Artificial intelligence is already helping auto repair shops save time, improve communication, and increase efficiency. In this webinar with Dan Molloy, we explore how Molloy Sales Development Group and AutoVitals are using AI-powered tools to help shops work smarter, not harder.
You’ll learn:
- A fluff-free breakdown of what artificial intelligence actually is
- The most common AI tools used today
- Ways AI can help generate inspection notes, texts, and marketing content
- How AI can simplify reporting, KPI analysis, and shop operations
- Real-world, shop-tested examples you can start applying today
- and more!
Episode Transcript
*This transcript was generated with Artificial Intelligence. Error may occur. If you identify an error please contact [email protected].
Lauren Thunen (00:00:01):
There we go. Good morning and good afternoon, everyone that has already joined us. Thank you for being prompt. We really appreciate it because we are going to get straight into it. And it’s actually funny, I was looking at the attendee list here and I see that someone’s AI note taker is in the meeting room. So AI is among us, very on topic for today. So hi, Firefly’s AI note taker. Hi, Richard. Thank you for joining us. And today I’m really excited about today’s webinar. We have a great guest, Dan Molloy. I’ll let him introduce himself in just a second. But just setting the scene, we’re going to be talking about practical artificial intelligence for your auto retire shop. And why I’m so excited about this is not because we’re talking about artificial intelligence, but really we’re going to be talking about what it means for you because it means a lot and we’ll give an overview of how it’s in play in the world today and what it means and what it does and what it’s capable of.
(00:01:04):
But there hasn’t been a ton of discussion, at least that I’ve heard of what can you start using today in your shop and how you can start experimenting with it and how it’s really going to impact your bottom line. So that’s what we’re going to spend most of today talking about. My name is Lauren Tunan. I have the pleasure of being the director of partners and product marketing at AutoVitals. I am also very lucky because AutoVitals has been a very AI-forward business so far in which that we’ve gotten to learn a lot as employees of AutoVitals. We’ve had the opportunity to test a lot of different softwares that are available on the market today. I’ve done a lot of research on my own because it’s a personal interest, so very excited to share all that with you today. And Dan, would you go ahead and introduce yourself?
Dan Molloy (00:01:51):
Sure. Lauren, I’m thrilled to be here with you. This must be our fourth or fifth webinar together, which is fun. But again, I’m Dan Molloy and I’m the founder of Molloy Business Development Group and are under our moniker of SalesMax Plus, which is what we do. We’ve been in business for almost 30 years. I want to do a shout-out to my friend. I just see a Richard Garrett. If that’s my Rich that I know for a while, I know Rich for about 25 years and we’ll see if we see anybody else that we know here. But anyway, I’m thrilled to be here. This is a great exciting topic. So let’s do it.
Lauren Thunen (00:02:34):
Yeah, let’s get straight into it. So I’m going to go over briefly what our agenda is for today’s webinar. We have about an hour together. We’re first going to start with just going over a brief breakdown of what artificial intelligence actually is. For those of you that might not be as familiar, a little bit behind the curtains of how it works. We’re not going to get super into the weeds there. Just a brief overview. Review some of the popular artificial intelligence tools today, what they’re good at, give some examples of what we use them for and what you could be using them for. Again, briefly go over, we’re not going to go over every single risk and consideration, but just call out some of the most important risks with using artificial intelligence. And then really what we’re going to spend the bulk of our time today is talking about how AutoVitals and Molloy Sales Development have been using artificial intelligent and embedding it into our products so that you can use it day-to-day in your shop safely and then wrap up key takeaways.
(00:03:31):
But before we really get into the what is AI, I have a poll that I want to launch for you guys and it’s just asking how familiar you are with artificial intelligence today. So you should see a poll pop up on your Zoom screen. It’s going to ask you, how often do you use artificial intelligence in your shop today? All the time, occasionally, rarely, and never. So I’m going to give everyone a minute to start to answer that poll, but I’m going to keep moving with our webinar as you guys answer that and we’ll review the poll results once you guys are done answering it, if that sounds good. Also, just a few housekeeping things. You should have access to a Q&A and a webinar chat at the bottom of your Zoom screen. There should be a chat and a Q&A button. Feel free throughout the webinar if you have questions, comments, concerns, throw them in the chat or the Q&A.
(00:04:19):
We will probably answer those toward the end. If we can’t get to all of your questions, we get a nice export from the meeting of everything you’ve asked and we’ll reach out to you individually.
Dan Molloy (00:04:28):
I’ll keep an eye on it for you, Lauren.
Lauren Thunen (00:04:30):
Perfect. Sounds good. All right, let’s get into it. So what is
Dan Molloy (00:04:35):
Chat is disabled, by the way, just so you know.
Lauren Thunen (00:04:38):
Okay. Use the Q&A. I tried to enable it before, but technology’s great until it doesn’t work. So use the Q&A. We’ll keep an eye on that. So a brief overview of what artificial intelligence is. So at its core, it’s a computer science that enables machines to simulate forms of human cognition. They can learn from data, they can perform tasks, they can generate output. Now it’s interesting because we’re talking about artificial intelligence today in 2026, but the study of artificial intelligence has actually been around for quite some time. It was actually coined in the 1950s, I believe it was 1956 at Dartmouth University. And that’s when people really started to experiment with how can we train computers to be able to simulate human cognition? How can they produce and learn from data just like our brains do? Really where the massive shift and now we’re all talking about it today happened was recently in the past couple of years when generative AI became at the forefront and we as consumers and the average person had access to tools like ChatGPT where we could actually use artificial intelligence in our day-to-day lives.
(00:05:49):
That’s what the real new thing has been. And what generative AI does is it takes a massive amount of publicly available information for the most part as well as some training and it learns from all of that massively public available information. The internet is one of the biggest sources. It has crawled, indexed, and understood most of what’s available on the worldwide web that’s public information. And so what AI is doing is it’s recognizing patterns. So that’s why when I asked ChatGPT to finish the sentence and it said, instead of turning left, Lauren turns blank, it’s going to say right around the other direction because it’s recognizing those patterns from all of the information that it’s analyzed and anticipating what the outcome is going to be. So that’s
Dan Molloy (00:06:45):
Lauren, I just want to just
(00:06:48):
Type in here for a minute. I’ve been engaged in studying language and communication for 45 years and for the past, I don’t know, 20 years using call tracking and things like that. And then about 10, 12 years ago, the AI started to come up and it was titled Keyword Spotting and Speech Analytics and things like that. It was very rudimentary, but we were all over it. And we used to do side-by-side studies between the
speech analytics and keyword spot. And you’re saying it could find patterns in language and it could find keywords pretty easily, but it really wasn’t that accurate. And then to your point, about three years ago, it got to be really interesting and really powerful with the use of … It really started to get very user-friendly and way more accurate, the AI agents. And so we’ve been heavily engaged in all that stuff.
