DataBytes 10 – October 2020

The Suds Creative crew is back with a new DataBytes episode. See how the industry has recovered from the initial coronavirus pandemic shutdowns and find out how you can register to get your state’s weekly data.

Transcript

Jason Baumgartner: All right, welcome back to DataBytes, October 2020 edition. I’m Jason Baumgartner, President and Co-founder of Suds Creative. With me as usual, Chris Moriarity, our VP of Consumer Strategy. Chris, how are you today?

Chris Moriarity: I couldn’t be better.

Jason: That’s what I like to hear. Well, let’s jump into it, we’ve, it’s been a while since we’ve talked to you guys, but we have a lot to say so we’ll take a look at the agenda. First, we’re going to give you a national look, we going to show you how wash volumes have fared across the nation. We’ll break that down and take a look at some different trends and some interesting things that we’ve noticed, in the national look. We’ll break down also, what’s a state discussion. We’ll pull out some of the key interesting States, and we’ll give you an opportunity to actually register to receive your state’s information. And we’ll do that a couple of times during this broadcast. And then we’re going to show you something really interesting, and I’m going to save it. It’s traffic density, pre-COVID, and then current traffic density. But this guy, Mr. Moriarty, is going to take you there. And this is really interesting stuff. So let’s dive right in. First, let’s take a look at the national look. Any orange you see 2019, these are 2019 averages. And again, this data is compiled over 1,000 locations across the United States and we break it down state by state. We aggregate all that in this particular view, and we’re looking at week by week, car wash volumes week by week. And then we’re going to compare 2019 week by week, to 2020 week by week. And right now we’re at week 42. Is that correct Chris?

Chris: Absolutely.

Jason: So you can see, I mean, things ever since about week 25, everything just kind of, actually week 22, it’s been really right on track with where we were in 2019. Looking back at what happened when COVID hit right around week 10, you did see the bottom drop off. And again, this is not news to anybody, but that length of time that it took for this industry to recover and recover back to where it was the year before, was only about 12 weeks. And so all things considered, consider yourself lucky being in this industry that we were able to be so insulated. But one really interesting thing, Chris, and you and I were talking about this before we started this broadcast, was look at, excuse me, look at this peak. It’s identical from week 22 of 2019 to week 22 of 2020. And for those of you at home wondering what week 22 is, it’s the week of May 18th. So the week of May 18th is this week was week 22, it was a Monday. Just really interesting as we were talking, you know, how does that hit you? Or what are some things that maybe you can use to correlate the consistency of week 22?

Chris: Well, I just assume everyone took their mothers out for dinner, mom got crazy made a big mess. Everyone’s got to go to the car wash the week after. Actually don’t know mother’s day is around there somewhere. But what was, what was wild about this whole springtime, and especially for those of you who were kind of following along with us, we were waiting for a specific kind of moment to happen in the recovery, which was about 20% off the floor, is what we were looking at before we would say hey, we think we’re consistently on an upward trajectory. What we were all looking for after then is how high up will we go? And as Jason’s pointing out, we returned, you know, right to where we wanted to be, in that same timeframe. What’s, and what’s interesting about, where we started should this return to normalcy and being subject to the problems that we used to have whether it be, just weather, competition, all the stuff we wrestle with daily. It’s interesting, no matter where you are, how those cyclical events just tend to repeat. That’s why I was a history major for one whole semester, Jason, and we have to remind ourselves that, that very little is new. COVID was new, but now that we’re kind of back and, just as this is demonstrating, we’re kind of back into those patterns. This is why we’re able to kind of see things coming again and know what’s normal. And as we get kind of into these traffic patterns that’s what everyone wants to know. Is this happening to me? Is this happening to everyone? Is this happening in my town? I can feel very isolating, but the data really helps shine a light on why anything’s happening.

Jason: Absolutely. And you’ll notice, you know, this is a period of time over the last three or four weeks where typically wash volumes will start to drop. We’re really not seeing that as much. And so for the last several weeks here, 2020 is outperforming 2019, and I just, it just shocks me the consistency, right, week over week. And we’ll get into that some of the States that we’re pulling out to show as examples, that it certainly is either almost identical, or it’s the inverse.

