Name: What AI Actually Looks Like at a Car Wash
Uploaded: 2026-04-30T18:01:05.802Z
Duration: 30 min 2 s
Description: What AI Actually Looks Like at a Car Wash

Transcript for "What AI Actually Looks Like at a Car Wash": Alright. Hello, and welcome everyone to our live demo. Thank you so much for joining us today. We're really excited to have you here. We're going to be talking a lot about AI today, so let's start there. As you come in, feel free to drop your name, your wash, and whether you're already using AI in any part of your business in the chat. And we'd love to hear what you're already experimenting with. We'll be diving today into what AI actually looks like at a car wash. My name is Sarah Brough. I am the marketing director here at RINCE. I'm joined with Jessica Gilles, who is our product designer and has played an integral part in the development of Mo, our new Rince AI assistant, and which we'll be talking about a little bit later today. And then also Kyle who is VP here at Rents. Jess and Kyle, thanks for joining us. Thanks, Patrick. Now I've asked for having us, Daryl. yeah. Now I've asked everyone to drop in the chat, whether they're already using AI in their business or not. But I love to hear from you guys, what are some ways y'all have seen just, businesses use AI more generally? Kyle, Alright. I'm gonna start. why sorry. Yeah. I I think I think operators are across the board. I think, you know, we've really seen it over the last year. ChatGPT start? was this thing we started to hear about. Right? And then everybody. starts using it. And I think what's what's really growing is the automation I think people are using it for. So, when, when supplies run out, employees can easily, you know, scan a QR code and then AI is helping put that into a Google Sheet or or, you know, some document. Some advanced you know, more advanced users are using some of the AI app building tools to build their own apps for, you know, their own internal use. I think you see even more, you know, people going more advanced writing Python scripts and things, but I think that's kinda rare. But, I think you're seeing it more and more as kind of an everyday tool, at the car wash. Yeah. And you. said everyday, baby, which I agree. Jess, how about Yeah. Those are great examples. For me, it's? really been a game changer as a thought partner. So I kinda put an initial idea in there that's half baked, and I ask it questions, and it checks my assumptions. It gives me new ideas that I never would have thought of on my own. And then I kinda, like, pick out what resonates with me and guide it, and the end result is way stronger than what I had at the beginning. So just having that kind of thing to bounce ideas off of has really changed, how I work every day. Yeah. Agreed. I know for me, I I always see, like, touches of AI everywhere. I think, I don't know. I am a big Target shopper, and so I pull up the Target app all the time. And I'm noticing that the, suggestions are getting more and more finite as to, like, what I need, which is a little scary to me at some time. So then I'm like, oh, this is really useful. And I have been able to get things that I realized that I needed, but I guess Target kinda got me a couple times there. But it's helpful for sure in those cases just in shopping as well. Now, Kyle, you had brought this up, but, you know, we've had AI for a little bit, and it has been around for a while. Lots of people are using it. It's moving fast. And before we go any further, I kinda wanted to do a level set of what we're really seeing or talking about when we talk about what AI is, as there are a lot of different models, different use cases, different explanations. So today, we're going to really focus in on kinda three types of AI. The first is probably the one everyone is most familiar with, generative AI. These are tools that create things, like chat GBT, writing text, or tools that generate images and videos. If you ever typed a question into chat GBT or used AI to draft an email, you've used generative AI. It's the most visible form of AI right now. The second is unsupervised learning. This one is a little less visible, but it's still very powerful. This is AI that finds patterns on its own without being told what to look for. A really common use case is grouping customers into different segments or personas. So the AI looks at behavior and says, hey. These people are doing similar things, without anyone necessarily defining the groups ahead of time. It's discovering things you didn't even know to ask about. The third one is supervised learning, and that is, this is AI that makes kind of predictions based off of past examples. A really common example of this is, for example, email spam filters. Every time you've ever marked something as spam or not spam, you're actually training an AI. It's studied thousands of examples of what spam looks like, you know, certain words or senders, patterns, and now it makes that call on its own before an email either even hits your inbox. So that's supervised learning, and it was taught using past examples with known outcomes and now it predicts new ones. So now that we've kind of level set on what AI is, let's talk about how what it means for your wash. Today, our agenda is going to go over three practical ways to use AI in your business. The first is prediction. So this is where we lean right back into that kind of supervised learning model we just talked about, knowing what's coming before it happens, not reacting to your business, but getting ahead of it. And Kyle is going to walk