(00:07:59):
But yeah, it’s followed the nice progression that you outlined.
Lauren Thunen (00:08:02):
Yeah, absolutely. And one thing to call out from what Dan said is that artificial intelligence gets better the more information that it has and the better the information it has. So three years ago when it was relatively new on the scene, didn’t have a ton of information, the output wasn’t great. It hadn’t been trained by … I’m going to use ChatGPT, for example. They have folks that work for ChatGPT for OpenAI and their whole job is to train the models and help guide the output. So just like a human, we get better at our jobs, the more information that we get and the better that information is. Artificial intelligence is the same. So one thing to call out as we go through some of the risks and considerations is if you put trash in or the model is trained on trash, you’re going to get trash out.
(00:08:51):
The output is only as good as the input. So before we move on to the next slide, I just wanted to pull up our poll results. So of the folks that answered the vast majority, over 60% using artificial intelligence all the time, awesome to hear, excited to hear a little bit more about what those uses are as we go through this. About 25% occasionally and about 10% rarely. So thank you for sharing that with us. That gives us a good guide for what we’re
Dan Molloy (00:09:15):
Going to talk about. Can I share one other point?
Lauren Thunen (00:09:18):
Yeah.
Dan Molloy (00:09:20):
Given my seniority here, I got involved in the internet early in the game, early in the early 90s by the mid 90s, I was doing streaming of music and things from venues here in New Jersey just as a hobby we would have fun with it, but it was really a go, go, go, go time. I was just talking about it with my wife when we were having lunch together and doing HTML and things like that in the mid 90s, sitting at the computer and dialing up. It was all done by dial up back in the day. So this reminds me of that time period only. Only the caveat is that it’s way faster. This is moving exponentially faster than that go, go, go, go, go time period back in the 90s. So it’s very exciting to be alive and to be in business. And as we were just talking, while I was having lunch with my wife, there was a congressional hearing going on in the background.
(00:10:31):
They were talking about AI eliminating jobs and all that. And I was like, wow, I don’t look at it like that at all. I look at it like this is one of the most exciting times to be alive. If you’re creative and you have ideas and you want to do things and you want to help companies and help other people, really exciting time to be alive, my opinion.
Lauren Thunen (00:10:55):
Yeah, absolutely agree. Absolutely agree. So as we go through … Oopsies, skips ahead. So today, again, this is going to be changing. This isn’t an exhaustive list, but some of the things that artificial intelligence is really good at today is number one, data analysis, analyzing large sets of data, not just numbers, text, pictures, images, et cetera. It is very good at analyzing data because that’s its foundation. That’s how it’s built is to recognize, and this goes into the next thing, recognize patterns against large data sets and then produce output. Some other things that it’s very good at is coding, writing instructions for computers to
perform tasks. Why is it good at this is because coding is somewhat scientific and mathematical. It follows a predictable pattern so it’s able to replicate everything it’s learned and produce coding. It also today, and different models are better and worse at this, we’ll go into that next, is content creation.
(00:11:51):
It is extraordinarily good at facilitating human language and writing in a way very similar to how a human would talk. So I can ask, I’m going to use Claude to write an essay on why AutoVitals is the best DBI provider and it will write however many words you want, 100, 200, 10,000 words, very detailed, very natural. It is very good at producing content. Is getting better at image generation. I can point out a couple of the images in this slide deck are actually produced by AI. And again, it’s doing that because it’s recognizing the pattern in pixels and how to create an image. So it is very good at producing original content. And then automation is one of the biggest things that I think a lot of businesses are using it for is how can we use artificial intelligence to assist us and automate parts of our job that are pretty repetitive.
(00:12:46):
Again, it’s very good at pattern recognition. So anything that it’s repetitive, it can use technology and artificial intelligence to perform tasks with less human input. You always want human oversight, but with less human input. Anything to add here, Dan? Well,
Dan Molloy (00:13:00):
I just wanted to let everybody know that Lauren is not real. He’s really an avatar.
Lauren Thunen (00:13:05):
Yep, exactly. I am AI
Dan Molloy (00:13:07):
Generated. I had to say that.
Lauren Thunen (00:13:09):
Yeah.
(00:13:13):
So some risks and considerations … Or sorry, nope. We’re going to go popular AI tools, then risks and considerations. So some of the tools that you probably have heard about using today, ChatGPT, this is probably by OpenAI. This is probably the first major consumer tool that most people started to hear about. ChatGPT is a very good starting point for most folks. It’s a very well-rounded AI model. It can do a lot of things very well. You can build agents, you can have projects, it can generate images, it can analyze large data sets. Again, very good starting point. Claude is, I think, probably the next most popular, at least in my mind. Some of the things that Claude is good at is that it has much larger context windows, which means you can input so much information into Cloud. It will retain it, large datasets. If you have a spreadsheet of every single one of your business metrics from the time that you started business in 1990 to today, it is the best AI tool in the market today for consumers that is going to be able to understand and store and analyze large data sets.
(00:14:24):
It also has a little bit more robust thinking, so it’s better for complex analysis than ChatGPT. Trade-off with that is because it’s running through a more robust analysis on each one of your queries. It takes a
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little bit longer. So with ChatGPT, you pretty much get an instantaneous response, or you can if you want to. That takes a couple of seconds. Cloud can take a few minutes even more depending on how complex the task is to generate a response. Some other ones, Gemini, Google Gemini, and Copilot, Microsoft Copilot. These AI tools are very deeply embedded into either the Google Workspace or Microsoft. So if you’ve ever … Just an example, I’m on Google Chrome today. If I search best places to travel over the summer, I’m going to get my websites down below. But the first thing I’m going to see is an AI overview.
(00:15:17):
This is generated by Google Gemini. And so again, it’s built into a tool like Google that you might already be using today. The first thing I see is Google Gemini’s summary of this.
