WEBVTT - Why Instacart Backtracked on an AI-Pricing Experiment

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news.

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<v Speaker 2>One weekday this fall, thirty nine shoppers fired up the

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<v Speaker 2>grocery delivery service Instacart and filled their virtual carts. They

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<v Speaker 2>all put the same twenty items in there from the

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<v Speaker 2>same Seattle Safeway, wheat Thins, Heinz, Ketchup, Cheerios, Skippy peanut butter.

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<v Speaker 2>But when it came time to check out, the total

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<v Speaker 2>price of their baskets was different as much as nine

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<v Speaker 2>dollars and fifty nine cents different. One shoppers two dollars

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<v Speaker 2>ninety nine cent jar of peanut butter was another shopper's

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<v Speaker 2>three dollars and sixty nine cent jar of peanut butter.

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<v Speaker 2>Two identical boxes of wheatins could vary by as much

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<v Speaker 2>as ninety cents. Now, a few dollars here or there

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<v Speaker 2>might not sound like a lot, but over a year

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<v Speaker 2>of buying groceries, it can add up.

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<v Speaker 1>Grocery are a major line item for most families budgets.

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<v Speaker 1>The other thing that's a problem for many families is

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<v Speaker 1>when pricing is so variable, your grocery budget starts to

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<v Speaker 1>feel really unpredictable.

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<v Speaker 2>That's Lindsay Owens, the executive director of the Groundwork Collaborative,

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<v Speaker 2>a progressive economic policy think tank. This month, Groundwork released

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<v Speaker 2>an investigation with the organization Consumer Reports in partnership with

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<v Speaker 2>the news nonprofit more Perfect Union that found that instacart

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<v Speaker 2>has been using an AI tool to run algorithmic price

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<v Speaker 2>experiments on shoppers around the country, often without their knowledge,

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<v Speaker 2>at a time when inflation has driven grocery costs higher.

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<v Speaker 2>The revelation that instacart was charging some consumers more for

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<v Speaker 2>the same goods struck a court.

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<v Speaker 1>A one to two dollars markup just from shopping online

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<v Speaker 1>versus in person just sounds crazy to me when you're

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<v Speaker 1>already doing the tip and having this service fee here.

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<v Speaker 3>Obviously, this needs legislation, so let your representatives know that

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<v Speaker 3>this matters to you.

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<v Speaker 1>But until we have that law, avoid in store apps.

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<v Speaker 2>And it did get attention from lawmakers and regulators.

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<v Speaker 1>That is instacart stock is falling this morning after Reuters

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<v Speaker 1>reported that the FTC sent the grocery delivery company a

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<v Speaker 1>civil investigation demands.

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<v Speaker 2>The instacart said that it does not use any personal

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<v Speaker 2>demographic or user level behavior data to set prices, and

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<v Speaker 2>that prices weren't changing based on real time supply and demand. Instead,

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<v Speaker 2>they said that the price discrepancies were the result of

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<v Speaker 2>completely randomized ab testing, the kind of test retailers often

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<v Speaker 2>do to figure out how sensitive shoppers are to the

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<v Speaker 2>price of certain items. Still, the company said report raised concerns.

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<v Speaker 2>Quote at a time when families are working hard to

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<v Speaker 2>stretch their grocery budgets, customers should never have to question

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<v Speaker 2>the prices they see on Instacart, an instacart spokesperson told

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<v Speaker 2>us and this week the company need a big one

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<v Speaker 2>to eighty. Instacart is ending a program where customers saw

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<v Speaker 2>different prices for the same product ordered at the same

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<v Speaker 2>time from the same store.

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<v Speaker 3>Oftentimes, you know, companies get criticized for things all the time.

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<v Speaker 3>It doesn't necessarily change their strategy.

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<v Speaker 2>That's Leah Nylan, who covers antitrust for Bloomberg.

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<v Speaker 3>But Instacart was pretty quick to sort of pull back

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<v Speaker 3>on this policy, given like the significant outcry that there

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<v Speaker 3>was in response.