us through this section and specifically how AI can help predict churn so you're not losing members before you even knew they were at risk. The second portion is automation or doing more than any human team could do manually. This is where AI becomes a real operational advantage, and we're going to show you this live. Jess is going to demo Moe, our new RINCE AI assistant, so you can see exactly what this looks like in action. And the third is personalization, making every member feel like your only customer. We're going to bring kinda everything together here and show how AI enables to deliver this personalized experience at scale that, just wasn't possible to do manually before. So as we go through these three areas, feel free to drop any questions you have into our chat, to the right of the screen if you're on desktop or below the video if you're on mobile. We'll answer all questions at the end of, the presentation. So let's go ahead and dive in. Kyle, let's talk a little bit about predictive behavior. There are a lot of ways AI can help provide guided direction to better run your wash. I know you've been spending a lot of time focusing on using AI to get ahead of membership churn. You'll be talking about this actually at the Car Wash Show. So what are some things you've been learning through that process? Yeah. I I think it's one of the strong areas for AI to be practical. AI is prediction. Right? So sometimes we forget when we're using it as that thought partner as I do too every single day. You you, like, you start to think this thing knows you. It's like, how do you know all of this? And, really, when you when you think back to how it's predicting, like, the next word to use, and then it's going back into this thread and it's saying, is there anything I need to change? And then it's looking at what it knows about you. Should I change? And it's it's predicting one thing at a time. Just like we type in all of these things about us and get these predictions, we have mountains and mountains of data in our our POS systems, in our CRM that AI could use to look at patterns and then predict. So I think one of the the big areas that we're just really excited about is this prediction churn model that we've created. It does not use one of the LLMs. It's not a traditional, hey, Claude, just go do this or or chat GPT. It's our own model trained on car wash data. And I think the big question for me as an operator when I think back to to all of the the problems of churn, there's this idea that we don't wanna wake the sleeping bear. Right? So it's like, alright. This person hasn't washed in a while, but I'm not gonna say anything because I might remind them that they have this membership. And then they're like, oh, yeah. I need to cancel that immediately. And I think that's prevalent across the industry. And, actually, there is a lot of data behind if you do poke everybody who's not using it, you are gonna see churn, you know, kind of go up because people will be reminded of it. However, the literature in retail and subscription businesses in general also see the power of selective messaging based on segmentation. So not as soon as somebody stops mess stops visiting for three weeks, we send them a message saying, hey. You're really wasting this membership thing you have. Like, that's not what we wanna do. We really wanna be very selective and be tailored to a particular set of behavior. So, for example, one of the things that we've learned in modeling this in the is that the amount of times you visited the car wash is not necessarily the thing we wanna go by because everybody has a certain set of trends. So for example, I'll use an extreme addition. Hey. We haven't seen this person in two months. Man, we need to message them. However, if you look at the data, they never wash in December, January, or February. Okay. These are snowbirds. They probably leave, you know, the the cold weather of of that location, and then they come back and then they wash once a month. So it's not just, uh-oh. We haven't seen them. We're afraid. We need to message them. It's understanding people's trends and changes in those trends. So maybe there's somebody who only washes once a month, but they love the convenience of the membership, and they're totally fine with that because they want it at their disposal. Just because they're washing one time a month, that's their trend. It's always been their trend. Maybe we have years of data. So we don't wanna necessarily disrupt them and say, hey. Something must be wrong here. I think the other thing is finding creative ways to message people without saying, hey. We haven't seen you in a while. Loss aversion is really not the behavioral, you know, kinda element bias here that we wanna lean into. We really wanna be reminding people of value as early as possible. So you wait too long and it's and it's too late. But as soon as we see changes in that behavior, we wanna maybe say, you know, some operators are doing, hey. We just wanted to give you a free wash for friends and family because you're a valued member, another perk of membership. It's not, hey, we've noticed this behavior. It's, hey, I just wanna give you another perk of membership. What we really are trying to do is remind people of the value in membership. So it's kind of a question of just different segments, and there might be dozens in in reality of of selective messaging, you know, that we're gonna use. So that's kinda how we're looking at, predictive churn, in in in the CRM app. Yeah. Thanks, Kyle. I think there is a lot of power to be