressing. Wait, are you a little bit less relaxed about some of this now? Please tell me you are.

I still kind of think I still think I would be happy to pay more for an Uber if my phone were going to run out. But there are many aspects of this that I find uncomfortable. Surge pricing does not bother me. same way other things do. I do want to attend an Ideal Works company ancillary revenue masterclass. Maybe we could do that one day. I do not. Let me just throw that out there. No, I mean, that list of junk fees that David was reading, we're like a hair away from them basically charging for oxygen in order to breathe, right? Like, we're almost there. That seems excessive. On the plane, it's like, does that thing fall out? Do you pay extra? To make sure. To make sure.

that the thing will fall out. Yeah. Well, the one other thing I was going to throw in is I know they talked about the Federal Reserve being slow to approach this. And to some extent, you know, it's such a thorny issue. As soon as the word greedflation comes up, people immediately start arguing about it. Maybe you could couch it in different terms, you know, price pack architecture, more sophisticated pricing, personalized pricing, and all of that. But I will say this is something that has come up in our conversation. conversations with Richmond Fed President Tom Barkin, where he talked, I think he might have even used the idea of genie out of the bottle, which is one thing that companies have learned from the past couple of years is that they can push price and experiment with demand elasticity. That's true. I think to David's point, what it says is that some of these things are like a whole of government approach. And so the idea is like also it's like the Fed does not have like tools to go after like junk fees or whatever. But yeah. I thought that was fascinating.

Shall we leave it there? Let's leave it there. All right. This has been another episode of the All Thoughts podcast. I'm Tracy Allaway. You can follow me at Tracy Allaway. And I'm Jill Wisenthall. You can follow me at the stalwart.

Follow our guest, David Dayan. He's at D. Dayan. And Lindsay Owens, she's at Owens, Lindsay One. And definitely check out that new edition of the American Prospect magazine. Follow our producers, Carmen Rodriguez at Carmen Armin. Dashel Bennett at Dashbot and Kel Brooks at Kel Brooks. Thank you to our producer. producer Moses Andam. For more oddlots content, go to Bloomberg.com slash oddlots,

where we have transcripts, a blog, and a newsletter. And if you want to chat with fellow listeners 24-7, go to our Discord.discord.g.g. slash oddlots. And if you enjoy oddlots, if you like it when we dive into price pack architecture, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely add free. All you need to do is connect your Bloomberg with Apple Podcasts. To do that, find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.