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<v Speaker 2>As more online retailers lean on AI to influence their

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<v Speaker 2>pricing strategy, the groundwork collaboratives Lindsay says Instacart's saga raises

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<v Speaker 2>new questions.

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<v Speaker 1>How far can you take a pricing practice before you

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<v Speaker 1>touch the stove.

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<v Speaker 2>I'm Sarah Holder, and this is the big take from

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<v Speaker 2>Bloomberg News today on the show what Happens when an

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<v Speaker 2>algorithm determines your grocery bill? How volunteer shoppers revealed Instacart's

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<v Speaker 2>invisible pricing practices and what came after the back. In

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<v Speaker 2>twenty twenty two, instacart acquired a company called ever Site

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<v Speaker 2>that offers AI powered pricing software.

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<v Speaker 3>And what this did was it helped retailers, primarily grocery

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<v Speaker 3>stores like Kroger, Albertson's, Safeway, things like that set prices

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<v Speaker 3>for like sort of everyday grocery items.

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<v Speaker 2>Leah Nylan, an antitrust reporter for Bloomberg, says the tool

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<v Speaker 2>has been controversial.

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<v Speaker 3>They could increase the price if they thought, for example,

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<v Speaker 3>you were somebody who really needed an item, or you know,

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<v Speaker 3>were the sort of person who might not see a

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<v Speaker 3>price increase and walk away, so they could sort of

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<v Speaker 3>jack up the prices for certain people or lower them

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<v Speaker 3>for others. The sort of problematic thing about this tool

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<v Speaker 3>is as a consumer, you have no idea that Instacart

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<v Speaker 3>or the grocery store is even using.

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<v Speaker 2>Earlier this year, researchers and analysts at the Groundwork Collaborative

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<v Speaker 2>and Consumer Reports decided to look closer at the grocery

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<v Speaker 2>delivery company's pricing strategy and how it could impact consumers.

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<v Speaker 1>We were interested in this kind of concept of surveillance pricing,

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<v Speaker 1>this idea that companies are collecting data on us not

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<v Speaker 1>just to get better at advertising to us, but also

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<v Speaker 1>maybe to get better at overcharging us.

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<v Speaker 2>Lindsay Owens, again, the executive director of the Groundwork Collaborative.

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<v Speaker 1>We knew a little bit about what instacart was up

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<v Speaker 1>to because they have been reasonably transparent with one population

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<v Speaker 1>their investors. So they have talked about their pricing strategies

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<v Speaker 1>and their earnings calls. They have been transparent about the

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<v Speaker 1>types of technologies they were buying and perfecting in their

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<v Speaker 1>patent applications, and they have also talked a little bit

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<v Speaker 1>about this on their website and some of their marketing materials.

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<v Speaker 1>When they purchased Eversite in twenty twenty two, one of

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<v Speaker 1>the reasons they did so is because ever site offered

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<v Speaker 1>better technology for running the types of experiments we found.

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<v Speaker 1>So we knew that some sort of pricing experiments were

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<v Speaker 1>going on with instacart, but we wanted to understand was

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<v Speaker 1>it just a few pennies here, or was it something

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<v Speaker 1>that could really be contributing to the high cost of

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<v Speaker 1>groceries that so many families in America are frustrated about

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<v Speaker 1>right now. So we basically turned instacarts pricing experiments right

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<v Speaker 1>back around on them.

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<v Speaker 2>Consumer Reports went to their network of members and asked

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<v Speaker 2>for volunteers to participate in an instacart shopping experiment. More

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<v Speaker 2>than four hundred people ended up participating.

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<v Speaker 1>We said, okay, all of the consumers in the study,

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<v Speaker 1>you're going to all pick out the exact same eighteen

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<v Speaker 1>to twenty grocery items Wheat thins and Quaker oats and

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<v Speaker 1>Deli lunch meat. You're going to put them in your cart,

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<v Speaker 1>and then you're going to take screenshots of the prices

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<v Speaker 1>you're being offered for each of the items, and we

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<v Speaker 1>had our data set. What we found was pretty extraordinary.