Chris: That May time period, where they kind of had a, you know we all did the big shutdown, everything in life was supposed to be good, and then they said, nope it’s not good, we’re going back, and they pulled it back again. And we got reams of questions about what’s going to happen this time and our prediction was, we are going to see a dip, we believe it’s going to follow about the same shape it did the first time, but it’s not going to go as deep, and it’s not going to last as long. So history was what it was, but I would be very, I would have loved to have seen coming right off that peak in May had they not pulled back, or have re-instituted some of those restrictions, we could have been on a beautiful trajectory. Not that we’re not now. We’re happy to be where we are. We are pleased to be in this industry above many others, but if folks remember, like it was, we were full steam ahead and then they kind of kneecaped us once again,

Jason: Resurgence in some key states. Yeah, well, let’s look at some of those states. So, Oregon’s a really interesting one. Oregon, you know, really since week 27 has outperformed dramatically, outperformed where they were in 2019. You think of Oregon, you think of you know parts of Oregon, you know, quite a bit of rain, this year, you know, some very dramatic events you know, capped off by just a crazy fire season. I know I’m from Oregon, your wife’s from Oregon. Same high school actually. So crazy story, you know, you take a look at this it’s, it was not bad for washing cars, but certainly, you know, the impact of the climate and the lack of rain caused havoc in a number of other ways. But it just goes to show you how important weather is to overall car wash volumes.

Chris: Well, I think you had some again, going back, as I said, going back to the spring time, you know, one of the things we kept reminding people when we’re using the sentiment filters, it’s so important to really look at what’s happening in the news through a filter. Especially Oregon made me think of this. We were looking at the graphs because right now, you know, a lot of the news coverage that they’re getting is, you know, it’s a lot of chaos. It’s a lot of civil unrest, and being someone from Oregon as you are and myself having lived there for a number of years, people think that Portland and Eugene are Oregon. And what this really demonstrates is it’s not. So again, as you kind of think about, what is the business climate today, what is the economy doing? Look out your window, before you turn on the news. And I think this is exactly what you’ll find. When you look at your neighbors and look at your communities and, you know, take care of each other and each others businesses.

Jason: Absolutely. You know, the interesting thing is we go through some of these States that are performing really well against 2019. You go back and you look at it right about here is when COVID hit right? And so you see in the blue, you see this dip and it, you know, it stayed down and then, you know, kind of shot back up. But you see similar types of dips, whether it be one week or two weeks and then shoot back up, that are weather related. And if you’re looking at this, you wouldn’t necessarily look at this and say that there was a pandemic. And then you look at another little dip here, and that was weather related. It may have been related to some of the other things that you were talking about, the civil unrest, but just really interesting to look at this and we’ll look at another one here. Utah is one where again, you know, pandemic starts right about here. Obviously, there was a a big drop off, but then it shot right back up, and really very insulated and has performed extremely well in the third quarter of this year and heading into Q4.

Chris: Well, I think part of this, too, and this is why, you know, we, you’ve got to always separate yourself from how does something feel, versus what do the numbers tell you? I think people have a tendency to be a bit hyperbolic when they talk about a lot of the things this year, you know. So even if the numbers are telling you that, hey, you know, you were in the same place last year, it doesn’t feel that way. You know, when people say this always happens, does it always happen? Or did it happen twice before, but I’m particularly sensitive these days and so on. Plus I think too, in this community there’s always a lot of chatter, and I’m not so sure that people doing well are really putting it out there because they assume, and even if not in this industry and other industries where people aren’t doing so well, they just might not be sharing the news. So it’s, there’s a lot more good than bad out there, especially the numbers we see.

Jason: I’m going to show you one more again, really strong Q3. Talk to me about Nebraska.

Chris: Well go back and watch those DataBytes episodes from in the spring time. And Nebraska seemed like a strange choice for the five or six states that we would kind of showcase every week, but I became so drawn to it because it was such a steady eddy. I mean, what do they call that area of the country between New York and LA? Oh yeah, the United States, right? And these are folks that are insulated from a lot of the chatter and the chaos and people that were just seemingly going about their business as if a very little was affecting them. So it was unbelievable to watch how steady they stayed throughout that whole time period when there was so much volatility everywhere else.

Jason: Absolutely, all right. So let’s look at some States that haven’t fared as well. This is really interesting to me because geographically, these States are all contiguous. So you’ve got South Carolina, then North Carolina, Virginia, Maryland and even, you know I could have kept going, but I ran out of room on slides and we only have a limited amount of time. Look at what’s happening, Q3. Okay, this is 2019. So, these are, that’s good and then this is 2020, obviously well underperforming what happened in 2019. Weather-related?