(00:15:30):
And then last but certainly not least is today and continuing on there’s more tools like AutoVitals and Molloy Sales Group that are embedding artificial intelligence directly into the tools, software, services that your business is already paying for. Now, that is what we’re going to spend the bulk of the time talking about. If you want to go test ChatGPT, Cloud, Gemini, et cetera, we’re going to go over some of the risks and considerations for doing that. By all means, go do that. But really what we’re spending today talking about is AI solutions that are already in the products and services that you’re using that are trained specifically for the automotive industry and understand how your business really functions. Because while ChatGPT and Cloud and Gemini and Copilot are great, they’re trained on the whole entire internet. So that means that one of the things that AI loves is Reddit, that any person ever who’s told someone how to replace the shocks and struts on their vehicle and how much it should cost, ChatGPT and Cloud are taking into context.
(00:16:38):
So again, large amounts of information might not always be accurate for your specific shop and process versus tools that are embedded in most providers like Dan and AutoVitals, we are taking in consideration only what it needs to know. We’re only training on it once what it needs to know so it can ignore the rest of the.
Dan Molloy (00:16:58):
Practical, practical.
Lauren Thunen (00:17:00):
Exactly.
Dan Molloy (00:17:01):
The title of this thing. It’s been my search and my mission to help my clients and to help everybody out there is to take this technology, especially for me in the domain of language and communication and make it so practical that you can start to use this stuff right away and it can have an impact on your business immediately.
Lauren Thunen (00:17:23):
Yeah, absolutely.
(00:17:25):
So I’m excited to get to that. So let’s go through the last one of these summary slides. So risks and considerations as you’re starting, and again, a lot of folks here are using AI all the time, so hopefully you’re already taking this into account, but artificial intelligence is powerful today. Still for the most part, we recommend that there’s always a human reviewing the content that it is producing and that you have
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some level of oversight to it. That’s because number one, we talk about, again, trash in, trash out. Especially if you’re using models like Gemini and ChatGPT that are just trained on everything that’s on the internet, it can produce false information. There’s false information or information maybe you don’t agree with that’s out there on the internet. And one thing about artificial intelligence is all of these models are very confident. They’re like, “Here’s my recommendation that’s going to take your business to the next level.
(00:18:22):
Here’s what you should do. Here’s your next three steps.” If it’s incorrect, it’s going to be confident that it is correct information. So you really want to review and say, “Does that make logical sense to me? Does that kind of fit where I was already thinking about it? ” And also I see this all the time, you say like, “Hey, ChatGPT, I don’t think that’s necessarily right.” And then again, it’s going to be confident and it’s going to be agreeable and say, “You’re absolutely right, Dan, that isn’t correct. Here’s what I should have said instead.” It’s confidently wrong sometimes and it’s very agreeable when you try to correct it. So that’s something that you always want to be keeping an eye on is that does what it is producing make logical sense? Again
Dan Molloy (00:19:04):
When we started working, Lauren, with AI agents three and a half, four years ago, they used to hallucinate all the time. It was just you didn’t know what was going to come out of what they were going to say, but I haven’t heard anything mistakes. I mean, it’s gotten exponentially more user-friendly and just much better quality. And I don’t hear the hallucination, at least from the voice side. It certainly makes mistakes in other ways, but on the voice side is pretty solid.
Lauren Thunen (00:19:40):
Right. Yeah. It’s definitely, again, these risks are becoming much less as it gets smarter and more intelligent, so that is great. We’re talking about it at a good time. Three years ago, we would’ve spent our whole entire call talking about hallucinations. The second point, which is probably the most important is data privacy. Now, if you just go to claud.com or chatgpt.com and start playing with their free version that’s available to consumers, for the vast majority of models, if you’re not paying and you don’t have your data privacy settings turned on, anything that you enter into that public interface, that consumer facing interface is going to be used to train future models and to train future responses. What that means is anything that you enter is not private. It could be resurfaced in another response to someone else using a model. So an example is like, well, I’m going to use Automotives as an example.
(00:20:41):
I enter into a free model all of our product plans for the next six months, then someone from one of our competitors goes into ChatGPT and says, “What’s AutoVitals working on? ” Because I entered all that information into a public interface, it can surface that information because it’s being used to train the models. So when you are working with any model that’s not built into your tools and with models that are built into your tools, you want to make sure that what you’re working with, you have a private account. Typically, that means a paid subscription. So for ChatGPT, for instance, the paid subscription’s about 20 bucks a month and that way your inputs and all of your chats are not used to train the model. So what you’re talking about is private, it’s not retaining that information and using it in future responses for other clients.
(00:21:36):
It’ll use that information in responses to you so it can learn from your inputs, but it’s not someone random who logs into ChatGPT isn’t going to be able to learn from what you entered into the model. Anything to add there, Dan?
Dan Molloy (00:21:51):
No, I’m good.
Lauren Thunen (00:21:53):
Melissa asked, and I’m going to answer this question live, “What is a good AI to use for sensitive business information if you wanted to do business forecasts or stuff?” I think that today my personal opinion, so this is Lauren’s personal opinion, is Claude is the best at doing business forecasting and analysis and processing large amounts of information. When you sign up for Cloud, you’re definitely going to want to get a business account or a business subscription that has more privacy controls and you really are going to want to dig into their settings pages, understand, make sure you all you have all of your settings accurate so that your information is protected. The other thing I will say is never enter or input customer identifying or business identifying information. So you probably don’t want to say in your business forecasting and all that, this is for ABC Automotive located at 123 Main Street and here’s all of our customer information.
(00:22:50):
When you input it, you’ll probably want to remove any of that sensitive information and just say, “I run an auto repair shop.” You can probably give it some geographical understanding in Nebraska small town, just so it has some idea when looking at business forecasting and then you’ll want to remove any sensitive information just to be extra safe, especially for a lot of that analysis. It doesn’t need your customer names, it doesn’t need your shop address, things of that nature.
(00:23:21):
And then last but certainly not least, before we move on from the risks and considerations, today we’re looking at artificial intelligence as a copilot to what you’re already doing. So it’s augmenting the humans in your business, your rational thinking, your judgment, and it’s amplifying you and your team’s ability to produce output skills. It’s not substituting your expertise. For instance, I use artificial intelligence to help generate this presentation today, but all of the notes, all of the things that you see on the slide today were manually inputted by me and then artificial intelligence helps shape it into a PowerPoint presentation that looks nice and has our brand colors because it takes a long time if I was just to do that in PowerPoint. That’s a good example of it’s augmenting my skills. I’m not just completely outsourcing the contents of this presentation to artificial intelligence. How that looks for your shop we’ll talk about in a little bit.
