June 3, 2024 • 55 mins
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.
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Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of The Odd Lots Podcast.
Speaker 3 (00:22):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:25):
Tracy, you know what I feel is become a common
Twitter conversation that I've seen happen a bunch of times.
Speaker 3 (00:32):
Uh, this could be anything, but go on.
Speaker 2 (00:36):
Someone tweets like, oh my god, I just paid, like,
you know, fourteen dollars for a hamburger and fries at
the McDonald's and then someone else goes, well, actually, you
can get it for three ninety nine right now if
you just use the app. Yes, I've seen this many times.
Speaker 3 (00:53):
Both of them are not wrong, but it is crazy.
First of all, I'm so thrilled that we're finally going
to do 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.
(01:15):
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 through 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
(01:36):
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
(01:58):
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, y 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
(02:19):
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
(02:43):
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.
Speaker 2 (02:53):
Like companies basically just getting better at figuring out the
maximum price they can charge for something. Wait, I have
a personal question for your 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.
Speaker 3 (03:06):
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
(03:26):
don't I go ahead and do that?
Speaker 2 (03:28):
Yeah, I'm so lazy. I am not a points person.
I'm not an app person. I've never been a Miles person.
It seems like I probably should. I don't trouble 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
(03:51):
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.
Speaker 3 (04:01):
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 surge pricing in
fast food is kind of already there, right, you know,
(04:23):
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.
Speaker 2 (04:42):
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, differentiating prices.
Speaker 3 (05:01):
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 is 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 fastest.
Do you think there's going to be in a meaningul
supply response in Hamburgers?
Speaker 2 (05:20):
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 twelve oh one New Year's like,
you have to raise the price such that some people
like I'll take the subway or whatever. Anyway, enough, what.
Speaker 3 (05:36):
I think we don't have to debate.
Speaker 2 (05:37):
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
(06:00):
be some time out in the future. And we're going
to be speaking with David Dayan. He's the executive editor
of The American Prospect magazine, and The American Prospect has
a full edition of the magazine coming out on June
third that is entirely devoted to the world of pricing
and how companies do this in the history, and both
of us have read the whole edition in the magazine.
(06:21):
Is fantastic. They've worked together on this. It is a
really interesting body of work. I think it will be
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 Outlaws, thanks for having me.
Speaker 4 (06:35):
Thanks for having us.
Speaker 2 (06:36):
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.
Speaker 5 (06:52):
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
(07:13):
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.
(07:33):
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 williness
(08:00):
to pay among their customers, and so we think we
can 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
(08:25):
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
(08:49):
can personalize prices, which is really kind of where I
think a lot of businesses see a lot of opportunity,
the idea of 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,
(09:12):
what government, what role they have to play in maybe
doing something about it.
Speaker 3 (09:17):
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 greed inflation here. I
(09:41):
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 waive this theory away. But
could you maybe talk about concrete evidence we have that
(10:02):
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?
Speaker 4 (10:16):
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 sense of the report is retailers are in a
(10:36):
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
(10:58):
like Ravionics and Mantec and others who are basically bundling
up competitors' data using sort of surveillance, targeting and geoanalytics
to take in competitors' data and then spitting out for
the retailer's advice and recommendations on you know, how to
keep prices higher for faster and longer. And so when
(11:18):
I get a question like this, I really just like
to go to the quotes 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
(11:42):
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
(12:03):
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 recruitment
and where revenue maximization and pricing is really critical to
the game. And big data and new technologies has really
allowed this pricing to go high tech and these new
(12:25):
strategies to really flourish. And so I don't like to
make too many predictions, but you know, 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
nineteen has obviously allowed folks to collect more and more
data on consumers and I think we're just really at
(12:47):
the tip of the iceberg here. We're just sort of
starting to see these strategies unleashed across industries.
Speaker 2 (13:08):
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
(13:29):
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 are trying to get data. Talk
about this sort of like the role that data aggregators
have and maybe the specific industries that use this data
(13:52):
to get better at pushing price.
