Qore Conversations
Tune in for engaging conversations about the latest technology, innovations, and trending issues in the automotive industry. QoreAi's podcast delivers expert insights, practical tips and problem-solving solutions. Stay informed and inspired with every episode.
Qore Conversations
Revolutionizing Automotive Retail With Identity Verification and Data
Unlock the secrets to safeguarding your dealership and enhancing your sales strategy with the latest episode of Qore Conversations. Join us as we sit down with Todd Smith, Founder and CEO of QoreAI, and Brian Epro, Alliance Manager at Equifax, to explore the cutting-edge innovations in identity verification and data analytics. With automotive fraud soaring towards an alarming $8 billion, discover how QoreAI's pioneering dealership operating system, bolstered by Equifax's data expertise, is setting new standards in security and personalization.
Imagine leveraging the power of advanced data analytics and AI to not only prioritize leads but to genuinely understand your customers' buying journeys. Todd and Brian share their insights on how you can gain a competitive edge by analyzing consumer behavior and using economic cohorts to predict customer preferences. This episode is packed with actionable strategies for optimizing your marketing efforts, reducing costs, and creating unforgettable customer experiences tailored to individual needs.
In a rapidly evolving industry, staying ahead means embracing a data-driven approach. Learn practical advice for integrating real-time data into your operations, from optimizing inventory management to personalizing vehicle recommendations. Todd and Brian also tackle the challenges dealerships face in this transition, offering tips to streamline processes and customize tech solutions to fit unique business requirements. Tune in for an enlightening discussion on the future of automotive sales and the indispensable role of data in driving success.
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Welcome to Core Conversations, where we discuss innovation and technology advancements and how they're shaping the automotive industry. In this episode, we're going to be discussing identity verification and data in the automotive retail environment, and joining the conversation, almost as always, todd Smith, founder and CEO at Core AI, and Brian Eppro, alliance Manager at Equifax. Nice to see you, guys. How are you Doing great, doing awesome, awesome, awesome, todd, hey, I, just I want to get into these questions. I know the audience is loving this content, so before we do that, though, I'd like to get a little brief overview, just, you know, a little bit of a brief overview on Core AI and maybe throw over to Brian, to a little bit of Equifax, just to set the standard for our audience.
Speaker 2:Yeah, absolutely. I appreciate that. So, core, our premise was really to build the dealership's first OS. We think there's so much disconnected technology inside the dealership and we thought it was a good time to kind of start fresh with our plan, and our immediate focus has been around identity verification, credit documents, but that's also really helped us understand a deeper level of data, a deeper level of communication and, ultimately, how to build a platform that will play nice with others in the marketplace. So they're kind of our core principles and, yeah, we're excited as a startup. You know you always have challenges, but we've been having a blast building it out.
Speaker 1:Nice, Brian. Tell us a little bit about Equifax and your role over there.
Speaker 3:Got it. Well, you may have heard of this little company called Equifax that I work for, right, so you know the big misconception out there is that Equifax is a credit bureau and that's it right, and that was even my misconception. I've been here about four years now. I'm on the automotive partnership team, so I work with different vendors and providers to dealers in the industry. The biggest surprise for me when I finally agreed to come on board is that it's a lot more than just credit and what I would say is that kind of the company's North Star is personalization. So it's using credit data for personalization. It's using identity data for personalization. It's using traditional marketing data that you're used to considering as an auto deal for personalization. But we take that data to the next level where we actually layer in some directly measured income and economic measures inside of those marketing measures and make those very easy for companies like as a, for instance, core AI to make available for their dealers to use.
Speaker 1:I love it. I especially love it when we're using more of this data in a useful manner for dealers, versus just confusing them with it.
Speaker 1:There's been so much of that over the last probably 15 years. So it gets me excited to hear you guys talk about these things, because it seems to bring a lot more clarity to the puzzle pieces as they begin to show image a lot more clearly. So well, hey, I want to jump in first and this is probably for you, todd but maybe provide a little explanation on how Cora AI's identity verification process works and maybe even an additional why it's so crucial for today's environment.
Speaker 2:Yeah. So look, we really started with identity first, for two specific reasons. The first reason is just the rise of fraud in the industry. This year, somewhere right about $7.98 billion of fraud will hit automotive. Now that's up and down a whole stack of income misrepresentation, identity fraud, lender fraud, straw purchases. You have a whole host of activities that are driving fraud inside the industry. But if we break down specifically to identity fraud as well as synthetic fraud, that's about 2.3 billion of that. So we really felt that was an important issue to solve and you break that down. Think about that as like 5% of automotive transactions are fraudulent or so this year. I mean it's mind blowing to think that.
Speaker 2:So we wanted to solve it. We knew we couldn't just solve it with driver's license, because even our government's moving away from a driver's license only world You've seen. If you've flown in the last I don't know six months, you'll see this thing called Real ID. If you've flown in the last I don't know six months, you'll see this thing called Real ID. The government's moving towards all government facilities, irs, everything, social Security, all, as well as TSA, moving to this Real ID. Real ID is like we don't believe in your driver's license alone anymore. So we need another way to ID you. We need another way to ID you.