Chris: Well, again, if we, and we will probably maybe we’ll go back to doing this, but to really put a fine point on the weather discussion, you know, we were kind of creating our own weather maps for each one of these things. And you saw those states getting hammered kind of altogether consistently for a good number of weeks. And what’s this entire industry based on? Behavior.Patterns. You get enough events in a row that it starts to change people’s patterns. There’s going to be a lag effect in terms of how they, because all of a sudden, it’s like you, when you start living without something for a long enough time well, you’re going to keep on doing what you’re doing now. So it doesn’t surprise me. And we’re probably, certainly I do with a little bit more measurement and inspection on those fronts, but that’s why you tend to see these pockets and these waves where things move together because, especially with something like a massive weather system, you know, even though it feels like it’s picking on you, it’s not. It’s having a large massive effect on us, huge areas.

Jason: Yeah, and certainly you mentioned, you know, Delaware, even up through Pennsylvania, parts of Pennsylvania and New Jersey. New York, not as affected, you know, a little bit with the exception of Manhattan, more toward the inland, but certainly those coastal cities along the Atlantic coast, have had a rough time weather-wise the last several weeks, and that’s showing up in those wash count numbers. Oh yeah, you put that.

Chris: You kind of got up to that Ohio and Indiana border there and just everything up into the West of that. Just, they just got skipped. All the additional fun.

Jason: Absolutely. All right, so if you’re interested in seeing your state’s data every single week, we invite you to register. And you can do this a couple of different ways. If you’re viewing this on your computer today, go ahead and just take your camera and take a picture of this QR code. Actually just hold your camera up to the QR code. It’ll actually compose a message for you, all you have to do, it’ll pre-populate databytes and the message and just hit send. And it’ll ask you a couple of questions. The first question is going to be what’s your email address? It’ll ask you to type in your email address, and then you’ll actually be registered. We’ll send you an email with a form, and that form will just ask you to fill out certain states that you’re interested in seeing data on and certain MSAs, and why that’s important we’ll get to in the next section. If you don’t, if you’re looking at this on a mobile device, go ahead and write this number down 528-7403 text databytes to 528-7403. And you can register the exact same way. This is actually a product that we’re releasing called SudSender. It’s a text message program that we’re, that’s integrated into our Sudsy marketing automation platform, which also integrates in with via ODBC and API connection through DRB that we’re very proud of. We have several clients in several states right now that are piloting this. And it’s kind of fun to think about the prevalence now of QR codes and how familiar and comfortable people are scanning those. It opens us up to a lot of what we are calling contactless membership engagement, which is going to be really important heading into the winter this year, especially if there is some type of resurgence in COVID. So take a second here, scan, we’ll wait for you. We’ll give everybody, I’m just kidding. I’m going to move on, but you can pause it, scan it or send us a text message and register and you’ll get those weekly updates in your inbox. I’m going to hand this over to you.

Chris: I mean, the reality is folks are probably watching this with their kids and families. Just have your son or daughter scan it there I’d say it’ll be really easy.

Jason: Sit down the popcorn.

Chris: Exactly hush kids, hush. But, you know, talking about that platform to a couple of people, I had one gentleman just stopped me in my tracks where he said, you know, I don’t want to do any of that because there’s too many steps. Because if you remember when QR codes first came out, it seemed like a great idea, but just the logistical capabilities of open this app, scan this thing and now go over here, everyone was like “Nah, you know what, I think I’m good.” And when we showed him that it’s literally scan, click and it changed everything, changed the tone, and they’re kind of back in play. But again…

Jason: The best part about it, you can have a mask on, you don’t have to unlock your phone to do it. So, it’s very, very cool technology that we’re excited to release. And so you get to be a part of that and see how it works from the inside. Chris talk to us about what we’re looking at here.