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<v Speaker 1>These were not little differences. Sometimes one consumer was offered

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<v Speaker 1>a price twenty three percent higher than another consumer for

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<v Speaker 1>the exact same good at the exact same time.

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<v Speaker 2>The total price for the consumer's baskets differed by an

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<v Speaker 2>average of about seven percent.

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<v Speaker 1>So the best way to explain this if you and

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<v Speaker 1>I were standing in line at Target right now, and

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<v Speaker 1>we were holding the exact same box of cheerios. We

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<v Speaker 1>would expect to pay the same amount, right.

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<v Speaker 2>Same store, same day, same item. Yep.

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<v Speaker 1>Like, we're in line together, irl, right and you check

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<v Speaker 1>out your box costs four ninety nine, You're still bagging

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<v Speaker 1>your box. I check out next. My box is six

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<v Speaker 1>ninety nine. I look over at you and I'm like, wait,

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<v Speaker 1>how much did you pay? In you're four ninety nine?

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<v Speaker 1>And then we both look at the cashier, Wait, why

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<v Speaker 1>am I paying six ninety nine? If you and I

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<v Speaker 1>stepped out of line, fired up our phones, got on instacart,

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<v Speaker 1>got the same box of cheerios from that same pickup

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<v Speaker 1>location that we're standing in, there is a very good

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<v Speaker 1>chance that we would be offered different prices. We found

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<v Speaker 1>price variation on seventy five percent of the items in

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<v Speaker 1>the grocery carts, and we found that one hundred percent

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<v Speaker 1>of our secret shoppers got variable pricing at some point

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<v Speaker 1>during the experiment. So no one was immune and seventy

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<v Speaker 1>five percent of the items were offered at variable prices.

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<v Speaker 1>We're effectively part of this big experiment. Well.

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<v Speaker 2>Lindsey also says that this isn't a niche issue. Grocery

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<v Speaker 2>delivery picked up during the pandemic, and a range of

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<v Speaker 2>people use the services today. In an instacart twenty twenty

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<v Speaker 2>five economic report, the company said that sixty eight percent

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<v Speaker 2>of its customers considered Instacart essential. App Trackers estimate instacart

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<v Speaker 2>has over fourteen million active users.

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<v Speaker 1>Some people have kept up with it because they can't

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<v Speaker 1>get to the store, or maybe it's not accessible through

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<v Speaker 1>public transportation, maybe you know, have an injury or something

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<v Speaker 1>like that and can't sort of pick up your own groceries.

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<v Speaker 1>And also instacart allows shoppers to grocery shop at a

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<v Speaker 1>whole host of different outlets, low end grocers, discount grocers,

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<v Speaker 1>big box grocers, high end grocers. Right, so it really

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<v Speaker 1>covers the watershed of different consumer preferences. And so one

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<v Speaker 1>of the reasons why we felt like this study was

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<v Speaker 1>so important, but also we felt like our findings were

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<v Speaker 1>so problematic, is because this isn't sort of a niche market.

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<v Speaker 1>This really is increasingly a big part of the American

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<v Speaker 1>grocery experience.

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<v Speaker 2>And what did you find about why or what could

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<v Speaker 2>explain whether a customer would get a higher or lower price.

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<v Speaker 2>Was there anything about the profiles of shoppers that would

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<v Speaker 2>inform what prices instacart was serving them, or was it random?

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<v Speaker 1>So I think we have a couple of suggestive answers

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<v Speaker 1>to this. The first is we know from Instacart's own

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<v Speaker 1>public statements that part of the reason they do this

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<v Speaker 1>is just to test how much they can charge for

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<v Speaker 1>given items. So they're really conducting pricing sensitivity analyses figuring

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<v Speaker 1>out how high they can take Instacart's markup on top

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<v Speaker 1>of the retailer's price before you take an item out

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<v Speaker 1>of your cart, or close your computer and walk to

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<v Speaker 1>a brick and mortar grocery store. On our end, we

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<v Speaker 1>tested a whole host of demographic information to try to

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<v Speaker 1>see if we could predict which prices you would get

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<v Speaker 1>based on the information that we had. We didn't find

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<v Speaker 1>any statistically significant patterns, so we can't rule out that

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<v Speaker 1>it was random. However, we did find that people were

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<v Speaker 1>sorted into distinct price groups, so there were some people

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<v Speaker 1>who got higher prices pretty much across the board. There

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<v Speaker 1>were some people who got lower prices more often than not.