in, like you said, transitioning that messaging to value based. In the CRM specifically, it makes it really simple to do. We'll go ahead and share just a short demo that highlights how easy it is to create an audience to be able to send those messages out. To use the churn prediction model, navigate to audiences and select new audience. Give your audience a name. In this case, we're focusing in on the high churn risk members. Now select the membership churn risk category. Select the category that you're wanting, and that's it. So, yeah, it is within just a couple of steps, that it can happen. Now one thing was in that video, it showed a top a banner at the top that said, hey. Do this with Moe. And that's where the automation aspect of this all kinda ties in. Now, Jess, you played a large role in building out of Moe. Can you tell us a little bit about what Moe is? Yeah. So you might hear AI assistant and think, okay. This is just like chat g p t. And the answer is yes in a sense that you can kinda talk to Moe naturally. You can ask it questions or tell her what you're trying to do. But the big difference is that Moe is built specifically for car wash operators inside RINZ. So it understands what you've done in the CRM, your members, your data. It has industry best practices built right in. So instead of just giving you generic advice like you might get from ChatGPT or Cloud, Moe's gonna help you take action like building a campaign or finding the right audience or analyzing trends, and it's really gonna help you figure out what to do next within RINZT. And it's also included in our subscription price. Awesome. I think we have a quick video, that you you've made, to kinda highlight some of those. We'll go ahead and share that now. So let's jump into a demo to see how it works. So in your CRM, you'll see this card at the top that says do more with Moe. If you click that, that opens your chat box. A few things I wanna point out here is we have these suggestion cards. So these are personalized to you, what we think you should be doing in RINZED. The first one here I wanna highlight teach me your brand voice. So at any time, you can update your brand voice here. You click brand guidelines, and we're automatically detecting this from your website, but you can update your brand description, your tone, your colors, and any additional guidelines you might have. This helps make sure that any images we generate or any copy we generate is gonna be on brand, for your car wash. So close out of that, and let's start asking Moe some questions. So let's just ask what should I focus on this week to increase my members? Awesome. So let's see. He says, good question, but increased members can mean a few different things. So Moe will always ask you clarifying questions to point you in the right direction, make sure he's on track, and you're getting what you need. So this is an example of that. So I want to convert more new customers into members. Okay. Awesome. So he suggested a few things that I can do. One, push harder on my online checkout, run a conversion campaign. That sounds pretty good. Capture more contacts in the first place. The fastest thing I can do for you right now is to build a non member conversion campaign. That sounds pretty good. Let's try that. So let's do the conversion. Awesome. So Bill already knows what I've done in rent. So he sees that I have a audience that's gonna work pretty well for this. And there's a few questions before he's keep setting it up. So let's just do SMS right now. Which checkout form do I want? Let's use my default monthly membership checkout. And, awesome, looks like mom has made a plan. So this is the audience he's gonna use. He's gonna name the checkout form default monthly members. He's drafted some copy for me for my, text message, some recommendations about character count. But all this looks pretty good for me. He can even organize it into, folders just to keep things tidy. But I'm gonna go ahead and create this campaign. And then awesome. My campaign is created. So in just a few questions and clicks, I was able to see that he created this campaign. If we click on it here, it's gonna take me right there. So you can see this is the campaign he made, has made with Moe. This is all the copy and the settings that we set. It's currently inactive. So Moe will never activate anything for you or send things that you might not expect. You'll always have to go in and activate it. So you're very in control of what Moe does. And then I can always send a a test, a text message to make sure it all went well. So that's an example of how Moe can recommend something for you and take it all the way through to creation. Alright. So I love that example, Jesse, you provided about how it was a question that you asked and then a campaign built within just a a couple minutes. Are there any other what are some additional features of of Moe? Yeah. So we have a long list of things that Moe can do. He can create audiences, schedule campaigns like we just saw, things around your checkout forms you can update or create, set up your downsell plans, and even generate images for that downsell plan, NPS campaigns, contact lists. We have a whole laundry list of things. And then we are also for the car wash show, we'll be launching analytics. So you'll be able to ask Moe questions about your data, see how your car wash is doing, ask about member churn, just in plain language instead of having to go hunt in, our dashboards. And then at any time, you could just ask Moe. Hey, Moe. What can you do? And he'll give you