Speaker 5 (13:54):
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 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
(14:15):
it's been around since the I believe, the since deregulation
in the nineteen eighties. And they collect real time data
on every fare that's been published in the US 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
(14:38):
looked at this as a collusion operation, but they allowed
it to go forward in the nineteen nineties. 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
(15:01):
meat packing 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,
(15:22):
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
(15:45):
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
(16:08):
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
(16:29):
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
(16:53):
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.
Speaker 3 (17:11):
Go for It.
Speaker 5 (17:13):
So the McDonald's app is put together by a company
called Plexure, and Plexure works with Ikea, they work with
seven to 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
(17:34):
to figure out what you're doing on that phone, where
you are at particular times of day, what your food
preferences are, what you're 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.
(17:54):
And we had one of the slides from this presentation
that Plexure put together the other 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
(18:16):
that you get paid every other Friday, it might give
you a three dollars McMuffin on Thursday, but when Friday
you have some money in your pocket, it might raise
it to four dollars.
Speaker 3 (18:27):
Right.
Speaker 5 (18:28):
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 a mcflurry. Often, plecture
combines this data that's within the app, like what they
call first party data, with additional data about you through
(18:49):
what is called an identity graph that aggregates both you know,
stuff you're doing on the app, with your email, with
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
(19:09):
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
(19:30):
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
(19:52):
for the same product. Because what personalized pricing is always
run into is this sense of unfairness. And if it's
very apparent that I paid three dollars and the guy
behind me in line paid four dollars, I'm going to
be mad about that. If I'm the guy paying four dollars,
why did I pay more than the other guy? But
(20:13):
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 a fascinating and
(20:33):
maybe you know, to some people, dystopian reality.
Speaker 3 (20:37):
I was literally about to use that word.
Speaker 4 (20:39):
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 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
(21:01):
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 Wannamaker, the Philadelphia department
store owner, similarly had concerns about this. And by the way,
a business case in a large department store, you know,
(21:22):
haggling takes a little time, right, 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
(21:45):
all of the twentieth 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 the same amount as your friend did for the
same good. And we're really in some ways returning to
the bizarre the marketplace because of new technologies that are
(22:08):
enabling companies to more aggressively tailor price discrimination.
Speaker 3 (22:13):
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 twenty fifteen about exactly this theme. So the
(22:34):
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
(22:55):
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, one hundred
dollars to like ten thousand dollars something like that, and
(23:18):
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
(23:40):
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
(24:01):
profiles of people, and there are certain you know, 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?
Speaker 5 (24:21):
Yeah, I mean I talked to Lena Khan for this issue.
She's 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
(24:45):
economists liked to take a look at to see 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 to study out in
(25:06):
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
(25:27):
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 you know, I've talked to a
University of Chicago economists 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
(25:47):
two people at the very same time. One had eighty
four percent on their battery and one had twelve percent,
and the twelve percent 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
(26:09):
algorithmic surge pricing that I mentioned, there was a quirk
case over a company called rain Maker, 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 throw
out the case because he said, well, they were only
(26:31):
recommending certain prices, they weren't mandating it. Even though the
statistics that rain Maker even submitted say that ninety percent
of the time the recommendation has 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 as an open question. But lawmakers
(26:54):
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
(27:16):
also anti trust tools. Because the one secret sauce here
is market power. The idea that you can just sort
of willy nearly 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. In the market will sort of rebalance itself.
(27:37):
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 you know, competition
policy moves towards a place where these markets suddenly have
(27:58):
more choices for customers, then these pricing strategies lose a
little bit of their power.
Speaker 4 (28:03):
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.
You know, as you point out, any set of pricing
that relies in whole or in part on geography in
(28:24):
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 one hundred million rides, I believe, and what
(28:45):
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
(29:07):
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
(29:27):
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
(29:47):
not existing law is up to the task, or whether
or not new laws will be required to protect consumers
from discriminatory practices in tracing.