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<v Speaker 2>According to the report, Instacart confirmed that the findings from

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<v Speaker 2>the tests accurately reflect pricing experiments and strategies. In a

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<v Speaker 2>statement to Groundwork and Consumer Reports, instacart said, just as

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<v Speaker 2>retailers have long tested prices in their physical stores to

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<v Speaker 2>better understand consumer preferences, a subset of only ten retail partners,

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<v Speaker 2>ones that already apply markups, do the same online via Instacart.

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<v Speaker 2>These limited, short term and randomized tests help retail partners

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<v Speaker 2>learn what matters most to consumers and how to keep

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<v Speaker 2>essential items affordable. But in statements, instacart also said that

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<v Speaker 2>there's been reporting that's inaccurately characterized the mechanisms behind some

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<v Speaker 2>of its pricing experiments, and Bloomberg's Leah Nyland says instacart

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<v Speaker 2>stress that the retailer is the one that sets the

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<v Speaker 2>base price of groceries they sell on the app. Retailers

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<v Speaker 2>often have their own reasons and strategies for engaging in

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<v Speaker 2>pricing experiments, as groceries have notoriously narrow profit margins.

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<v Speaker 3>They felt that this study was sort of unfairly blaming

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<v Speaker 3>them for something that they don't have a lot of

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<v Speaker 3>control over.

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<v Speaker 2>Another thing I thought was interesting in the statement that

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<v Speaker 2>they released was that they really reiterated that they weren't

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<v Speaker 2>using surveillance pricing. In other words, they weren't using customers

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<v Speaker 2>personal information to set prices that it was like random

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<v Speaker 2>ab testing. Can you explain further the difference between algorithmic

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<v Speaker 2>pricing and surveillance pricing and why do you think instacart

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<v Speaker 2>was so clear in making that distinction.

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<v Speaker 3>Yeah, So when people think of the term surveillance pricing,

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<v Speaker 3>they generally think of a company that is taking a

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<v Speaker 3>lot of information about them and sort of coming up

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<v Speaker 3>with a price that is very personalized to them. So

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<v Speaker 3>they'll have all of these different characteristics and they will

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<v Speaker 3>use those particular things about you to set the price.

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<v Speaker 3>Instacart was saying, we weren't doing that. It's not like

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<v Speaker 3>we were like deciding that you as Jane Doe, and here,

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<v Speaker 3>you know, we have all this information about you and

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<v Speaker 3>so we were tailoring the price to you. We were

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<v Speaker 3>just like using various algorithms that sort of like are

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<v Speaker 3>testing various things about our app to see if maybe,

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<v Speaker 3>you know, like if we highlight this type of deal,

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<v Speaker 3>you're more likely to click on it. And the way

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<v Speaker 3>they do that is this thing called ab testing, where

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<v Speaker 3>they'll show one customer one thing and they'll show another

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<v Speaker 3>customer something slightly different, and then they see which one

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<v Speaker 3>is more effective for whatever it is that they're testing.

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<v Speaker 2>Coming up, how price experiments started creeping into more industries,

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<v Speaker 2>and how lawmakers and regulators are responding like it or not.

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<v Speaker 2>Consumers are used to being experimented on, at least in

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<v Speaker 2>some arenas.

0:13:49.920 --> 0:13:52.520
<v Speaker 3>You know, you sort of think when you're buying airline tickets,

0:13:52.559 --> 0:13:54.640
<v Speaker 3>you know, or maybe concert tickets or something, you know

0:13:54.679 --> 0:13:57.200
<v Speaker 3>that it's a good that there is a limited.

