Levi's reportedly crunched the data to jump on the baggy jeans trend.

According to the Wall street journal, in 2020, Levi signed a deal with Google Cloud and began gathering data points from purchases, web browsing, retail partner sales and its loyalty program into a Google database and running daily machine learning algorithms designed to identify and predict purchase trends.

Jesus Christ.

And how many.

How many buzzwords were in that last sentence?

A lot.

For the last time, Levi's chief Digital.

For the first time.

Not the last time, man.

The.

For the first time, Levi's Chief Digital Officer Jason Gowins told the Journal, Levi's was able to continuously pull together data from 110 countries, not 100 and 110 countries, and 50,000 points of distribution, only 1100 of which were Levi's own stores.

Hmm.

As a result, the new data system helped the company understand that Baggy and Loose silhouettes weren't just for the TikTok generation.

They were for everyone.

As a result, Levi's dove into marketing campaigns like Live Loose, got to like that campaign, and began evangelizing on the trendiness of roomier fits to its retail partners.

And yes, are you buying or selling the impact of data that Levi's claims it has had on its business?

My God, there's so many merchandising questions in this.

I feel like I'm just getting slaughtered and they're going right to me.

So I'm interested to hear where you land on this, Chris.

But.

But look, I'm buying because the price is low.

You're buying.

I'm buying because the price is low.

And things can only go up from here.

Not because I think this baggy jeans example is like the case study I would choose to represent investing in this kind of data.

But I think you and I have heard repeatedly over the course of the last several weeks at all these conferences that the number one thing that the retail CEOs and executives that we've been interviewing have been saying that they're investing in is data to support decision making for them, including in merchandising scenarios.

I think you also have to be investing in AI tools to kind of aggregate this data to really bring that to something that the buying and merchandising teams at Levi's in this case, can really utilize and help inform some of the decisions they're making.

But much like the Walmart story that we were talking about earlier within home testing, I still think that that's going to be the thing that you have to invest in, but you still need this.

The art of the Merchandising here, like, you still need.

A good merchant would know that the baggage jeans trend is coming.

A good merchant understands that.

But I think what's cool about this is that I think you start to position Levi's in a more competitive space against some of the fast fashion players out there, like Shein and Timu, who are taking aggregated data on their platforms.

How much time, like, what people are searching, how much time they're spending engaging with, you know, games or, or shopping experiences for certain products in the app and then using that data to determine how much of products they make, what trends are kind of coming down the pipeline.

I think there's, there's a use case for this.

I think this is just an early stage and maybe not the best example for it, but I have a feeling that you're going to, you're going to take this in a completely different direction.

Chris.

Well, you're not buying.

You're not buying.

I got to tell you, you know me really, really well at this point.

You could probably tell from how I did the.

I'm, I'm.

No, I'm not buying this.

I'm selling this hard.

In fact, like, I think back, this is like, why, why I personally got into the business that we're in is, is to call, call PS on headlines like this.

I'm.

I'm selling this so hard.

This, this story to me is an example of claiming text impact for something that lines up after the fact, after it's happened.

Okay, the begging.

You're just doing this on Levi, like, for this Levi's.

Yeah, on the claim, on the claim that Levi's is attributing their success on the baggy jeans trend to their partnership with Google Cloud.

I just think it's total baloney.

I mean, and seriously, the baggy jeans trend, you didn't see that coming?

I saw that coming.

You know, like, I mean, and you're telling me, like, you even mentioned all the fashion merchants at Levi's went to data from Google Cloud to tell them that baggy jeans trend was calming.

Come on, I wasn't born yesterday.

And, and, and, but, you know, my last, I'd say is, good job by you, Jason Gowans, for trying to make Levi's sound much cooler from a tech standpoint than it probably is.

And, and for my friends there, like, I've heard very, very different varying degrees of how, how tech forward Levi's is and how, and how much they struggle on the tech side of things.

So, so maybe so.

I, I just think this is taking a victory lap for something that is just nicely correlated with your sales performance.

That's what I'd say.

So.

So to clarify, then, I think so you're saying you're selling the, the claim that Levi's is making.

You're not selling the idea that companies should be investing in this type of technology to aggregate data to supply their merchants with, and that there could be a positive outcome from that?

Yes.

Right?

Yes.

A hundred percent.

Yes.

Okay, here's.

I think we're on the same page.

I think we're on the same page.

Yes.

Here's how I'm guessing this conversation actually went down.

If I had, if I had, you know, a bird's eye view in a Macy's, if I was a fly in the wall or not Macy's in Levi's, if I was a fly on the wall in Levi's, like the fast.

The, the, the merchants are like doing their line review.

They're like, biggie Baggy Jeans is going to be the trend this year.

We're going to buy into it big.

And then some computer walk in the sides like, yep, our data says that, that, let's do that.

And then they're like, okay, fine, yeah, let's take credit for it.

That's how it works.

You know that.

Well, that's.

That's a funny thing about retail.

I mean, there's there's only still so much art and sci, you know, so much science that goes into the art of just having to make bet.

I mean, Levi's has to make some pretty big fricking bets pretty darn early too.

So, like, I don't know, I just, I don't.

I'm not buying it.

Maybe a little bit, but not buying it.

All right, all right, fair.

Well, we kind of agree not.

But not on the Baggy Jeans case study.

That's where we'll leave this.

Oh, yeah.

Data.

100% data is the foundation of good retailing going forward.

Yes, yes.