Chris: So one of the things that we know, I mean, the state data is amazing, but obviously, if you live in Texas, California or many places, heck Pennsylvania is actually one of the states that really got us investigating the, a more micro level of looking at some of these effects of COVID. So we wound up finding some GPS data where we could drill into the specific geographic areas, certain cities and what we really wanted to see was okay, so where was traffic density this time last year, and where are we relative to that? So for a perfect example here, if you look at Boise where our offices are in beautiful Boise if you were to drive around Boise, you would see, you would see activity, you would see cars, you would see it, it looks pretty close to normal, although I’ve certainly not spend as much time there as Jason has. But if you look at this top graph, you can see where it ends, and if you follow that line over there, it says negative, negative 0.2 which just means negative 20% or down 20% from where they were at this time last year. Now this is one of the problem-solving, sort of resources that we had to go to. Because again, we were looking at Pennsylvania, this is literally what kind of led to this, and certain things just weren’t happening. So we’re looking at the data for Pennsylvania and realized that this specific city was much, much slower to rebound than some of the other cities in Pennsylvania, but now we knew what was going on. So by being able to figure out, you know, what’s exactly happening has really been helpful. Now other cities, like we have Orlando up here, and you can see that Orlando is still down about 40%. They were down about 60%, but that’s fairly explainable. When you have a city that really relies so heavily on tourism and people driving around and Ubers to and from the airport, we would expect a dip like that and not necessarily be overly concerned with the local population, who is most likely to of course be purchasing memberships and washing their cars and so on. So you don’t want to jump to too many conclusions. You want to think about it within context. So if we go to another major city on the next slide, which would be Chicago, this is one that might catch people off guard, because again, they’re right there, you know, 40, 45% down. Well, think about, think about how that city’s laid out. This is a largely commuter-based city. Not that many people live downtown, relative to the suburbs and whatnot anymore. So now people aren’t commuting to work, but as we’ve seen that line steadily grow, it doesn’t mean they’re not moving around. Doesn’t mean they’re not running errands. It just means they’re working from home. So if we go to–

Jason: Oh, that’s a good point there to maybe talk about a little bit is, you know, initially when we did this we’re trying to figure out why this particular location was struggling from a traffic standpoint, from a volume standpoint, and they just happened to be in the middle of a mall, right? Or retail corridor, which well, that was exactly it.

Chris: Where if you had looked at that site, which bless them you know, a year ago or whatever it might be, I mean it was just such a sweet spot. But all of a sudden you realize that, in large part, you’re coat tailing off of those that are around you, like you are benefiting from the organic traffic that they’re bringing. And as great as any site is, you know it’s hard to pull, hard to overcome that on your own. You’re largely going to be affected of course, by the, in the area that you’re in. So as those stores are slowly opening up and rebounding and finding ways to do so, they will bring people in, but it just wasn’t matching the pace of other cities. But we finally did figure out a tool to help shine a light on why.

Jason: Sure, once you understand the why, there, that’s overcomable. So, you know, we just, we need to communicate a little bit more drive. We’re not going to be able to rely on street traffic. We’re going to have to drive people to our locations as a destination. I’ll show you the next one, and this is the one you were telling me about just kind of blew my mind.

Chris: Yeah, yeah it was interesting. I wanted to, you know, I wanted to look around. I didn’t want it to be kind of gloom and doom. I wanted to say, okay, so we know that all our cities and we’re all still trying to figure a lot of things out. Americans are not good with the unknown, just in general, we tend to be a bit reactionary, this just in. So when you read the news and you, of course, you see all the headlines about how well New Zealand has done, handling the pandemic and keeping it under control. So I was curious and I said well, Auckland being, I think, their largest city, if not one of them, I mean, I would guess that significant percent of the population is actually right there. But when you look at their line, they’re up, you know, they’re up almost 20% in terms of traffic congestion, which could be deemed a negative thing, if you’re trying to get around there. But this is where we’re going. If we assume that we’re going to recover and rebound as they have, then we know not only will people return to normal, they will go above and they’ll continue to grow as we started off the beginning of this year. So it’s again, when you try to look for other instances, the whole goal of data, I should say in large part, is not just being explanatory. Like not just looking in the rear view mirror. We want to start gearing ourselves up for, okay, can we see around the corner a little bit? If we follow this path, where we wind up versus that path. And I think they’re a great model to at least show us in theory that greener pastures, believe it or not, are in the future.

Jason: Is that, there’s some cheap joke in there somewhere greener pastures.

Chris: Yeah yes, there are. There is many and to our friends in New Zealand, where we’re going to skip it, and we’re going to save it for what we call DataBytes after hours.

Jason: Okay that’s perfect that’s just–

Chris: Technology-related jokes.

Jason: Once a month, we’re going to film one on a Friday at 4:30 PM and we’ll get a little liquored up and that’ll be the best, the best one of the month. So for everybody listening out there, Chris is very high on buying a carwash in New Zealand. If we get the opportunity. All right, if you’re interested in getting your state’s data and potentially MSA traffic data sent to you weekly, again, scan this QR code, it’ll pop up a text message. All you have to do is hit send. It’ll ask you a couple of questions, you’ll be registered. If not, you can text databyes to 528-7403. Again, databytes to 528-7403. We’ll get you in the same way. Thank you for paying attention for this long to a couple of crazy bearded guys. Look forward to talking to you in a couple of weeks.

Chris: Thank you.

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