0:13:56.880 --> 0:13:59.080
<v Speaker 2>Supply, right Bloomberg's Leah Nylan.

0:13:58.840 --> 0:14:01.240
<v Speaker 3>There are only so many any seats on a flight,

0:14:01.400 --> 0:14:04.200
<v Speaker 3>so yeah, maybe like the price might go up when

0:14:04.240 --> 0:14:07.840
<v Speaker 3>there's like fewer seats left. You know. Concert tickets are

0:14:07.880 --> 0:14:10.760
<v Speaker 3>sort of notoriously you know, get expensive the more close

0:14:10.840 --> 0:14:13.319
<v Speaker 3>to the date that you get. But with groceries, you know,

0:14:13.360 --> 0:14:15.400
<v Speaker 3>there's sort of always been this idea that you go

0:14:15.440 --> 0:14:17.079
<v Speaker 3>into a grocery store and everybody gets charged to the

0:14:17.120 --> 0:14:23.200
<v Speaker 3>same price. Increasingly, like, grocery companies and other companies along

0:14:23.240 --> 0:14:26.240
<v Speaker 3>these lines are trying to change that, and they're very

0:14:26.280 --> 0:14:29.240
<v Speaker 3>interested in finding more and more details about people to

0:14:29.320 --> 0:14:33.040
<v Speaker 3>try and tailor the pricing towards them. They've been introducing

0:14:33.320 --> 0:14:36.400
<v Speaker 3>what they call electronic shelf labels at grocery store so

0:14:36.440 --> 0:14:38.800
<v Speaker 3>that they might even have an opportunity to change that

0:14:38.880 --> 0:14:41.680
<v Speaker 3>shelf price throughout the day. And I think that is

0:14:41.800 --> 0:14:44.600
<v Speaker 3>a surprise to just the regular average consumer because we're

0:14:44.640 --> 0:14:47.760
<v Speaker 3>not really expecting that. We are used to going into

0:14:47.760 --> 0:14:49.320
<v Speaker 3>the store and the price is the price.

0:14:50.680 --> 0:14:54.640
<v Speaker 2>When the Groundwork Collaborative and Consumer Reports investigation revealed that

0:14:54.720 --> 0:14:58.400
<v Speaker 2>the grocery company Instacart was running its own pricing experiments,

0:14:58.960 --> 0:15:02.040
<v Speaker 2>many members of the public, we're taken aback. Yeah.

0:15:02.080 --> 0:15:05.000
<v Speaker 3>From lawmakers and regulators, there was sort of a big

0:15:05.080 --> 0:15:07.960
<v Speaker 3>hue and outcry because this is something, at least from

0:15:07.960 --> 0:15:10.840
<v Speaker 3>the regulatory perspective, that they've been concerned about for a while.

0:15:11.000 --> 0:15:13.080
<v Speaker 3>They know that in this day and age, when there

0:15:13.160 --> 0:15:15.640
<v Speaker 3>is a lot of data about consumers out there, that

0:15:16.200 --> 0:15:20.200
<v Speaker 3>retailers are trying to find out this information about consumers

0:15:20.280 --> 0:15:23.720
<v Speaker 3>and do this sort of personalized pricing. But it raises

0:15:23.720 --> 0:15:26.080
<v Speaker 3>a lot of red flags because you don't know exactly

0:15:26.600 --> 0:15:30.960
<v Speaker 3>how various factors are increasing or decreasing the price. There

0:15:30.960 --> 0:15:34.120
<v Speaker 3>are various federal laws that prohibit you from raising or

0:15:34.680 --> 0:15:38.720
<v Speaker 3>lowering prices based on particular characteristics, So for example, you're

0:15:38.760 --> 0:15:41.600
<v Speaker 3>not supposed to charge people different prices based on race,

0:15:41.840 --> 0:15:44.200
<v Speaker 3>or sex, or religion or things like that. But when

0:15:44.200 --> 0:15:46.680
<v Speaker 3>it's a black box like this, like you don't know

0:15:46.800 --> 0:15:50.800
<v Speaker 3>exactly what factors the company is using to make the