Speaker 2 (30:10):
You know, I mentioned by the way that I'll play
Devil's advocate here and I'll 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 I'm just gonna 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
(30:31):
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
(30:51):
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
(31:14):
that they have to deal with all of these different
rewards programs and things like that.
Speaker 4 (31:19):
Yeah, I don't even have airline points because I'm too
disorganized to keep up with accounts for Delta and America
and things like that. So I hear you one hundred
percent 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
(31:41):
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 fixed prices, in the grocery store for your family vacation,
where you're having to deal with algorithmic price fixing in
(32:03):
both airline class 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 coop on
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 from my toddler right now
(32:25):
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 ceios 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
(32:46):
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
(33:06):
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 Wanta maker coming
(33:29):
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 frickin' price. It may not be the lowest price,
but like I promised 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,
(33:50):
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 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.
Speaker 3 (34:08):
Right. And also, I mean it's pretty obvious to me
that if you are 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
(34:33):
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
(34:56):
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
(35:16):
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.
Speaker 5 (35:31):
Yeah, I mean, the first really comprehensive study on why
this phenomenon of poorer Americans paying more happens was published
in nineteen sixty three. 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
(35:54):
online products offering different prices in different geolocations based on
the IP address and the areas that saw that 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
(36:14):
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
(36:36):
you'll be charged more as you go up the income ladder.
But that's not really how it works.
Speaker 3 (36:42):
You know.
Speaker 5 (36:42):
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
(37:03):
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 and
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 dollars.
(37:24):
So there are a whole number of ways where this
does not look like you just pay more if you
have more resources. Willingness to pay is a very different concept.
Speaker 4 (37:37):
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 at all and
facilitates and accelerates it all. And so the reason that
rich people who could afford to pay more for things
(38:00):
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, we're paying more at Staples because Staples knew
they had them over a barrel, right. And so the
(38:21):
corporate concentration overlay is key here, and it is key
in one other way as well, which is really featured
prominently in the issue, which is that increasingly the business
case for mergers is data. So, you know, we highlight
the example of Walmart buying Visio. Why is Walmart buying
(38:42):
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 type 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. Smilarly in the piece, you know, there's considerable
(39:03):
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
at the highest bidder as they are on selling you cerios, right,
And so I think the data, the value of the
data for companies, and the interlay with consolidation, both as
(39:23):
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.
Speaker 2 (39:35):
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 that makes
a lot of sense. I have one more big question,
(39:56):
which is you know, I started we mentioned in the
intro the one industry it 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
(40:16):
airlines have been doing with frequent fire miles for decades
and then that sort of migrating over through consultants, etc.
Into other industries realizing that they can more or less
do the same thing.
Speaker 5 (40:29):
Well, it's really interesting because we had you know, a
number of different authors right 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
(40:51):
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 Idea 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
(41:13):
an ancillary Revenue Masterclass, 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
(41:34):
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
(41:58):
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
(42:20):
called Suburban pro Pain obviously, as they sell propaine 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,
(42:42):
a tank pickup fee, a minimum monthly purchase fee, a
system leak test fee, a reconnect fee, a wheel call fee,
a forklift minimum delivery fee, a diagnostic fee, an installation fee,
an early termination fee, an emergency special livery fee, a
late fee, a return check fee, and a meter account
(43:05):
maintenance fee. And I'd like to say that was an outlier,
but I'm not sure it is. Like we are seeing
these add on fees in all sorts of industries. It
originated in the airlines and now it's gone everywhere. And
you see the Biden administration actually taking this up as
(43:26):
a cause. The term junk fee was kind of invented
or coined by ro Hit 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,
(43:47):
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 attempted pushback on them.
Speaker 3 (44:02):
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 macro economics. 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
(44:27):
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.
Speaker 5 (44:47):
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 colic between Sharet Brown,
who's the chair of the Senate Banking Committee, and j
Powell when he was doing a semi annual report and
(45:10):
Sharet Brown was asking Powell about these pricing strategies, and
Howell 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 story, you get lower priced, and if
(45:31):
there are people in the story, 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
(45:55):
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
(46:18):
think our answer, and Lindsey 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
(46:39):
not do the whole job anymore, and that there are
other factors and there are other agencies that can be
brought to bear here.