(00:24:20):
Anything to add here, Dan?
Dan Molloy (00:24:22):
You’re on a roll, buddy. Keep going. All
Lauren Thunen (00:24:24):
Right, sweet.
Dan Molloy (00:24:24):
All
Lauren Thunen (00:24:25):
Right, so let’s get into the meat of it. So how artificial intelligence can help close the gaps in your shop. If you run an auto repair shop, we’ve all been this guy at one point or time, paper everywhere, frustration, so much to do, car counts through the roof. You’re just trying to make it through the day. We’ve all been there. It’s part of running a shop. But also part of running a shop, probably got into the business because you want to take care of your community, you want to take care of vehicles and make sure everyone’s on the road to drive safe vehicles. Take care of your community, do a great job at fixing cars. Probably why
most of us got into the business and make a little money, of course. But then when you own a shop, as everyone on this call knows, you’re also expected to be experts in marketing, sales strategy, Melissa, like you said, business forecasting, website content, analyzing business analytics and more.
(00:25:18):
That’s a lot. You’re expected to be Superman or Superwoman in your shop managing all of this. And for the vast majority of us, like myself included with everything I do for my job, I’m not an expert in all of those fields. It’s very unlikely that you’re going to be an expert at fixing cars and an expert in marketing and an expert in website SEO.That’s a lot to manage. And if you are, kudos to you. But we’re going to talk about today how artificial intelligence help you close those gaps in your shop so you’re able to focus on what you’re really good at it and then artificial intelligence can help you in some of the other areas.
Dan Molloy (00:25:55):
So now I have something to say.
Lauren Thunen (00:25:57):
There you go.
Dan Molloy (00:26:00):
That was me 25 years ago, 30 years ago when I became a partner in a company called Procare Automotive. Some of you may know it. It was out in Ohio. We had up to 129 locations and it was chaos. The chaos was everywhere. And the challenge was that we spent a fortune to make the phone ring and to generate sales opportunities. And what happened was I watched them fall through the cracks. And there was nothing we could do about it because we had all these hundred and some odd locations and millions of phone calls every year and the phone calls were just going and the people were just like this gentleman in the photograph, just out of control and the opportunities would just slip through the cracks. So this became Don Keoti’s windmill I’m tilting at Moby Dick’s white whale. This became my white wheel to be able to find and develop processes and systems to be able to retain, to keep the sales opportunities in the business.
(00:27:13):
I did the math with one of my colleagues a little bit, he’s on here, Glen and I did the math. You know what it costs to generate one sales opportunity?
Lauren Thunen (00:27:21):
How much?
Dan Molloy (00:27:22):
In one of the businesses? Take a guess. What do you think it costs to generate? And maybe this is an impromptu survey. What do you think it costs? This is for everybody. You type in the … Well, chat wasn’t enabled, but anyway.
Lauren Thunen (00:27:36):
Type in the Q&A.
Dan Molloy (00:27:38):
Type in the Q&A. What does it cost to generate one sales opportunity in the average business? What do you think it is, Lauren?
Lauren Thunen (00:27:47):
Ryan said 90 to $150.
Dan Molloy (00:27:50):
There you go.
Lauren Thunen (00:27:51):
I’m going to go higher basing off of what I know about some of our business. I’m going to say $900. We’ve got
Dan Molloy (00:28:00):
How much? 900?
Lauren Thunen (00:28:01):
$900. We got very busy. The other
Dan Molloy (00:28:03):
Repair, not in your business, the other repair
Lauren Thunen (00:28:07):
Business. Then I’m going to go with Ryan and say 150. Barry says 30 bucks. Ryan says 180 high ends. Matt says 100 bucks.
Dan Molloy (00:28:18):
Well, we got to Ryan. Listen, I think Ryan’s been smoking the same stuff I smoke. I’m joking with you. But the point is that it’s exactly, he’s spot on. We just did the math. We know because we have the AI tools to actually measure every sales opportunity coming into the businesses. We know the numbers. And if you take the sales opportunities and divide it by your overhead, it comes out to 150 to $200, exactly right in that spot. And this is what we were experiencing when I had that big company. I was a partner in that thing and it was so frustrating to take $25,000 out of my pocket and send it off to an advertising firm and then go into the stores and find out that, well, Dan, the ads, the advertising is not pulling. It’s not working. And that was just one part of it.
(00:29:11):
But then there was missed calls during the day. People get so busy, the phone rings, people are at the counter, they’re too deep at the counter and it’s kind of crazy and calls just get dropped and then there’s before hours and after hours calls. So it’s a real challenge.
Lauren Thunen (00:29:30):
I mean, that leads perfectly. You set yourself up into what we wanted to talk about as one of the first practical applications. So talk to us a little bit more about how you guys are using artificial intelligence to help capture some of those lost opportunities specifically on the phone.
Dan Molloy (00:29:47):
We created a whole program we’re called the AI Max Sales Agents. And the point is to capture every sales opportunity that comes in before hours And after hours. Number one. Number two is to capture all the missed opportunities. After a certain number of rings that we program over time, it’s really based on time. After a certain amount of time, if somebody at the store doesn’t pick up, it goes immediately to the agent. Then the agent can have a nice dialogue with them. It’s really quite interesting. Should we do a demo? Should we just do something, take a shot and do something live right now to show people what it’s all about?
Lauren Thunen (00:30:32):
Yeah.
Dan Molloy (00:30:33):
Yeah,
Lauren Thunen (00:30:33):
Go for it. Yeah, I’ll stop sharing.
Dan Molloy (00:30:35):
Let’s do it. We’ll take a shot. What is life without risks?
Lauren Thunen (00:30:41):
Yeah, exactly. Live demos are always risky, but that’s what we’re giving you guys today.
Dan Molloy (00:30:49):
So this is the backend of one of our processes. This is where we collect calls and we call this CallMax plus with AI data mining. And what we’re doing here is collect, this is happening in real time. And what you’re seeing over here, this is all the data we’re collecting from all the calls. Then we take all this data. Is it a sales opportunity? Who’s a salesperson? And a lot more. I don’t want to get into it. I could get lost in the weeds here. I don’t want to do that. Suffice it to say that we’re collecting all the data from all the calls coming in. That’s number one. Number two, we have over here another platform that we built. This is Sales Max Plus. And in here, one of the things we do with AI, this is real data in real time of real missed opportunities occurring inside a company.
