The holy grail for a long time has been
what if we could charge every single
person the maximum amount that we know
they're able to or willing to pay.
>> They know things about us that we don't
know. They're smarter than us and we're
training them in a way that is
incalculable.
>> Walk into any grocery store and on
average everything is about 30% more
expensive than it was in 2020.
>> Inflation, supply chains, tariffs, we've
heard it all. But what if something else
is happening? Something intentional.
>> What if someone has charged $2 for these
eggs, but another person has charged
$240 at the same exact store and it's
pushing prices up? 5 months ago, a
researcher reached out to me about
Instacart. She'd been studying their
Washington DC workforce. Different pay
for nearly identical work. Her question,
if they do this to workers, what about
consumers? Before joining More Perfect
Union, I worked in grocery pricing. So,
I agreed to help investigate. The
problem, it wasn't easy to test. Grocery
prices change all the time for
legitimate reasons. Receipts you can't
compare. If we wanted to do this, we'd
need a team. A researcher, community
organizers, other journalists, and most
importantly, regular people who care.
Lots of them. 5 months of digging, what
we found is bigger than Instacart. Yes,
inflation is real. But something else
has been pushing prices higher this
whole time. There's a system, one that
grocery stores and tech companies built
together. It learns from every purchase.
It's not just online. It's in the
physical stores you walk into with the
primary goal. [music] Maximize profit
day by day. It's moving billions of
dollars one penny at a time. Here's how
we uncovered it. How it's turning the
grocery business into a gold mine. and
why without regulation, your grocery
bill may keep climbing no matter what
happens with inflation.
>> I'm now going to ask you to take out
your phone and we're going to get
started with shopping for 20 items at
the Safeway.
>> This is Katie Wells. She's the director
of research at Groundwork Collaborative.
She's the one who reached out. The plan
was pretty simple. Get everyone in a
room. Open up Instacart. Select the same
store, same items on phones and
computers. Select pickup to remove any
delivery calculations and write our
basket totals down [music] on a note
card. All to test a simple question.
Were shoppers being charged different
amounts for the same exact item at the
same exact store in time.
>> Congratulations, guys. You have finished
the test.
>> First, we all shared our cart totals.
We're in the same room, the same address
ordering, and we still had different
prices.
>> You're the highest.
>> I'm not surprised. What I've come to
understand is that a lot of things uh
that we do online is predicated on
algorithms.
>> Different totals. There's plausible
explanations, promotions, user [music]
error, app issues. But if the items
themselves had different prices, that's
something else.
>> The items had upwards of three different
prices offered. Katie analyzed the data.
>> The greatest difference was about a.7
spread. For eggs, the prices varied from
$459 to 469 down to $428.
It was a 41 cent [music] span.
>> One store, one moment in time. It's a
small sample size. This could be a
fluke.
>> Welcome, welcome, welcome. You have
found your way to the Consumer Reports
grocery pricing webinar. The problem
with testing any of this is that these
systems are so massive that you need
scale to even try. Consumer Reports
joined the collaboration. They brought a
volunteer network, community organizers,
a reporter. Alongside them, we recruited
volunteers, over 400 people. Same
process. Everyone opens Instacart. Same
store, same items. When pickup wasn't
available, same delivery address, same
[music] moment. Screenshot everything.
submit. The team verified every entry,
cross-cheed every screenshot, built the
database. Katie crunched the data, and
when the data came back, I got to be
honest, I stared at it for a while
[music] because what we found was weird.
I'm going to show you some basket
totals. Some people were charged about
$114 for the 20 items, others nearly
$124.
>> This wasn't in one or two cases. This
was the lion share of shoppers for the
lion share of items. If you zoom in,
nearly three out of four products had
[music] different prices during the
experiments,
four different prices for wheat fins,
five different prices for eggs, three
prices for peanut butter. Wait, what?
The system sorted people into price
groups where each person was charged the
same for every item. For this test,
there were four price groups. Same cart,
[music] same store, same moment. Same
with this test.
for this store. Seven different [music]
price groups.
This didn't seem random, but who or what
was doing the sorting? Back in August,
before we even ran the test, I called
Instacart. We don't set prices.
Retailers do. And we believe them. But
the group suggested something deeper was
[music] going on. Why would an algorithm
sort people into buckets where everyone
pays the exact same prices? Not just on
one item, but across multiple products.
All higher together, all lower together.
I started researching and that's when I
stumbled on surveillance pricing.
Companies tracking your behavior, your
purchase history and [music] charging
you based on that. It's a type of
algorithmic pricing where companies hand
pricing over to an algorithm. It's
almost impossible for people outside the
companies practicing the art the dark
art of of algorithm price determination.
Exactly what is driving those algorithms
to set the prices that we observe.
>> Len Sherman studies this at Columbia's
business school. Was that what was
happening here? When we showed Instacart
the test results, they were clear.
Retailers control all pricing. The
findings were just stores putting out
random feelers to see where the pricing
sweet spot is. [music] They aren't
targeting you specifically. So, we
verified with the stores we tested.