Speaker 2:So, and looking at auto auto's kind of stuck in a position of neutral where they're just doing driver's license scanning at most when we realized, okay, that would not be enough. So we looked around and we first started with looking at the browser that the customer is accessing on. If they're remote If they're at the dealership, you don't have that. But if they're remote, we were able to start IDing the browser to know are they coming from a fraudulent IP? Are they saying in a conversation they're in Ohio, yet it's resolving to China, eastern Europe, africa, somewhere else? So our first part was to fingerprint the browser.
Speaker 2:And then this is why Equifax came into play we found an opportunity to partner to do device verification. So we said the phone in the customer's hands is probably one of the most accurate ways to ID somebody and you can quickly determine hey, that's a burner phone, recently activated SIM card in their phone. There's so much data and intelligence around the phone because we use these devices all day. So, with our partnership with Equifax, we hit through Equifax the carriers. Carriers returned to us customers full name, legal name, address, verified the phone number. Obviously, at that point we let the customer update the email address only because we found many people have multiple email addresses and knowing that we've returned the right email address out of, I think average consumer in America has four, it's probably pretty hard. So we just let the customer put that in.
Speaker 2:Then we do driver's license and then we do what we consider the basics of our industry synthetic ID as well as red flag and OFAC, and we run some additional government agency data in the back to also match it against the driver's license's address and the address returned through Equifax. So we're doing kind of a very multi-point process of verification and our number one goal is stop fraud right up front. But stopping fraud then also led us, I think, in a vision that was like wow, once I ID a customer to that level, we can unlock a huge amount of additional data. And that's probably one of the most exciting things right now for Core was the ability to look past. Okay, I've ID'd them. What else can I learn about them? Are they going to buy? What are they going to buy? What can they afford? There's so much valuable data that's out there that we can leverage to help dealers kind of push their business to the next level.
Speaker 1:Yeah, I think it makes a lot of sense. The partnership, obviously, with Equifax. I remember it's probably three or four years ago an Equifax report where it was. I think at that time it's like they were reporting 30% might have been more than that consumers that misreport or leave out really critical financial details during their loan processing, and there's a lot of fascinating points of data like that. That with what you're doing is, I think, critically important for dealers and the billions that rack up every single year. What dealer wouldn't want to be getting some of those costs and profitability efficiencies back while also improving in this particular area? I think it's a. It's a. There's a lot of win, wins here. But before I move on from that, brian, I did want to also get any thoughts from you regarding the partnership between Equifax and Core AI. Just see if you have any thoughts on that.
Speaker 3:Yeah, I have a lot of thoughts on that. I mean, they're all good, don't worry. Don't worry, I figured you. So what I get a kick out of is, when I got to Equifax, we had a capability where we could go into the phone. Basically, you know, consumer consent to go in the phone and grab their contact information and put that into the dealer's database. Right, and that was always thought of at Equifax as a fraud product, and it is still sold as a fraud product, right To Todd's point.
Speaker 3:There's this awesome side effect of it, though, which is that, as a result of doing it this way, you're getting very clean, correct data being put into your database in the first place, and the biggest problem a lot of dealers have when they're trying to enhance their data sets and to append data to them is that the data itself is dirty, and you can't fix dirty data right.
Speaker 3:You can't append good data to bad data. It just simply doesn't work. So, as a, for instance, our data sets require a name and an address for the types of data that Todd is using, that Core AI is using, right. If you don't have the name and address, you can't have the data. We're not going to key off of a phone number or an email because they're too amorphous, they change, they come and they go. People have multiples, so you have to be able to prove the person is that person. So, long story short, by having this process Todd's put in place for dealers is right up front, rather than having to deal with dirty data down the line. He's getting crystal clean data right at the beginning. And that is the core no pun intended of what the benefit is that he's bringing to the table so it's authenticated and it's correct in the first place.
Speaker 1:Nicely done, Brian. I use the word core.
Speaker 2:It's core on core. It's funny. I told my wife this. I was like it's like. Once we did this identity thing, I was like like percy spencer. You know, percy spencer is no answer.
Speaker 2:Come on, let's go guys so percy spencer was the guy working on microwaves and he had a candy bar in his shirt and he got too close to it and it melted it and he's the guy who basically invented the microwave. And I found like wow, like this side effect of as Brian so put well that we're IDing a customer with really good data upfront to push into the CRM or any other system for the dealer. It unlocked this whole other magical side of the business of what we are now able to do, and then it just magnifies when you start running these models using actual AI I'll use the word I hope in the correct way today to be able to deliver something beyond decision tree or trying to just create the most basic models that almost every system in the past is continuing to use that I believe you call the deterministic scoring system from like one to a thousand.
Speaker 1:Would you be willing to elaborate a little bit on what that means, how that's calculated?