(00:31:49):
And as you can see, there’s a lot of them. And then we also, and we break it down into the appointment requests, hangups, general inquiries, service or price requests, vehicle status like that. But then we have it set up so that it can be managed. This is the same data in a very easy to use form that you can control over here with the filter. You want to look at what’s happening today. You want to look at what’s happening in a particular one particular store. We’ve got it for you. It’s right here. Again, like I said, practical. So you can stay on top of every missed opportunity that’s coming in the business. The other thing that is pretty cool, I just got to find that. Check this out. When there’s a missed opportunity that hits the network, before hours, after hours, or the store gets notified by email instantly.
(00:32:54):
In addition to the reporting, which is running at the same time, this is all happening right now in real time, that the store staff, we direct the missed opportunities to whoever you want to receive them. So the price request can go to one person. The appointment request can go to another person.
(00:33:19):
The information requests or customer service requests or status calls can go to somebody else. It’s all right here, who the customer is, the date and time, and all this kind of stuff. Now the other thing to do a demo just to show you what it looks like. Let me see. New call. So here goes folks with a demo of what they’re like now. It wasn’t like this three years ago, but check it out.
AI Agent – Jessica (00:33:54):
Hi, this is Jessica with Molloy. Our team’s tied up right now, but I can help with appointments, pricing, or I can get a message to the crew. What can I do for you?
Dan Molloy (00:34:02):
Hey, Jessica. This is Dan. I wanted to find out if you could get me a price on a brake job for my Camry.
AI Agent – Jessica (00:34:11):
Yes, Dan. I can help you with a price on a brake job right now. My name is Jessica and you’ve called the right place for brake services. We’re a full service shop and we handle brakes, tires, alignments, oil changes, big repairs like engines and transmissions, and even small fixes like flat repairs. Plus we offer payment plans if you ever want to take advantage of that. Now, while I’d love to give you an exact price for your Camry, we’re committed to accuracy. So how about this? We’ll provide you with a free inspection and then give you a precise quote. How does that sound?
Dan Molloy (00:34:42):
Well, let me ask you a question, Jessica. First of all, Jessica, have you ever been in a webinar?
AI Agent – Jessica (00:34:48):
Ah, good question, Dan. I haven’t personally been in a webinar since I’m an AI assistant, but I’m here to help with anything you need, whether it’s about your car or something else. What’s on your mind?
Dan Molloy (00:34:59):
Well, somebody told me that for my brakes that I really another dealer told me I needed calipers. What the heck are calipers? I don’t even know what they are.
AI Agent – Jessica (00:35:13):
Ah, I see, Dan. Calipers are an important part of your braking system. They’re the components that squeeze the brake pads against the brake rotors to create the friction needed to slow down or stop your car. Think of them as the muscle behind your brakes. If a dealer mentioned you might need new calipers, it could mean they’re worn out, sticking or leaking brake fluid. But don’t worry, our team can inspect them for free to confirm if they really need replacing. Would you like to book an appointment to have that checked out?
Dan Molloy (00:35:39):
Yeah, I think I better do that. Do you have
AI Agent – Jessica (00:35:41):
An
Dan Molloy (00:35:42):
Expert tomorrow?
AI Agent – Jessica (00:35:44):
Let me check for you, Dan. We’ve got availability tomorrow, May 21st. How does either 10:00 AM or 2:00 PM work for you?
Dan Molloy (00:35:51):
Oh, 20 PM would be great, Jessica.
AI Agent – Jessica (00:35:54):
Got it, Dan. So you’re all set for tomorrow, May 21st at 2:00 PM. Let me just gather a bit more info to get the store ready for your appointment. Sure. What’s the year of your Camry?
Dan Molloy (00:36:03):
It’s a 2018 Camry.
AI Agent – Jessica (00:36:06):
Thanks, Dan. So a 2018 Camry. Got it. How many miles are on it?
Dan Molloy (00:36:11):
About 180,000.
AI Agent – Jessica (00:36:15):
All right. 180,000 miles. Thanks for that. When was the last time you had it serviced?
Dan Molloy (00:36:20):
Well, within the past year.
AI Agent – Jessica (00:36:25):
Got it. Serviced within the past year. Lastly, can you share your cell phone number for the appointment schedule?
Dan Molloy (00:36:31):
Sure. 22222.
AI Agent – Jessica (00:36:39):
Thanks, Dan. Just to confirm, your number is 222. 222-222, correct?
Dan Molloy (00:36:45):
Yes, that’s correct.
AI Agent – Jessica (00:36:50):
Perfect, Dan. Would you prefer to receive text messages or phone calls for updates about your appointment and vehicle status? You can opt out anytime.
Dan Molloy (00:36:58):
Yeah, text messages would be fine.
AI Agent – Jessica (00:37:00):
Great. I’ll note that you prefer text messages for updates. Thanks for sharing all the details, Dan. I’ll pass this along to the store and they’ll confirm everything with you by text. Is there anything else I can help you with today?
Dan Molloy (00:37:13):
I’m just curious. Do you guys sell tires too?
AI Agent – Jessica (00:37:16):
Yes, we do, Dan. We specialize in tires and have an amazing tire program. We’ve got millions of dollars worth of tires in our warehouse and no one beats our tire offers. Plus, if you ever have a quality issue with a tire you buy from us, we’ll replace it. No questions asked. You’d only pay for mounting and balancing. If you’re ever in the market for tires, we’d be happy to help. Anything else I can assist you with?
Dan Molloy (00:37:38):
No, I’m good. Thank you, Jessica.
AI Agent – Jessica (00:37:42):
You’re welcome, Dan. I appreciate you calling Molloy. We’ll see you tomorrow, May 21st at 20 PM. Have a great day.
Dan Molloy (00:37:49):
Thank you, Jinsica. So that’s an example and now that exact call will show up, this is a demo obviously, but it will show up in the email of the … So practical. Again, my commitment was to make it practical. Missed opportunity. Here it is served right up so somebody can call back and we’re adding other things to the mix also depending on the client for texting and things like that back and forth to the customers. So we can text appointment links, calendar links, things like that right back to the customer. Pretty cool, huh?
Lauren Thunen (00:38:35):
Yeah, it’s awesome. I also love, as you’re watching this, I’m sure everyone here can tell this AI agent, there’s lots of AI agents on the market AI call agents that are going to be able to answer the phone for you, but not all of them are trained specifically on the automotive industry to answer the questions like they did, not give pricing over the phone. All of that I assume, Dan, too. You can customize responses, tailor it for your shop. Again, this is, again, one of the advantages of working with someone that specifically works just with automotive and tire shops versus if you just go buy an AI call agent off of the internet, you’re going to get a lot of things that you probably don’t want.