First, Albertson's Safeway. They're an
Instacart partner. Silence. Then, we
contacted Target. They responded, and
honestly, my jaw dropped. [music] They
told us, "We don't work with Instacart.
We don't set prices. We have nothing to
do with any [music] of this. Wait,
Instacart says retailers control the
prices and Target says they don't even
work with Instacart. I started digging.
[music] Turns out in 2017, Target spent
over half a billion dollars to buy
shipped, Instacart's competitor. Why
would they help Instacart? We asked
Instacart about Target's response.
Instacart admitted they actually do
manage Target's [music] prices on the
marketplace and that they were running
tests to figure out how much they can
charge on top of Target's normal prices.
Their explanation [music] shifted, but
the question we started with was still
the same. How does the system sort
people into different price groups? To
figure that out, we needed to understand
what Instacart actually does.
You may think of Instacart as a delivery
app, but it's much bigger than that.
>> With Instacart is more the technology. I
don't think of it as a grocery delivery
company. I think of it more of a
technology company
>> selling technology that powers grocery
websites, advertising campaigns,
promotions. In 2022, Instacart bought
Eversight, a company that optimizes
grocery prices.
>> Eversight says it runs constant
experiments that are not made visible to
consumers. And it is running tests in
part to collect data about how much I'm
willing to pay for canola oil. And it's
using that information to likely create
more profits for these companies.
>> The company calls it AI for everyday
price performance. The website promises
2 to 5% profit increases. In early
November, Consumer Reports ran follow-up
experiments at Costco. They found price
gaps, 15% on a bag of chips. Derek asked
Costco to explain.
>> We got an email a few hours later from a
Costco vice president of grocery.
>> The message described a program called
Smart Rounding. You know, it took us a
little bit of time to realize what we
were seeing, which was an internal
communication between Instacart and
Costco. Inadvertently, this Costco
executive forwarded us this internal
email. As far as we can tell, Instacart
has only talked about smart rounding
once. In a 2023 letter to shareholders,
the company defined it. Machine learning
driven tool that helps retailers improve
price perception and drive incremental
sales. translation, flex prices up or
down based on what the algorithm says
will maximize profit.
>> For some of our major grocery partners,
this has led to millions of dollars in
annual incremental sales.
>> Millions of dollars.
>> This is a very um sophisticated,
very deliberate, explicit attempt to
maximize profits and do so somewhat
surreptitiously.
>> We'd answered some questions, different
prices for different people. Yes, random
testing, maybe not. Smart rounding
showed its design for profit. Retailers
in control, debatable. Instakart sets at
least one ger's prices. But we still
couldn't answer, how does the system
sort people into price groups. Then one
store showed us the bigger picture.
Shnooks, regional ger, they're on every
Instacart press release. No price
variation at all. One night, it hit me.
What if they already moved past [music]
online testing? You've probably heard
stories about electronic shelf labels,
digital price tags that can change
prices instantly. If they're testing
prices in [music] store with those
labels, and the app just mirrors what's
on the shelf, you'd never catch it with
our test, which might explain Shnooks.
The typical fear with these labels is
surge pricing, raising lemonade prices
when it's hot out. What if the goal
isn't surge pricing at all? What if it's
more subtle, more permanent? Would you
rather charge $10 for a bottle of water
during a single hurricane or 20 cents
more every single day? Derek had a
genius idea. Patents. He found one. It
described an infrastructure for constant
instore price testing. Take dozens of
stores, cluster them together, test
different prices in different clusters.
The purpose, find out the most
profitable price point. Once you do,
adopt it. We asked Shnooks and
Instacart. Both denied it. But for
Instacart, their website told a
different story. If you go there right
now, you'd see this three features
[music]
before we asked. Four features and the
one removed price optimization with
Eversite via electronic shelf labels.
Gone. So, Instacart denied doing it,
then changed their website. Later, they
told us it was never a feature and the
update was made for accuracy. But that
didn't track. The feature seems to show
up in past marketing materials and press
releases. If it's operational, the
system would be a truly impressive feat
of [music] engineering. In store,
testing across locations, online,
testing across individuals. But we still
couldn't answer how the online system
decided who gets charged more. [music]
So, we started building a theory, not
based on what Instacart told us, but on
what Instacart told the government.
Patents. The word that appears over and
over in them. It's not random. It's
segmentation.
Derek started reading through the
criteria they could use to sort people.
Some things raised red flags.
Demographics. It's illegal to charge
someone more based on those. Katie
controlled for that. No correlation in
the sample.
>> I don't believe they would try to vary
prices based on those kinds of
characteristics. Nor would it be very
effective if they [music] did. What
would be way more effective and
perfectly legal as far as I know is to
vary prices based on behavioral
characteristics. Behavioral
characteristics. [music] That's exactly
what the patents show. Buying behavior,
purchase [music] history, how frequently
you shop, whether you're shopping
around, coupon usage, loyalty program
participation, an infrastructure that
tracks everything you do, uses it to
decide what to charge you. We asked
Instacart, "Does this explain who gets
sorted into different price groups?"