0:15:50.840 --> 0:15:54.080
<v Speaker 3>decision about pricing. Among lawmakers, it was also sort of

0:15:54.160 --> 0:15:57.800
<v Speaker 3>a red flag because food is an essential thing, you know,

0:15:57.840 --> 0:16:00.600
<v Speaker 3>everyone has to eat, and especially at a time right

0:16:00.640 --> 0:16:03.760
<v Speaker 3>now when grocery prices have been such a touch point

0:16:03.760 --> 0:16:06.840
<v Speaker 3>with voters. It really did get a lot of lawmaker reaction.

0:16:07.560 --> 0:16:11.320
<v Speaker 2>After the instacart report came out, members of Congress, including

0:16:11.360 --> 0:16:15.080
<v Speaker 2>Senator Chuck Schumer and Senator Amy Klobuchar, wrote letters to

0:16:15.160 --> 0:16:19.680
<v Speaker 2>Federal Trade Commission officials expressing their concerns. Reuters reported that

0:16:19.720 --> 0:16:23.320
<v Speaker 2>the FTC has sent inquiries to Instacart regarding its use

0:16:23.400 --> 0:16:27.800
<v Speaker 2>of AI enabled pricing tools. FDC Chair Andrew Ferguson posted

0:16:27.800 --> 0:16:31.320
<v Speaker 2>on x this week that the FDC quote began investigating

0:16:31.360 --> 0:16:35.200
<v Speaker 2>these potentially unlawful practices in the spring. With all this

0:16:35.360 --> 0:16:38.560
<v Speaker 2>new scrutiny on the role of technology in price setting,

0:16:39.000 --> 0:16:41.920
<v Speaker 2>I asked Leah about how long the issue has been

0:16:42.120 --> 0:16:43.520
<v Speaker 2>on regulator's radars.

0:16:44.000 --> 0:16:46.320
<v Speaker 3>This is something that the Federal Trade Commission, which is

0:16:46.360 --> 0:16:49.720
<v Speaker 3>the US's primary consumer protection agency, has been concerned about

0:16:49.720 --> 0:16:53.040
<v Speaker 3>for a while. During the Biden administration, the FTC had

0:16:53.080 --> 0:16:56.240
<v Speaker 3>started an investigation into a lot of retailers. They have

0:16:56.320 --> 0:16:59.600
<v Speaker 3>this special power that they can ask retailers to sort

0:16:59.600 --> 0:17:02.240
<v Speaker 3>of turn over information for the purposes of a study.

0:17:02.320 --> 0:17:04.439
<v Speaker 3>So they had asked a bunch of major retailers to

0:17:04.480 --> 0:17:07.320
<v Speaker 3>do that, and then they were looking essentially at how

0:17:07.320 --> 0:17:11.560
<v Speaker 3>frequently they use these sort of algorithms to help determine pricing.

0:17:11.920 --> 0:17:15.119
<v Speaker 3>And that study is still underway. The Trump folks didn't

0:17:15.200 --> 0:17:18.480
<v Speaker 3>kill it upon coming into office, but we still don't

0:17:18.520 --> 0:17:20.879
<v Speaker 3>really have the results of that yet. And the FTC

0:17:21.040 --> 0:17:24.680
<v Speaker 3>in particular had already had an investigation into Instacart over

0:17:24.720 --> 0:17:29.040
<v Speaker 3>whether it's Instacart plus this is its membership program was

0:17:29.200 --> 0:17:34.000
<v Speaker 3>sufficiently transparent enough about its pricing and cancelation policies.

0:17:34.160 --> 0:17:36.680
<v Speaker 2>And Instacart has to pay sixty million dollars back to

0:17:36.760 --> 0:17:39.400
<v Speaker 2>consumers as a result of that investigation.

