Data shows retail businesses have maintained amid Delta variant

Ben Kaplam, CEO of Top Data, breaks down the latest data on how the Delta variant is impacting retailers.

Video Transcript

ADAM SHAPIRO: We want to bring into the stream Ben Kaplan. He is Top Data CEO. It’s good to have you here. And you track different kinds of data. And you’ve recently done the September edition of your COVID impact study, analyzing, you know, those of us who allow it on our tracking devices or on our phones, to tell us about what we’re doing in different industries and in different retail settings. So what are you finding?

BEN KAPLAN: Yes, well, first of all, thanks for having me. It’s really interesting. We’ve been looking at aggregate cell phone GPS data. So we can track for 12 million people where are they going, when are they going there. We can’t track you specifically, but we can track and see overall patterns. First big pattern is that retail businesses, for the most part, have successfully weathered the Delta variant, so Delta variant, a lot of uncertainty. People are like, oh, gosh, are we going through this all again?

And what we actually found is that overall, retail businesses in terms of foot traffic only down about 0.5%, about half a percent since the rise of the Delta variant. And really, what’s been bolstering that is back-to-school shopping right now. And also service businesses, you know, your haircuts, your nail salons, they’ve been doing OK. Not as well as retail, but actually outperforming a lot of other in-person businesses.

The biggest hit right now– movie theaters, down almost 50%. And so what it seems like is happening is people are starting to learn to live with the pandemic, live with COVID, but not all in-person locations are equal. They’re willing to go into a store. They’re willing to shop, probably, behavioral economics tells us, because they have more control over the situation there versus a large in-store gathering or a one-to-one extended interaction they’re avoiding.

So what’s really interesting from an economics perspective is elasticity. It’s usually measured in terms of price. Now we’re seeing it measured for industries in terms of pandemic and how consumers will behave.

SEANA SMITH: Hey Ben, what caught my attention about this list was there are some– in areas where we’ve seen traffic actually decrease, so some of those states you’ve listed out. And some of them aren’t a big surprise. It’s where we’ve seen Delta really surge in states like Louisiana, Alabama, Georgia. But on the other hand, there are some states on that list that have seen a drop in spending where Delta hasn’t surged, states like Vermont and Maine. What do you attribute this decline in traffic to?

BEN KAPLAN: Sure, it’s– well, it’s actually– it’s not just the Delta variant itself, but it’s actually the perception of what that means. So in some places, people are just more responsive. They’re going to adjust their traffic patterns, where they’ll go. They’re more vigilant about staying clear. And other places, people are sort of more willing to just go on and live their lives.

I actually think what we’re seeing overall is that in-store traffic doing better, generally speaking, in the Northeast and the Western US. So generally speaking, in places that have a better overall, you know, COVID response, but some places that actually what happens is very high vaccine response rates. And those are some of those states, those people are still not taking the risk because I think they’ve learned that just because you’re vaccinated doesn’t mean you can’t catch COVID. So that’s the counterbalancing effect there.

And I think the other thing that’s really interesting is that this idea of do consumers have control in certain locations over whether they can steer clear of the virus or not. And so what we’re seeing is in industries where consumers have control– I can decide if I’m shopping for clothes and there’s a bunch of people in there, I’m not going to walk in the store– those stores will do fine. But in other kinds of locations, you know, gyms, movie theaters, large sporting events, there is a noticeable effect.

ADAM SHAPIRO: Is that what you meant by the elasticity rather than price elasticity?

BEN KAPLAN: Yes, that’s exactly what I mean. And elasticity means, you know, how responsive are consumers to changes in some kind of variable? And so, typically, in economics, we think about price elasticity, right? Let’s adjust the price and see if consumers are still willing to buy. In this case, what we’re seeing is pandemic elasticity, meaning if the pandemic cases go up, if Delta variant surges, will people still go into stores and have that same foot traffic? In some industries, they will.

Retail, they’re doing well. Service sector– a little bit less, but still pretty well. In other kinds of in-person industries, they are highly elastic. If there’s a surge, they’re not going to movie theaters. So the prediction is coming up as we enter the holiday season, those industries that are inelastic to the pandemic will still perform well. Those industries that have a lot of elasticity, it’s going to be up and down. You’re going to see that in the stock market, too.

SEANA SMITH: Ben, any indication– I’m curious what you found because you follow this foot traffic very closely, obviously. We’ve been talking a lot about retailers, specifically business owners in general, and one of the big issues that they’re facing in this recovery, the fact that they simply just can’t find the workers. And some of these retailers have had to cut back on hours as a result. Have you seen this affecting shopping patterns or consumer behavior at all?

BEN KAPLAN: Well, I think the biggest thing we’re seeing in terms of that is that consumers are actually adapting their shopping patterns to what the in-store patterns are. So I think people are kind of learning to expect. And, you know, here in San Francisco, right, some stores are open. Some stores are closed. I’m used to being able to shop at the store at night. It’s no longer there.

So what’s actually happening is I think stores, because they have less supply of workers, they’re, like, maybe reducing their hours, sharpening their focus on their sort of target day part. And consumers are willing to go along with that. So largely, those stores that have adjusted hours haven’t seen drop-offs because consumers are operating on this new normal. I think what will be really interesting is the holiday season, because traditionally, it’s extended hours. It’s long hours.

And so we’ll see if those stores can’t get workers for all those hours, will that have a hit on that sort of in-store retail bricks and mortar sales and traffic? It could, and it’s going to have a counterbalancing effect on e-commerce as well. So really interesting to see we’re not in an extended hour period. The holiday period really is. And we’re going to know that pretty soon.

ADAM SHAPIRO: All right, sure. Ben, let’s wrap it up with this. We’ve got roughly 100 million visitors, unique monthly visitors to this platform. And I’m curious, what would you tell them, if they’re retail investors, about the data, what you’ve learned? What would you tell those 100 million people?

BEN KAPLAN: Sure, I think the biggest thing from the data that you can learn is the difference between leading indicators and lagging indicators. And so what happens is a lagging indicator is often the trailing result that’s like, OK, how many hospitalizations do we have? Unfortunately, how many deaths have we had? How many infections?

But you can actually look at the leading indicators first. And things like foot traffic in store, looking at what is the elasticity of certain industries in regard to that foot traffic, that can give you all kinds of insights. So I think in general, in just thinking about investments, thinking about healthcare response, thinking about public policy, we’ve done a little bit too much focusing on lagging indicators.

We should do a little bit more focusing on leading indicators. And actually, those foot traffic patterns, the amount of social distancing that we can measure, for instance, through cell phone GPS data, it’s a predictor of what will happen a few weeks down the line. So one lesson? Leading indicators– focus on that. And that could certainly help a lot of retail investors as well.