Speaker 4 (46:47):
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 folk supplotting inflation headed back
(47:09):
to two percent 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
(47:29):
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 this shift. You know, of course
these techniques proceeded inflation, but they do seem to have
been unleashed 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
(47:51):
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 racing 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
(48:12):
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 numble or fast moving or
(48:33):
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.
Speaker 2 (48:43):
By the way, I checked out the sample two day
agenda of the Idea Works Company and Cellary Revenue Masterclass,
and it really is a boot camp on charging more
ten fifteen Coffee Break ten thirty, Top ten things you
need to know about ancillary revenue in airlines eleven, Antilia
revenue boost the bottom line twelve Like it's really amazing.
(49:04):
David and lindsay, that was so fantastic. Really appreciate you
both coming on odd lots. Everyone should check out the
June third edition of The American Prospect. Really fascinating stuff
on a range of topics. Great chatting with both of you.
Speaker 4 (49:17):
Thanks thanks for having us.
Speaker 2 (49:31):
Tracy. I thought that was fantastic and there us 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
(49:51):
something else out there that's really annoying. Maybe it is
a sort of polite way to put it, or like
aggravating about this economy and this sort of psychological 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 compound the aggravation of higher prices themselves.
Speaker 3 (50:09):
No, absolutely, and also just the point about, well, the
genies 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
(50:30):
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 all blots, and we spoke with Samuel
Rans about this, of course, and you can see the
(50:50):
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.
Speaker 2 (51:02):
By the way, our producer Kale came through the reference
the nineteen sixty seven 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 rich
in theory in 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
(51:25):
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.
Speaker 3 (51:39):
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 point. 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
(52:01):
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
(52:22):
depressing myself as I talk Joe. This is depressing. Wait
are you a little bit less relaxed about some of this?
Speaker 1 (52:29):
Now?
Speaker 3 (52:29):
Please tell me you are.
Speaker 2 (52:31):
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 the same way other things do. I
do want to attend an Ideal works Company ancillary revenue
master class. Maybe we could do that one day.
Speaker 3 (52:51):
I do not let me just throw that out there, No,
I mean that list of junkxies that David was reading
where like a hair away from them basically charging for
oxygen in order to breathe. Right, Like, we're almost there.
Speaker 2 (53:06):
That seems successive on the plane. It's like, does that
thing fall out?
Speaker 5 (53:10):
Yeah?
Speaker 2 (53:11):
Do you pay extra, pay extra to make sure that
the thing fall will fall out?
Speaker 3 (53:16):
Yeah?
Speaker 2 (53:17):
Well.
Speaker 3 (53:17):
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.
(53:39):
But I will say this is something that has come
up in our 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 ealisticity.
Speaker 2 (53:59):
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.
Speaker 3 (54:14):
Shall we leave it there.
Speaker 5 (54:15):
Let's leave it there, all right?
Speaker 3 (54:16):
This has been another episode of the Odd Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (54:22):
And I'm Joe Wisenthal. You can follow me at The Stalwart.
Follow our guest David Dayan, He's at d Dayan. And
Lindsey Owens She's at Owens Lindsey One. And definitely check
out that new edition of the American Prospect magazine. Follow
our producers Carman Rodriguez at Carman armand dash Ol Bennett
at Dashbot and kel Brooks at Kelbrooks. Thank you to
(54:43):
our producer Moses Ondam. For more odd Lots content, go
to Bloomberg dot com slash odd Lots. We have transcripts
the blog and a newsletter and go on chat with
Hello listeners twenty four to seven, go to our discord Discord,
dot gg, slash od.
Speaker 3 (54:56):
Lots and if you enjoy all thoughts. If you like
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And remember, if you are a Bloomberg subscriber, you can
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(55:17):
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Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of The Odd Lots Podcast.