Their response, "One old patent from
2015 [music]
before we purchased Eversite." Patents
are always broad. This doesn't prove
we're actually using this technology.
Fair point. Here's the same chart and a
host of other patents, [music] mostly
about promotions, marketing material
that touts the patents, and then this
one, a promotional [music] patent that
describes shopper and product headroom.
Meaning, how much more money could this
person spend overall? and how much more
could they spend on this product? The
patent says they can calculate this for
every individual consumer. But for
efficiency, typically people are grouped
with similar consumers [music] groups
just like our test showed.
>> Every company that I know is practicing
first-degree discrimination strenously
denies that they're doing so.
>> And again, Instacart denies segmenting
people by personal or behavioral data.
What happens when companies actually do
this at scale? In 2022, Uber rolled out
algorithmic pricing for riders and
drivers. Len studied what happened next.
>> For the next three years, average rider
price per mile went up up up up up up.
>> Uber denies all of this. But at about
this time, they went from burning money
to a cash machine.
>> That's why more and more companies are
trying as hard as they can to perfect
this dark art, devilishly effective dark
art, as I've called it. That's how you
turn grocery sales into a gold mine.
>> Now, algorithmic pricing sometimes
offers lower prices and the total impact
on grocery prices impossible to measure.
Instacart is just one company, a sliver
of the grocery market. They claim
[music] 10 clients withight. What are
other companies doing? I started
looking.
>> Pricing is [music] the single most
powerful lever to raise profits. Far
more effective than either boosting
sales [music] or cutting costs. Prices
optimized,
profit increases.
>> There's an entire industry built around
optimizing grocery prices. I called Earl
Schweiser, 25 years in grocery, former
VP of grocery at Whole Foods. Why is
everyone racing to adopt this?
>> It's very much defensive. Amazon's
already doing it. Walmart is doing it.
So, everybody's got to keep up.
merchants, pricing [music] teams, they
all rely on technology and algorithms to
safeguard their profits.
>> That's Walmart's former VP of [music]
pricing.
>> So, Instacart has played this really
vital role for the competitors of Amazon
and Walmart, which is pretty much almost
everybody else to have a lot of the same
tools and access to consumers as the
[music] big guys. The systems are
watching you, learning your patterns,
using that to charge everyone
accordingly.
>> They know things about us that we don't
know. They're smarter than us, and we're
training them in a way that [music] is
incalculable.
This didn't happen overnight. 20 years
of building this infrastructure. It was
[music] kept in check by inertia.
Everyone was afraid to raise prices. Co
changed [music] that.
>> There's no guard rails. It's a
free-for-all. It's a wild wild west.
Companies are investing millions into
systems designed to outsmart you.
Testing, [music] learning, finding the
maximum profit.
>> The holy grail for a long time has been,
what if we could charge every single
person the maximum amount that we know
they're able to or willing to pay.
Studies like this are just validating
that [music] firms are very much already
midway through trying this, executing
it. That's Lena Khan, former chair of
the Federal Trade Commission. She agreed
to review our findings with an eye
[music] to how we should protect
consumers.
>> This could ultimately end up being
another big form of wealth transfer from
ordinary Americans to massive
corporations.
>> I asked about the instore testing
apparatus, electronic shelf labels, the
patents. Firms have been trying to
figure that out for many decades. But I
think what's different now is [music]
both the sophistication of the tools
that are available. Just the deep
information asymmetries that exist
between consumers and these firms that
are benefiting.
>> But there was something else that
concerned her. When you have companies
like Instacart [music] that could be
facilitating, it could also ultimately
allow firms that really should be
competing against one another when
setting these prices to actually engage
more in something that looks like price
fixing or collusion
>> because it could mean that one company
Instacart is setting prices for
retailers who should be competing with
each other. Then I asked her about
regulation. Her answer surprised me. I
think we need to have a much more first
order conversation about do we even want
to permit some of these tactics in the
first instance. [music]
>> Under Khan's watch, the FTC started an
investigation into surveillance pricing.
>> This week, it launched an investigation,
the FDC, into the use of AI to rapidly
change pricing.
>> That investigation is [music] now in
question. The Trump administration
claims it is ongoing, but Khan's
replacement stopped public [music]
comments. But Lena pointed out that
states don't need to wait for the Trump
administration.
>> The steps we've seen um even from states
like California and New York to ban
certain types of algorithmic price
fixing [music]
in areas like housing and rent, for
example, I think are extraordinarily
important steps. [music] We need more
investigations. So I think we need a a
360 view uh to try to understand what's
really happening here. [music]
>> 5 months, three organizations, 400
volunteers. We know the system exists
for surveillance [music] pricing, but we
don't know if it's operational because
we can't see inside [music] and that's
intentional. It's a system that's
designed to stay hidden. [music]
>> This work that you all have done is is
fantastic, but state AGS have subpoena
power. They can be requesting and
demanding information so they could look
under the hood and be understanding how
[music] far firms actually using this
data.
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