a list of all of his capabilities to kinda give you inspiration, And you can ask also ask him what you should be doing. So that can be a really powerful tool as he's looking at, you know, everything that you have done in CRM, what you haven't done in CRM, what other people are doing. We have strong benchmarking tools. So that can be a really helpful thing for you to just ask Moe to learn. Yeah. Definitely. Let's go in. I know you also provided an example of how that, MO Analytics will work, so let's, share that now. Sorry. It will not go for you. One second. Alright. So next, I wanna give you a sneak peek about what is coming next. So this isn't live yet, but it's where we're headed. And I think it's gonna change how operators like yourselves make decisions about your car washes. So imagine typing a question into Moe about your car wash, and he looks at the data, tells you what's happening, and suggests that you how you can improve. So let's give it a try. Let's ask him. Tell me my conversion rate by location. So you can see that, Moe went into your data, found all of your locations, found your membership sales, your conversion rate, highlighted that Christopher is our top performing, location and the industry and what the industry averages. So now you have a benchmark against what's happening in the industry. And they identified a gap and, a quick gap that's worth exploring. So let's say, what can I do on rinse to increase my conversion? Great. So now Moe has given me a bunch of examples. I could update my checkout forms. I could do some campaign messages. I could update my contact forms and have text to join keywords, scheduled messages. I could update my downsell plans. And straight from here, Moe could start working on any of this for you. So now we've gone from asking in in plain text my question, about my data, getting the response, and knowing how to take action to improve that data. Awesome. So that gives a little taste of Moe Analytics, which will be is in beta right now. Correct, Jess? Yes. We're starting beta. So if you're interested in being a beta tester, feel free to reach out to us, but it will be live by the car wash show. Yep. Exactly. Now moving on to that third element. So we've talked about prediction, automation, and the last one is personalization, which kinda brings these elements altogether. Kyle, I wanna start with you. You have a lot of experience within the car wash industry, and within marketing and outreach specifically. Why does personalization matter so much for retention? Yeah. I think, look, at at at its core, it's a psychological thing. It's like we all like to feel that we are unique and you're seeing me as an individual and not as, you know, some generic group of people that are all passing by this big billboard. So we we love it. It's just hard to do. So we think of personalization maybe initially as, like, insert first name. Right? So instead of it just saying a general message, it says, Kyle, save money today with with this promo. But personalization really goes far beyond that, and I think that's where AI and data is really going to continue to help us unlock it. I might be you know, you might be able to break your users or your subscribers, your your customers in retail, into 50 different segments, all of which respond differently to different types of offers, different types of frequencies, cadences, styles. I think even today, we can start to build out that with many of the segmentation tools that we already have, in RINCE. But personalization is getting more and more sophisticated into these nuances. Remember, we talked about, like, prediction, and, really, this is, like, kind of part of that as well in that it can look at the patterns into all of this audience data, and it could predict, hey. If you segment it into this group, this is where we should message, you know, this type of of thing. So I think personalization, yes, we wanna insert name. We wanna be collecting as much contact data as we can. That's just table stakes, you know, incentivizing to collect first name, last name, that type of thing. But it really goes beyond that into personalizing what message and really predicting what message is going to have the highest impact into that LTV for that particular customer. Yeah. I'm glad that you made that distinction, Kyle, that it's really going beyond just saying, like, hi, first name, and providing not just, like, the personal communication, but really the targeted message that makes most sense for that person at that time based off of their behavior. So and Moe really does that or helps do that with it, for us at scale. Just you wanna talk a little bit about, like, how you can actually deliver that at scale with Moe? Yeah. Exactly. So, what you're saying about scale is really the main point here. So before Moe, this would feel like a very daunting task where you have to go into all of your campaigns, create a bunch of stuff, come up with your copy, have your idea, and that's probably not something you have time to do, and you're not really interested in doing and rinse. But with Moe, you can just describe what Kyle said, and Moe can pick out the steps that you'll need to take. You'll be able to draft the copy, know exactly what segments or audiences you'll need to create, and he'll just be able to do it right there for you. And you can check everything as you're going. But this becomes a task you can do, you know, in twenty, thirty minutes versus probably a week worth of effort trying to come up with all of this. So really being able to do all this