Speaker 3 (00:22):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:25):
Tracy, you know what I feel is become a common
Twitter conversation that I've seen happen a bunch of times.
Speaker 3 (00:32):
Uh, this could be anything, but go on.
Speaker 2 (00:36):
Someone tweets like, oh my god, I just paid, like,
you know, fourteen dollars for a hamburger and fries at
the McDonald's and then someone else goes, well, actually, you
can get it for three ninety nine right now if
you just use the app. Yes, I've seen this many times.
Speaker 3 (00:53):
Both of them are not wrong, but it is crazy.
First of all, I'm so thrilled that we're finally going
to do 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.
(01:15):
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 through 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
(01:36):
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
(01:58):
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, y 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
(02:19):
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
(02:43):
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.
Speaker 2 (02:53):
Like companies basically just getting better at figuring out the
maximum price they can charge for something. Wait, I have
a personal question for your 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.
Speaker 3 (03:06):
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
(03:26):
don't I go ahead and do that?
Speaker 2 (03:28):
Yeah, I'm so lazy. I am not a points person.
I'm not an app person. I've never been a Miles person.
It seems like I probably should. I don't trouble 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
(03:51):
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.
Speaker 3 (04:01):
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 surge pricing in
fast food is kind of already there, right, you know,
(04:23):
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.
Speaker 2 (04:42):
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, differentiating prices.
Speaker 3 (05:01):
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 is 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 fastest.
Do you think there's going to be in a meaningul
supply response in Hamburgers?
Speaker 2 (05:20):
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 twelve oh one New Year's like,
you have to raise the price such that some people
like I'll take the subway or whatever. Anyway, enough, what.
Speaker 3 (05:36):
I think we don't have to debate.
Speaker 2 (05:37):
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
(06:00):
be some time out in the future. And we're going
to be speaking with David Dayan. He's the executive editor
of The American Prospect magazine, and The American Prospect has
a full edition of the magazine coming out on June
third that is entirely devoted to the world of pricing
and how companies do this in the history, and both
of us have read the whole edition in the magazine.
(06:21):
Is fantastic. They've worked together on this. It is a
really interesting body of work. I think it will be
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 Outlaws, thanks for having me.
Speaker 4 (06:35):
Thanks for having us.
Speaker 2 (06:36):
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.
Speaker 5 (06:52):
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
(07:13):
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.
(07:33):
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 williness
(08:00):
to pay among their customers, and so we think we
can 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
(08:25):
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
(08:49):
can personalize prices, which is really kind of where I
think a lot of businesses see a lot of opportunity,
the idea of 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,
(09:12):
what government, what role they have to play in maybe
doing something about it.
Speaker 3 (09:17):
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 greed inflation here. I
(09:41):
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 waive this theory away. But
could you maybe talk about concrete evidence we have that
(10:02):
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?
Speaker 4 (10:16):
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 sense of the report is retailers are in a
(10:36):
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
(10:58):
like Ravionics and Mantec and others who are basically bundling
up competitors' data using sort of surveillance, targeting and geoanalytics
to take in competitors' data and then spitting out for
the retailer's advice and recommendations on you know, how to
keep prices higher for faster and longer. And so when
(11:18):
I get a question like this, I really just like
to go to the quotes 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
(11:42):
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
(12:03):
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 recruitment
and where revenue maximization and pricing is really critical to
the game. And big data and new technologies has really
allowed this pricing to go high tech and these new
(12:25):
strategies to really flourish. And so I don't like to
make too many predictions, but you know, 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
nineteen has obviously allowed folks to collect more and more
data on consumers and I think we're just really at
(12:47):
the tip of the iceberg here. We're just sort of
starting to see these strategies unleashed across industries.
Speaker 2 (13:08):
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
(13:29):
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 are trying to get data. Talk
about this sort of like the role that data aggregators
have and maybe the specific industries that use this data
(13:52):
to get better at pushing price.
