00:00 Speaker A
Justin, thank you for being here. I’ve read your report. Um, just lay it out for us. This involves Instacart basically uh charging or yeah, charging different prices for the same item for different people, different parts of the country and we’re not even talking taking into consideration shipping costs, I’m assuming.
00:25 Speaker B
Yeah, that’s right. We had heard some uh tips that Instacart was doing this sort of uh personalized, individualized pricing. Um, so what we did is we recruited a bunch of consumer reports members. Um, we sent them all to the same exact stores. I said, hey, go shop at the Denver Safeway uh using Instacart, buy the same 20 items and then we’ll compare to see what you got at the end of the day. Um, and we were really surprised that actually for the majority of items, we saw differential pricing between consumer and consumer, again, shopping at the exact same store, at the exact same same time for the exact same item.
01:14 Speaker A
And I’m wondering how prevalent this has been throughout history. I don’t think it takes AI to uh produce any kind of algorithmic pricing that might account for different prices here and there. Um is there any precedent to this? what’s the back backdrop there?
01:36 Speaker B
Yeah, this is something that’s happened occasionally over time. I mean, Amazon famously in around 2000 got caught doing this for DVDs. Um some people would get like, you know, 23.99, some people 19.99. They got caught and they were they were embarrassed by it. They they apologized said this was wrong. Um and so researchers have been kind of looking for it ever since and there’s been a few examples here and there. Um but this is this was surprising to us the extent to which they were um again, for so many products for so many people were um charging different prices as much as 23% difference um for for the same item. So some people might be getting Skippy for 2.99, some people were paying 3.39, some people paying 3.69 for the same thing.
02:26 Speaker A
Yeah, that’s a huge difference. Um, let’s talk about some of the companies involved here. First of all, Instacart has said that they’re stopping the practice, but nevertheless, uh it was found that Target items were part of this survey or part of the problem here. And consumer reports uh says that you’re saying that in your pricing experiments at Target. Target told consumer reports it had no business relationship with Instacart, yet Instacart acknowledged scraping Target’s public prices and adding amounts for costs. So, uh what went on here?
03:07 Speaker B
Yeah, so I think there there’s some people who deliberately took advantage of software that uh Instacart offered and said that you can do this sort of personalized pricing. Um, but again, you can go on Instacart and buy uh through companies that they don’t have a relationship with. Instacart still would have the ability to set the prices themselves. Um and so in this case, Target said that they weren’t involved. it was all Instacart’s decision. Um a lot of Instacart uh uh clients said that they weren’t doing this, um that they charge the same in the store that they do for folks online. And like you said, since since this all was exposed last month, Instacart says they’re not allowing uh anyone to do this anymore. Um but you can this is just one company, um as you say, AI is more prevalent now, we might start to see this in more areas over time. So that’s why we’re going to continue to do this sort of research, but also work on potential legislation around the country, um to at the very least require transparency, but in some cases maybe this should just be prohibited. Uh there should just be one price that we can decide to pay it or not.
04:32 Speaker A
Yeah, really interesting there. and maybe we can circle back to the regulatory front. Just talk to us about the bigger picture on personal data and what we’re talking about surveillance pricing and some of the things that you’ve found and some of the trends in place here.
04:47 Speaker B
Yeah, I mean people are definitely looking more and more at this. and that’s the concern as a consumer advocate, if companies know more and more and more about us, they know how much we’re willing to pay for Skippy. They know I’m I’m more demanding, I’m I’m more desperate. Um they’re going to charge me more for it than than someone else. And so for each transaction, if the company can take all the value, the consumer is receives less of it. I think that’s worse for us overall. Um again, there is a goodwill cost when companies get caught doing this. I think Instacart saw like a 6-7% um hit to their stock price um and it still has not recovered since the uh uh the investigation came out. Um but you know, it’s actually really hard to find this sort of thing. We had to do a very long study and recruit a lot of people and make sure our methodology was correct. Um and again, more and more companies are going to try to slide under the radar, um and try to do this, especially in concentrated industry with only, you know, one or two choices, they have more power over people. So they have potentially have more capacity to to try to extract again, the relative uh surplus from any transaction.
06:05 Speaker A
Well, I I can appreciate the difficulties uh and the extent to which you’d uh all the measures that you took to to to collect this data. Um I want to circle back to the regulatory front. You mentioned that uh you might be influencing some regulation here. Uh tell us the extent of that.
06:27 Speaker B
Yeah, so there’s been like some legislation introduced around the country. New York actually had a law go into effect, um this month or last month where they have to disclose if prices are or changed algorithmically based on individual data. Um we’ve also seen legislation to just prohibit a lot of personalized pricing. Um it got pretty far in California last year, um is going to be brought back um this session. We’ve seen legislation introduced federally as well. So I think we’re going to see it in probably maybe a dozen states this year. Also the potential for federal. Um and also that you know, the Federal Trade Commission might get involved. I think the Federal Trade Commission said that they are investigating this practice and had significant concerns about it.
07:22 Speaker A
We got time for one more here. any other pricing discrepancies or anything that’s been on your radar uh that you’d like to share with us here.
07:34 Speaker B
Yeah, I mean the other other other, you know, factors that might be concluded, you know, geolocation, there’s been some stories that if you’re close to a store, um they might give you a a a lower price than if you’re farther away and more desperate. Um there’s been examples of you know, companies based on IP address that they think you’re coming from um a richer city. Um maybe they’ll show you higher prices for hotel rooms or other services than like if you’re reserving online from somewhere else, um reserving, again, reserving the same particular hotel. So there’s more and more, you know, more and more data about us out there, more and more capacity to leverage that. People are always looking for extra margin. Um I and and again, that’s understandable like we I totally get it. Uh but from a consumer’s perspective, they just want some degree of fairness, some degree of like, you know, not try exploiting information that you don’t necessarily deserve to have to try to find out more about how much I’m willing to pay.
08:44 Speaker A
All right, we’re going to leave it there. really appreciate your investigation here and sharing the details with us. Thanks.
08:52 Speaker B
Thank you.