Dan Molloy (00:39:16):
Yeah. And the thing for me just as a businessman is I want to provide my clients with a platform. So Jessica is a part of a huge platform that we provide for our clients so that they can do other things down the road. So this is a perfect place to get started.
AI Agent – Jessica (00:39:40):
Another
Dan Molloy (00:39:41):
Great thing, and again, just from an educational standpoint, we also have developed practice bots so the sales team can practice their sales skills every day and we track all of that kind of stuff too. So anyway, another example of using AI practical purposes, I’ll show that. Why don’t you share something that you guys are doing and I’ll pull up something here too. Cool.
Lauren Thunen (00:40:14):
Sounds good. So again, one use in your store, I’m sure you guys know a lot of people call after hours. They get off work or shops close, call for an appointment. That’s a really great way to handle an inquiry after hours or if someone doesn’t pick up in a specific time in your shop. Some of the things that AutoVitals is doing on this front is writing customer facing communication. Now, again, some of you probably already know this if you’re using AutoVitals and you might already be using these tools in your shop, Melissa, I see a question from you on Otto Notes, so I’ll answer that in just a second. But again, most of you guys didn’t get into the automotive industry to write marketing copy or to write customer facing communication. I’m personally not a novelist. I don’t expect anyone else to be a novelist and a grammar expert, especially your technicians.
(00:41:04):
We don’t want them spending all of their time writing customer-facing communication. It’s not a good use of their time. It’s not what they’re best at. So one of the tools that AutoVitals recently introduced is called Otto Notes and I’m just going to blow this up real quick is if you’re on AutoVitals, Smartflow or above, now for the service advisor view, you should see a little icon at the top right corner for your customer notes. Now today, all a technician has to do is leave one or two words explaining the condition of the vehicle. So say we’re diagnosing the TPMS concern, TBMS lights on. Technician leaves the note lights on. AI in seconds is going to rewrite that note into a customer-facing note that explains what the
(00:41:49):
TPMS light is and why it’s important that you diagnose it. Same thing, air filter is dirty. It’s going to explain to the customer why it’s important that you have a clean air filter. It helps with engine fuel and performance. Especially these days, gas is very expensive. People are going to want to be approving those air filters more if they know exactly what it does and so on, so forth. So again, a practical way where AI text writing is embedded directly into your platform. You don’t need to go dump this text in some external model and you can rewrite right there. Again, fully under your control, your service advisors can review it, they can edit, they can revert it. All of that is available to you with inside the tool.
(00:42:30):
Melissa asks, “Can we as shops teach Otto Notes to sound more human?” That is something that we’re working on for the next iteration is so that you can have more controls about the tone of voice, how you want to tailor your responses. You can ask it to break it up into bullet points, et cetera. So that’s coming in our second version. So we’re working on that today, Melissa, so that’s a great question. But again, really the purpose here is for you inside the tool that you’re already using, be able to save your technician’s time because you’re not asking them to write detailed notes. You can save your service advisor’s time as well because then they’re not rewriting all of these notes and trying to figure out exactly what to put in this note. It’s trained on AutoVital’s educational proprietary information, how we word our educational videos.
(00:43:15):
It’s trained on all of these conditions, recommended actions. It’s not processing any of your shop identifying information. So it’s not sending that you’re from ABC Automotive. It’s not sending any customer or vehicle identifying information. It’s just taking into account all of the things that we’ve trained the AI model on, the condition, the topic, and the recommended action to produce that note, as well as anything that’s already in the open text field. I’ve seen folks that have gotten somewhat creative as they wait for the next version of this, Melissa, where they type in, “I want this note in all caps right here in the customer notes,” and the AI will generate that. So there’s lots of things you can play around with it as it sits today, but it is trained to be grammatically correct. And then relative, I mean, it’s a few sentences, relatively short, describe the issue and why it’s important to get it replaced is what it’s going to do with every note.
(00:44:12):
So that’s one built into AutoVitals. Again, you should have access to this already if you’re on smartflow or any package above. If you’re not sure what package you’re on, my contact information’s at the end of this webinar. I can get you sorted, see if you have access to it and if you don’t explain how to get access to it.
Dan Molloy (00:44:29):
I get something really exciting. This is great stuff. I love what you’re doing with the scripting there.
Lauren Thunen (00:44:38):
And then next, again, what we just talked about, probably didn’t get into business to be a marketing expert and you certainly, most of us, I’m not a text message marketing expert. It’s a very specific skill, how to craft text messages that folks open that are relevant and pertinent to them and also takes a lot of time. If you’re a shop that doesn’t have a dedicated marketing manager, you probably don’t have someone overseeing all of your text message blasts, et cetera. You might as the owner be doing it, you might be having your service manager do it, et cetera. So now in Automotive CRM, if you go to send a text message campaign, first you’ll select your audience, yada, yada, yada. We’re not going to go over that today. When you get to the text message screen to write your text message, before it was just write your text message text.
(00:45:28):
That’s kind of like, oh, I don’t know what to write. I don’t know what personalization tokens to put in. I’m not a grammar expert. What do I put here? So we now have what we’re calling Otto Campaigns where you can give it some instructions on what you want your tech message marketing campaign to be. So the goal
of this campaign is I’m going to remind customers to get their AC checks before summer. I’m going to generate that text message. And what it’s going to do is it’s automatically going to put in a personalization token. So hi, this stands for Motorist first name, customer first name. Summer’s coming. Have your AC checked soon at your shop name to stay cool and then it’s going to have your business phone number to schedule your appointment. Bam. In seconds, a personalized customizable text message campaign for your shop.
(00:46:17):
You can edit from there. So if you’re like, I just want to say call this number, bam, text saved. Let’s say you want to try something else. So let’s control the tone a little bit. We want to say, write a funny text message reminding customers to get their AC checked. So we didn’t like that. We want it to be a little more humorous. We’re going to play around with it a lot. Your AC’s been feeling a little lazy. Don’t leave it sweating through summer. Sorry, the video cut off right there at the end. Let me pause it. Don’t leave it sweating through summer. Schedule a checkup at shop name to keep cool. So Melissa, kind of back to what you were talking about, this already in Otto Campaigns for the text message, you have more control over the tone of voice, et cetera. I even was playing around with it the other day with a customer and I just literally put blah, blah, blah in Otto Campaigns because I didn’t know what I wanted it to write and it generated a beautiful service reminder because it was like, okay, Lauren’s being stupid, doesn’t have any ideas off the top of their head.