0:17:39.800 --> 0:17:44.080
<v Speaker 3>Yes, they're refunding consumers millions of dollars as a result

0:17:44.119 --> 0:17:47.160
<v Speaker 3>of this investigation because the FTC found that they weren't

0:17:47.160 --> 0:17:50.600
<v Speaker 3>being transparent enough about the terms of this membership program

0:17:51.000 --> 0:17:54.359
<v Speaker 3>and how people could cancel it, because the FTC found

0:17:54.359 --> 0:17:57.680
<v Speaker 3>that frequently people sort of didn't realize that they were

0:17:57.760 --> 0:17:59.760
<v Speaker 3>enrolled in this program and they would try and cancel,

0:17:59.800 --> 0:18:01.920
<v Speaker 3>and instead of giving them their money back to Instacart,

0:18:01.960 --> 0:18:05.520
<v Speaker 3>would give them a credit, which violates some consumer protection

0:18:05.600 --> 0:18:06.880
<v Speaker 3>laws about memberships.

0:18:07.400 --> 0:18:11.080
<v Speaker 2>On Monday, Instacart announced that retailers would no longer be

0:18:11.119 --> 0:18:14.800
<v Speaker 2>able to use ever site software to run item price tests,

0:18:15.080 --> 0:18:19.520
<v Speaker 2>effective immediately now. The company said in a statement, if

0:18:19.560 --> 0:18:22.119
<v Speaker 2>two families are shopping for the same items at the

0:18:22.160 --> 0:18:25.600
<v Speaker 2>same time from the same store location on Instacart, they

0:18:25.600 --> 0:18:30.960
<v Speaker 2>see the same prices period. So Instacart announced they're stopping

0:18:31.000 --> 0:18:34.600
<v Speaker 2>this tactic, which marks one sort of resolution to this story.

0:18:35.200 --> 0:18:38.840
<v Speaker 2>But could what happened here with Instacart set a precedent

0:18:38.920 --> 0:18:42.520
<v Speaker 2>for other industries that are experimenting with this kind of

0:18:42.600 --> 0:18:43.240
<v Speaker 2>price setting.

0:18:43.440 --> 0:18:46.000
<v Speaker 3>I do think that if anybody else is experimenting with

0:18:46.080 --> 0:18:49.720
<v Speaker 3>this price setting, they probably have seen what the sort

0:18:49.760 --> 0:18:53.840
<v Speaker 3>of criticism that Instacart got and are probably going to

0:18:53.840 --> 0:18:56.119
<v Speaker 3>be a little bit more reluctant to at least admit

0:18:56.160 --> 0:18:58.920
<v Speaker 3>that they are doing this, and or, you know, when

0:18:58.960 --> 0:19:01.560
<v Speaker 3>they get blowback a little bit more willing to pull

0:19:01.600 --> 0:19:03.520
<v Speaker 3>back on it. So it will be interesting to see,

0:19:03.880 --> 0:19:06.080
<v Speaker 3>you know, sort of as we go forward, how many

0:19:06.119 --> 0:19:10.080
<v Speaker 3>other companies to sort of try these types of tactics,

0:19:10.200 --> 0:19:13.920
<v Speaker 3>how transparent they are about that's what they're doing, and

0:19:14.240 --> 0:19:17.320
<v Speaker 3>sort of what the reaction is going forward. The basics

0:19:17.359 --> 0:19:19.480
<v Speaker 3>of consumer protection laws that you have to be very

0:19:19.480 --> 0:19:23.479
<v Speaker 3>transparent about what you are selling and at what price.

0:19:23.600 --> 0:19:26.159
<v Speaker 3>If you don't do that, the regulators will come after you.

0:19:33.480 --> 0:19:36.600
<v Speaker 2>This is the Big Take from Bloomberg News. I'm Sarah Holder.

0:19:37.400 --> 0:19:39.960
<v Speaker 2>To get more from the Big Take and unlimited access

0:19:39.960 --> 0:19:43.680
<v Speaker 2>to all of Bloomberg dot com, subscribe today at Bloomberg

0:19:43.720 --> 0:19:47.520
<v Speaker 2>dot com Slash Podcast offer. Thanks for listening. We'll be

0:19:47.600 --> 0:19:48.200
<v Speaker 2>back tomorrow