Speaker 5 (13:54):
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 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
(14:15):
it's been around since the I believe, the since deregulation
in the nineteen eighties. And they collect real time data
on every fare that's been published in the US 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
(14:38):
looked at this as a collusion operation, but they allowed
it to go forward in the nineteen nineties. 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
(15:01):
meat packing 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,
(15:22):
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
(15:45):
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
(16:08):
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
(16:29):
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
(16:53):
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.
Speaker 3 (17:11):
Go for It.
Speaker 5 (17:13):
So the McDonald's app is put together by a company
called Plexure, and Plexure works with Ikea, they work with
seven to 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
(17:34):
to figure out what you're doing on that phone, where
you are at particular times of day, what your food
preferences are, what you're 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.
(17:54):
And we had one of the slides from this presentation
that Plexure put together the other 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
(18:16):
that you get paid every other Friday, it might give
you a three dollars McMuffin on Thursday, but when Friday
you have some money in your pocket, it might raise
it to four dollars.
Speaker 3 (18:27):
Right.
Speaker 5 (18:28):
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 a mcflurry. Often, plecture
combines this data that's within the app, like what they
call first party data, with additional data about you through
(18:49):
what is called an identity graph that aggregates both you know,
stuff you're doing on the app, with your email, with
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
(19:09):
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
(19:30):
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
(19:52):
for the same product. Because what personalized pricing is always
run into is this sense of unfairness. And if it's
very apparent that I paid three dollars and the guy
behind me in line paid four dollars, I'm going to
be mad about that. If I'm the guy paying four dollars,
why did I pay more than the other guy? But
(20:13):
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 a fascinating and
(20:33):
maybe you know, to some people, dystopian reality.
Speaker 3 (20:37):
I was literally about to use that word.
Speaker 4 (20:39):
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 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
(21:01):
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 Wannamaker, the Philadelphia department
store owner, similarly had concerns about this. And by the way,
a business case in a large department store, you know,
(21:22):
haggling takes a little time, right, 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
(21:45):
all of the twentieth 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 the same amount as your friend did for the
same good. And we're really in some ways returning to
the bizarre the marketplace because of new technologies that are
(22:08):
enabling companies to more aggressively tailor price discrimination.
Speaker 3 (22:13):
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 twenty fifteen about exactly this theme. So the
(22:34):
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
(22:55):
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, one hundred
dollars to like ten thousand dollars something like that, and
(23:18):
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
(23:40):
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
(24:01):
profiles of people, and there are certain you know, 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?
Speaker 5 (24:21):
Yeah, I mean I talked to Lena Khan for this issue.
She's 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
(24:45):
economists liked to take a look at to see 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 to study out in
(25:06):
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
(25:27):
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 you know, I've talked to a
University of Chicago economists 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
(25:47):
two people at the very same time. One had eighty
four percent on their battery and one had twelve percent,
and the twelve percent 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
(26:09):
algorithmic surge pricing that I mentioned, there was a quirk
case over a company called rain Maker, 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 throw
out the case because he said, well, they were only
(26:31):
recommending certain prices, they weren't mandating it. Even though the
statistics that rain Maker even submitted say that ninety percent
of the time the recommendation has 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 as an open question. But lawmakers
(26:54):
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
(27:16):
also anti trust tools. Because the one secret sauce here
is market power. The idea that you can just sort
of willy nearly 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. In the market will sort of rebalance itself.
(27:37):
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 you know, competition
policy moves towards a place where these markets suddenly have
(27:58):
more choices for customers, then these pricing strategies lose a
little bit of their power.
Speaker 4 (28:03):
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.
You know, as you point out, any set of pricing
that relies in whole or in part on geography in
(28:24):
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 one hundred million rides, I believe, and what
(28:45):
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
(29:07):
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
(29:27):
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
(29:47):
not existing law is up to the task, or whether
or not new laws will be required to protect consumers
from discriminatory practices in tracing.
Speaker 2 (30:10):
You know, I mentioned by the way that I'll play
Devil's advocate here and I'll 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 I'm just gonna 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
(30:31):
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
(30:51):
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
(31:14):
that they have to deal with all of these different
rewards programs and things like that.