(00:47:14):
Let me just throw something at the wall here and see what sticks. Again, train specifically for the automotive industry, this again, not sharing any customer identifying information, it is sharing your shop name and phone number, any of those business details so you can get a customized text message response, but outside of that
Dan Molloy (00:47:34):
Yeah, practical. I love it, Lauren.
Lauren Thunen (00:47:36):
Again, so you don’t have to be a marketing expert anymore. We have it built into Otto Campaigns. For text messages, again, we are looking to in the future expand out this. Right now it’s just for text messages to the next frontier as you could probably logically deduce this email campaigns.
Dan Molloy (00:47:52):
That’s fabulous. I love it. I have something really exciting I want to share with the group.
Lauren Thunen (00:48:00):
Perfect. All right, let me stop sharing and so you can take it away.
Dan Molloy (00:48:06):
Yeah. So we shared with you the AI max sales agent, very practical use of telephone and AI agents. Now I’m going to show you another one. We call this our sales alert system and what it’s doing right now is finding missed opportunities in real time. That’s what you’re seeing here. Three minutes ago, this missed opportunity came into this company and it’s been assigned to individuals and they use it. So all they got to do to process the alert is open it up like this and it gives all the information about that missed opportunity and who the salesperson was and the store and the customer, all that customer information, but in real time so that … And I know this particular company gets around 12,000 phone calls a month. It’s a lot, a lot for medium-sized company. And every company that’s represented here in this webinar and everyone out there has missed opportunities every day.
(00:49:20):
So with the technology today, we can capture the missed opportunities that occur inbound, outbound, and during the day. And this one is a different type of missed opportunity. This is one where the service advisor and the customer didn’t get aligned and it fell through the cracks. And this is when I had the big company, like I said, this is what used to drive me insane. All these missed opportunities everywhere. Now we have the ability to manage them. And this is a game changer. You can close 25%, 30% of these missed opportunities again, think about it. They cost you a hundred. Well, actually I want to throw a caveat out there about the cost of the sales lead. Yes, the sales leads might cost $180 to generate when you take the total number of sales leads buy and figure out what the overhead is and all.
(00:50:18):
But if your closing percentage is only 50%, to generate the sale might be a $360 or $400 cost to generate to getting that customer in the door, that’s what’s so. So this type of application for me, I’ve been a 20-year quest of mine to develop this and we have it now. It’s live. I want to show one more thing over here.
(00:50:51):
I want to show this very, very, very, very good friend and client of mine. All this stuff also, we are now beginning to generate this data. This is language data. When you think about your business, you have your KPI data, everybody does. They’ve got KPIs, they’ve got financials, they’ve got more data. The point of sale system spits it out. You’ve got it. What you’re looking at here some of you for the first time is language KPIs because my philosophy and what I wrote about in my book titled The Language of Commitment is that all your KPIs are generated by language.
(00:51:39):
What you’re seeing here is some of the language, not all of them, but some of the language KPIs. We’re generating all this now by AI. So for instance, how frequently is the team saying, yes, I can help you with that. How frequently are they off making service declarations such as, Lauren, I’m thrilled that you called today for an oil change and I want you to know we’re a full service shop here. Not only do we do oil changes, we do brakes and tires, alignments, check engine lights, and we have payment plans for you as well. We also track payment plans. There’s a different screen. And then it all comes down to closing percentages.What’s the batting average on inbound calls? And I can tell you that this company right now is averaging around in the 70%. When they started, they were in the 50s. Remember I told you about the AI practice, the sales practice bots?
AI Agent – Jessica (00:52:43):
Yeah.
Dan Molloy (00:52:44):
Here’s where we keep track of it right here, practice metrics. They’re practicing every day. Their team is practicing every day. This is on a monthly basis. 165 times a month they practiced last month, 176 in March. They’re already up to 118 so far. They’re practicing and here’s what I always tell them. Well, you’re practicing and you’re going to class over here on this left side. The competition isn’t doing that. So these guys are busting at the seams. They just open their fourth store and they’ve got plans to open more and more and more. So it’s using the tools, the AI, they’re using all these tools. Using the tools, the AI tools right now to capture, to keep all the sales opportunities, you spend way hard earned money to make the phone ring and to have people contact you, let’s keep it. That’s my motto. Let’s keep it all.
Lauren Thunen (00:53:43):
Yeah, absolutely. And this is great, the data visualization. And like you said, there’s the top end indicators like how many new customers are you generating? What’s your average repair order? What’s your revenue? But the little things like what happens on the phone to schedule an appointment are the influential metrics that are driving that. So being able to analyze that among every single call is so powerful and something that before artificial intelligence, you would’ve had to go manually listen to each phone call and say, yes, they did it. No, they didn’t. No one has time for that. You’re trying to grow your business. You don’t have time to listen to every single phone call. So this is really helpful so you can identify who’s doing it best, who needs some work, what happened last month we were down. You can easily see where you need to take your business.
Dan Molloy (00:54:32):
Yeah. We have all the data for, like you said, down to the individual level. We have it all down to how effectively are people speaking about tires? How effectively are they speaking about? And this all ties back into what you’re doing and what we’re doing with you in terms of taking your DVI. You have the
DVI, you have all the data. How effectively is the team communicating about the data and the information in the DVI? Really mission critical also.
Lauren Thunen (00:55:03):
Right. So we’ve got a couple more minutes left. So I wanted to share one more thing that AutoVitals is doing on the AI side of things. Then we’ll get to the wrap up. There’s a couple questions, so we’ll save those for the end and any other questions you have, we’ll either spend a little extra time here or we’ll follow up with you over email. So last but certainly not least, I’m very excited. We’ve been talking about Otto scoring inspection scoring for, I think we’ve been talking about it for about a month or two now. It is officially in beta. It’ll be our first beta testers are getting access to it next week. If you’ve already indicated that you’re interested in beta testing it, we will be reaching out to you next week and it’s called inspection scoring. And again, what this is doing is as your technicians are completing your digital vehicle inspection, in real time your service advisors will be able to see a quality score of how effective and how high quality that inspection is along with action items to improve the score.