personalization at scale is the key here, which is where it becomes most impactful. Yeah. I I just wanna give a shout out. Jess has done a phenomenal job designing this tool. I think it's it really is a game changer because you could do this in chat g p t. Right? You could say, hey. I'm a car wash. I have this many contacts. How should I be segmenting this? But now you could do the same thing with Moe. The difference is at the end, Moe will just say, do you want me to go ahead and do it? And instead of going through all those screens to now do it, it it's all automated. So I think it's a it the workflow itself, we're trying to reduce the the decision fatigue that the average operator has to go through. Like, it's Monday morning. What should I be working on? And I think the tool, that Jess and team have built out is just a a really powerful way, to kinda reduce that decision fatigue and just make it much, much easier. Yeah. Agreed. And I don't know. As a marketer myself, this makes me so excited to be able to have tools like this, and to be able to know, like, I can create all the different segments and audiences and nurture campaigns that I've always imagined to be able to build out, like, so much easier. Because it really is, like, Kyle, what you're saying, taking that next step and just having it all in one place so that you can just be like, okay. Build it out, and it's done. So it makes it really easy, to be able to execute at that level. Now that we've kind of talked through all of these different aspects of prediction and automation and personalization, let's get into any questions that may have come up. It doesn't look like there have been a ton of questions. Anne, I know that you talked about the RINCE quarterly benchmark data, within the chat, and it I would it is brought into Moe, and Moe does use that as parts of the data that it's pulling from. And that is a big distinction, like Kyle and Jess had said before about what makes it different than just a regular, like, chat. GBT chat, is we're bringing in that industry knowledge, that industry information so that these are educated and best practices. I don't know, Jess, if you have anything more to say on that. No? That was good. Great. And I know, Mike, you asked about would you be able to see your top salespeople as well. These, reports are within top salespeople is within sales path, and those are brought in there for reporting. I don't know. Just do you have more insights into into that? Or, Kyle, maybe you wanna step in for for that one? Yeah. What do you think, Jess? I defer. Yeah. I would say Moe is Moe is not directly, hooked into Sales Path at this time. It's something that we're looking into. And if we're, you know, hearing from you all that you want to chat with your Sales Path data, that's definitely something we'll look into. So keep that feedback coming. So, yeah, that's my answer. Yeah. I think I think we. would love to hear the use cases you have in mind and and where it would be helpful. So, you know, looking at your leaderboard of your top salespeople, you can, you know, bring it up pretty easily today. But what do you wanna do after that? Where do you wanna go with that data? How how can we be helpful? Yeah. And I really appreciate the feedback in the chat saying, hey. This would be helpful to be able to talk with our sales path data. We'll bring that back, to our team for sure. So appreciate that. Richie asked us if Moe is able to interact with support agent. Yes. So Moe can update your knowledge base. It can create, different, support agents. It can edit them. It can delete them. It can also review support, agent AI feedback and apply any suggestions. So it can do a lot of stuff within support agent around configuration, and then once we launch the data analyst product, reading from that. Awesome. Yeah. Thanks, Richie, for that question. And I'm glad that we could highlight that it's it expands into the support agent, for sure. Just looking at the other questions here, individual churn rate for salespeople oh, thanks, Joe, about the suggestion on individual churn rate for salespeople as well and comparing to industry standards. That is something that we mentioned before that we do bring into Moen as we think about how to expand it to other products. We'll bring that in as well. So if there are any it doesn't look like there are any other questions. So we'll go ahead and move forward with wrapping up. But we just wanna say thank you all so much for joining today. We really appreciate you being here. I we also will just mention that we will be at the car wash show. So if you are headed to the car wash show, come find us. We'll be at Booth Number 822, and we'll be demoing live along with several other new features, including our sales path driveway checkouts and AI based coaching and a bunch of other new features that we'd love to show you. If you aren't able to make it to the Car Wash Show but would select to get a demo, feel free to hit that get demo button at the top of the screen, and we'll reach out to you directly. Also, a call out to Kyle as he'll be giving two talks at the Car Wash Show. One will be diving deeper into the prediction churn model that he mentioned at the beginning of of this session, and that's on Monday at, May 11 at 11:30. And then the second one will go for those Sales Path users. It will go more into the power of coaching, And that will be on Tuesday at eleven at 10AM, sorry, at the Solutions Theater. So both will be definitely worth your time. We appreciate you all, and we hope we'll see you in Nashville. Thanks.