Speaker 4 (31:19):
Yeah, I don't even have airline points because I'm too
disorganized to keep up with accounts for Delta and America
and things like that. So I hear you one hundred
percent 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
(31:41):
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 fixed prices, in the grocery store for your family vacation,
where you're having to deal with algorithmic price fixing in
(32:03):
both airline class 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 coop on
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 from my toddler right now
(32:25):
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 ceios 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
(32:46):
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
(33:06):
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 Wanta maker coming
(33:29):
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 frickin' price. It may not be the lowest price,
but like I promised 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,
(33:50):
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 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.
Speaker 3 (34:08):
Right. And also, I mean it's pretty obvious to me
that if you are 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
(34:33):
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
(34:56):
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
(35:16):
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.
Speaker 5 (35:31):
Yeah, I mean, the first really comprehensive study on why
this phenomenon of poorer Americans paying more happens was published
in nineteen sixty three. 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
(35:54):
online products offering different prices in different geolocations based on
the IP address and the areas that saw that 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
(36:14):
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
(36:36):
you'll be charged more as you go up the income ladder.
But that's not really how it works.
Speaker 3 (36:42):
You know.
Speaker 5 (36:42):
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
(37:03):
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 and
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 dollars.
(37:24):
So there are a whole number of ways where this
does not look like you just pay more if you
have more resources. Willingness to pay is a very different concept.
Speaker 4 (37:37):
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 at all and
facilitates and accelerates it all. And so the reason that
rich people who could afford to pay more for things
(38:00):
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, we're paying more at Staples because Staples knew
they had them over a barrel, right. And so the
(38:21):
corporate concentration overlay is key here, and it is key
in one other way as well, which is really featured
prominently in the issue, which is that increasingly the business
case for mergers is data. So, you know, we highlight
the example of Walmart buying Visio. Why is Walmart buying
(38:42):
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 type 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. Smilarly in the piece, you know, there's considerable
(39:03):
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
at the highest bidder as they are on selling you cerios, right,
And so I think the data, the value of the
data for companies, and the interlay with consolidation, both as
(39:23):
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.
Speaker 2 (39:35):
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 that makes
a lot of sense. I have one more big question,
(39:56):
which is you know, I started we mentioned in the
intro the one industry it 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
(40:16):
airlines have been doing with frequent fire miles for decades
and then that sort of migrating over through consultants, etc.
Into other industries realizing that they can more or less
do the same thing.
Speaker 5 (40:29):
Well, it's really interesting because we had you know, a
number of different authors right 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
(40:51):
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 Idea 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
(41:13):
an ancillary Revenue Masterclass, 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
(41:34):
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
(41:58):
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
(42:20):
called Suburban pro Pain obviously, as they sell propaine 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,
(42:42):
a tank pickup fee, a minimum monthly purchase fee, a
system leak test fee, a reconnect fee, a wheel call fee,
a forklift minimum delivery fee, a diagnostic fee, an installation fee,
an early termination fee, an emergency special livery fee, a
late fee, a return check fee, and a meter account
(43:05):
maintenance fee. And I'd like to say that was an outlier,
but I'm not sure it is. Like we are seeing
these add on fees in all sorts of industries. It
originated in the airlines and now it's gone everywhere. And
you see the Biden administration actually taking this up as
(43:26):
a cause. The term junk fee was kind of invented
or coined by ro Hit 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,
(43:47):
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 attempted pushback on them.
Speaker 3 (44:02):
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 macro economics. 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
(44:27):
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.
Speaker 5 (44:47):
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 colic between Sharet Brown,
who's the chair of the Senate Banking Committee, and j
Powell when he was doing a semi annual report and
(45:10):
Sharet Brown was asking Powell about these pricing strategies, and
Howell 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 story, you get lower priced, and if
(45:31):
there are people in the story, 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
(45:55):
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
(46:18):
think our answer, and Lindsey 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
(46:39):
not do the whole job anymore, and that there are
other factors and there are other agencies that can be
brought to bear here.