(00:56:03):
Again, this is in real time. So as your technicians go to complete the inspection and complete more topics, the score will go up. If they’re missing things, the score will go down in real time. What this enables is at a glance, technician completes the inspection, submits it to the service advisor. I can see without having to go through the entire inspection, how many topics were completed, how many issues were found, how many recommendations the technician made on the vehicle, how many photos they took and how many of those recommendations had a photo attached. Are they only taking pictures of what’s good or are they actually taking pictures of the meet, which is what needs to be repaired on the vehicle. It’ll give you an understanding of why they scored that score and then action items for your technician or service advisor to complete to increase the quality score.
(00:56:50):
Obviously this is based on benchmarking data. So we analyzed so many of our inspections and vehicle information we had and we broke vehicles into mileage buckets. So I think it’s like zero to 30,000, 30,000 to 60,000, 60,000 to something, 90,000, 90,000 to 120,000 and 120,000 plus. So it’ll put each vehicle in your shop into one of those mileage buckets and it’ll compare you to the benchmarks that we see. So for instance, a vehicle with over 200,000 miles, there needs to be more than five recommendations on that vehicle, especially if it hasn’t been in your shop recently, you need to be finding issues. If a technician comes back and only found one issue on a vehicle with 200,000 miles, you know something’s up. You can send that inspection back to the technician, talk to them about it. Maybe there’s a legitimate reason like this vehicle was in your shop a week ago and is just coming back to get one more thing done.
(00:57:47):
Absolutely. Of course there’s always going to be things that deviate from the standard, but it’s going to give you a standard quality score that you can compare and benchmark yourself to. Hey, Lauren? Yeah, go for it.
Dan Molloy (00:57:59):
I just got a question from Ray Carr. Great question, Ray. Can Jessica populate the data fields client and vehicle info and the point of sale system? So the answer is yes if we can get the linkage into your point of sale system. So certainly it’s something that can be done and there’s ways around that too. So I’d be happy to talk with you about that offline. Yeah.
Lauren Thunen (00:58:29):
Sweet. Awesome. So this is again, the next frontier. It’s in beta now. We will start to release it to our shops once we get through the beta testing, but really excited about this because it’s giving you not only the ability to look at your inspections retroactively and see where opportunities were missed, but see in real time while the car is still in the shop, what additional opportunities you can capture so that when you go to send that digital inspection report, it is a high quality report. This to start is going to be available on the service advisor screen. And then in future versions, we’re also going to include it live on the technician’s app so they can see in real time too what benchmarks they need to hit, how their progress so they’re getting real-time feedback on the vehicles that they’re inspecting. So very excited for inspection scoring that’s coming soon.
(00:59:20):
Melissa, I saw you asked, are all of these AI integrations available in Canada as well? For AutoVitals, yes, if you’re a shop in Canada, you still have access to all of these. It’s not just for our US space shops. Dan, I assume the same too, you guys operate in Canada?
Dan Molloy (00:59:36):
Yes.
Lauren Thunen (00:59:37):
Okay, perfect. Great
Dan Molloy (00:59:39):
Question. Yeah.
Lauren Thunen (00:59:40):
Roy, I see your comment about being included in the scoring beta testing. I will definitely get you in that. And Roy also asked, will this be a KPI in the BCP? Yes, we will be adding this so you can see by service advisor, by technician, what are the average quality scores going out? There’ll be integrated reporting into the business control panel. So again, And you can see it in real time and retroactively. Who
Dan Molloy (01:00:02):
Always on the button?
Lauren Thunen (01:00:05):
Yeah, we are on it. It is 11 o’clock. So in summary, how to implement artificial intelligence today, a lot of you have already done this. Today was a great if you haven’t, first step. And number one is educate yourself on what AI tools are available, what tools are best for your shop. And then also what tools does your software providers already have? So the teams that you’re already working with, how are they integrating artificial intelligence into your shop’s process? What other vendors specifically, again, we recommend in the automotive space are using artificial intelligence in deciding what’s best for you. From there, experiment, begin testing selected AI tools. Again, in controlled environments with human oversight. If you’re going to use external tools that are not in your current software stack, make sure that you’re using paid models that have data privacy protections. But again, the best way to learn how to do anything is just to try it.
(01:01:00):
So start to get familiar with it, educate your team on it. And then from there, once you have a good idea of what’s possible and where you want to go, set an implementation plan, share the plan and the tools with your team so they have access. And then last but certainly not least is in a month, in a quarter at the end of the year, review the results. Make sure that you’re using tools that are practical and that are improving your bottom line, helping you capture more missed opportunities, increasing your revenue. You don’t want to just be using them for fun. You really want to be comparing to benchmarks in your job.
Dan Molloy (01:01:30):
It’s got to be practical. Yeah. So anyway, Lauren, great job my friend. Thank you so much.
Lauren Thunen (01:01:37):
And last but certainly not least, if you want to keep in touch with either of us, Molloy Sales Development Group, that’s Dan. I will also include Dan’s contact information in the follow-up email that we are going to send and AutoVital’s contact information. That’s my direct line. You can call or text me. If you have more general inquiries, you can go to AutoVitals.com and get more information. Some of the questions that I see is Ray Cars. Looking forward to hearing from you, Dan. Ray, I’ll make sure to share your contact information with Dan. Melissa, I got you and beta. I will reach out to you specifically about this. Glen, ask if there’ll be a copy of this webinar available to be viewed again. Yes, if you’re in the webinar or if you registered for the webinar and you didn’t make it live or made it to part of it live, we will send a follow-up email with the webinar recording.
(01:02:26):
It’ll also be available on AutoVital’s YouTube channel for public viewing as well. Anything you wanted to add before we get out of here, Dan?
Dan Molloy (01:02:34):
No, I really just appreciate you working with me to put this together and it’s great. We have fun doing it and we’ll be doing it again soon and I know we have some other things we’ll be collaborating on. So this is great fun. Yeah,
Lauren Thunen (01:02:49):
Absolutely. Thank you. Appreciate
Dan Molloy (01:02:51):
It.
Lauren Thunen (01:02:52):
Thank you everyone for joining us. If you have any other questions, you can reply to that follow-up email that we send as well. So we’ll be in touch and have a great rest of your day.
Dan Molloy (01:03:02):
Yes. Thank you.
Lauren Thunen (01:03:03):
Thanks everyone. Take care.
Dan Molloy (01:03:05):
Bye-bye now.
Lauren Thunen (01:03:05):
Bye.