Speaker 4 (46:47):
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 folk supplotting inflation headed back
(47:09):
to two percent 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
(47:29):
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 this shift. You know, of course
these techniques proceeded inflation, but they do seem to have
been unleashed 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
(47:51):
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 racing 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
(48:12):
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 numble or fast moving or
(48:33):
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.
Speaker 2 (48:43):
By the way, I checked out the sample two day
agenda of the Idea Works Company and Cellary Revenue Masterclass,
and it really is a boot camp on charging more
ten fifteen Coffee Break ten thirty, Top ten things you
need to know about ancillary revenue in airlines eleven, Antilia
revenue boost the bottom line twelve Like it's really amazing.
(49:04):
David and lindsay, that was so fantastic. Really appreciate you
both coming on odd lots. Everyone should check out the
June third edition of The American Prospect. Really fascinating stuff
on a range of topics. Great chatting with both of you.
Speaker 4 (49:17):
Thanks thanks for having us.
Speaker 2 (49:31):
Tracy. I thought that was fantastic and there us 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
(49:51):
something else out there that's really annoying. Maybe it is
a sort of polite way to put it, or like
aggravating about this economy and this sort of psychological 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 compound the aggravation of higher prices themselves.
Speaker 3 (50:09):
No, absolutely, and also just the point about, well, the
genies 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
(50:30):
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 all blots, and we spoke with Samuel
Rans about this, of course, and you can see the
(50:50):
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.
Speaker 2 (51:02):
By the way, our producer Kale came through the reference
the nineteen sixty seven 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 rich
in theory in 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
(51:25):
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.
Speaker 3 (51:39):
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 point. 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
(52:01):
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
(52:22):
depressing myself as I talk Joe. This is depressing. Wait
are you a little bit less relaxed about some of this?
Speaker 1 (52:29):
Now?
Speaker 3 (52:29):
Please tell me you are.
Speaker 2 (52:31):
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 the same way other things do. I
do want to attend an Ideal works Company ancillary revenue
master class. Maybe we could do that one day.
Speaker 3 (52:51):
I do not let me just throw that out there, No,
I mean that list of junkxies that David was reading
where like a hair away from them basically charging for
oxygen in order to breathe. Right, Like, we're almost there.
Speaker 2 (53:06):
That seems successive on the plane. It's like, does that
thing fall out?
Speaker 5 (53:10):
Yeah?
Speaker 2 (53:11):
Do you pay extra, pay extra to make sure that
the thing fall will fall out?
Speaker 3 (53:16):
Yeah?
Speaker 2 (53:17):
Well.
Speaker 3 (53:17):
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.
(53:39):
But I will say this is something that has come
up in our 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 ealisticity.
Speaker 2 (53:59):
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.
Speaker 3 (54:14):
Shall we leave it there.
Speaker 5 (54:15):
Let's leave it there, all right?
Speaker 3 (54:16):
This has been another episode of the Odd Thoughts podcast.
I'm Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 2 (54:22):
And I'm Joe Wisenthal. You can follow me at The Stalwart.
Follow our guest David Dayan, He's at d Dayan. And
Lindsey Owens She's at Owens Lindsey One. And definitely check
out that new edition of the American Prospect magazine. Follow
our producers Carman Rodriguez at Carman armand dash Ol Bennett
at Dashbot and kel Brooks at Kelbrooks. Thank you to
(54:43):
our producer Moses Ondam. For more odd Lots content, go
to Bloomberg dot com slash odd Lots. We have transcripts
the blog and a newsletter and go on chat with
Hello listeners twenty four to seven, go to our discord Discord,
dot gg, slash od.
Speaker 3 (54:56):
Lots and if you enjoy all thoughts. If you like
it when we dive into to 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
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(55:17):
Apple Podcasts and follow the instructions there. Thanks for listening
Hosts And Creators
Joe Weisenthal
Tracy Alloway
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