Speaker 2:I think the audience would be really interested in hearing a little more on that. Yes, I think, through time, what is the dream of every dealer? Right, you want to be able to look into your existing customers. You want to be able to look into your inbound. You want to be able to look into your inbound leads. You want to look into your old leads that you spent $15 or $20 for, three, four, five years ago and now they're just toast. You're not doing anything. Maybe you're just sending a lobbying I call it the email bomb to them once a month that they're ignoring, a month that they're ignoring.
Speaker 2:But if you could look back into time and look even at the new inbounds and know which ones are in market, how valuable is that? And I think, with our partnership with Equifax, they have thousands of attributes and understanding those attributes enables us to start looking and determining. Is this customer truly in market? Are they looking to buy now? Are they still kind of mid or maybe they're upper funnel? Because I think by even understanding that at the most basic level, it changes your approach to that consumer. Most basic level, it changes your approach to that consumer, the consumer who's at the last, at the five yard line, it's do I have the right car and why buy from me? Right? But if they're high funnel, that consumer may be hey, let me just help you find the right car. So I'm going to ask you a whole different set of needs analysis questions and if you're a mid funnel, it may be a combination of hey, choose us, here's our Google reviews, here's stuff about us, here's why you should do business with us and here's all the benefits of us organizationally and inventory. That matches, most likely, what you're going to buy, right?
Speaker 2:So I think for us, it was learning to use data, and I think this will be a continuous journey. I don't think it's a stopping start. I think it's. We're going to use all this attributing data to continually try to understand the consumer's journey and to highlight it back to the dealer to say, hey, these people in your existing database whatever these 500 to 1500 people this quarter are right now. They're showing all the signals that they're going to buy a car, and those signals are not the same. One house you know has a new baby. They're going to need a new car. Someone bought a new house. Someone else crashed their car. Someone else's lease is about to be done. We have a multitude of potential scenarios, but when you start connecting them all together, it gives you a really deep understanding of consumer behavior and I think for us it's unlocking that finally for dealers and helping a dealer now see his data in a new light that he just didn't have before.
Speaker 1:It seems like that would be a really effective system for sales managers and salespeople when they're wanting to find some better way of prioritizing customers as well.
Speaker 2:Yeah, and look, I think lead prioritization has been around a long time. I think the signaling was more basic at the time. I think that it was probably more probabilistic. So you would build like a model and then you would hope that the customer aligned to the model. Now we're moving towards more deterministic data Sorry, I can get that out of my mouth on Friday where you know now, predictably, the consumer is going to do this right, because once you track so many scenarios over a course of time, you find those behavioral patterns, and AI is the best at pattern matching.
Speaker 2:It literally thrives in that environment. So for us, this piece is only going to get better, more accurate, and it's going to help us close the gap of oh, customers in market, we're in market. Oh, they're in this part of the market. So this is what you do here to get them to the next step. And I think this is the power of AI being able to deliver this.
Speaker 2:Well, what I consider the linear customer journey, can't you know when you're like day one, do this, day seven, send that. Day 12, text, day 14, call, and that only doesn't work. This is why every CRM or map system, marketing automation, they have thousands of uncompleted task operations, because the salespeople are like I talked to Brian a week ago he's not buying until next month. Or Sean, he's waiting to get his tax return. Yet this thing has 15 different follow-ups to Sean between now and when tax return season is possible. So I think we're just to me, we're just entering such an exciting time to be able to use data in new ways that will have, I believe, an absolute, profound effect on dealer operations.
Speaker 3:Can I jump in on one thing, please do? I always like to break this down to as simple a level as possible, right? So when we talk about lead prioritization, what we don't want to hear is and we never want to give somebody the impression of is that we're saying, hey, work these leads, don't work these leads, right. It's saying that if you use lead prioritization the right way, you have 10 leads in front of you. You know the three to call right now. You know the four that are going to need a different kind of customer journey path that Todd is talking about, where AI can can figure out that pattern and automatically do that once it has enough data. So it's not. Sometimes you get people get nervous when you say the lead prioritization, which is I'm going to go after this lead and then my salespeople are going to touch these other seven people. That's absolutely not what you want to do. You want to match your engagement to where they are in their buying journey. That's what prioritization allows you to do.
Speaker 3:Yeah to me it's like they are in their buying journey.
Speaker 2:That's what prioritization allows you to do. Yeah, to me it's like velocity, right, like if you get a hundred leads in today, you're going to attack them all at the same vigor. Right, tomorrow you get 100 leads. Well, what about the leads from yesterday? You can't attack 200 leads with the same vigor and get through all of them. And then, day three, now you have 300 leads that are all really new. How do you contact at that level? You have to triage, you have to prioritize and and you have to build systems that still contact all 300, but with the right personalized messaging. And I think this is what's going to be unlocked, versus the one size fits all coming out of a CRM or equity management tool or marketing automation platform. I think we're just going to see a much more precise, personalized world, because that's why AI and the ability to leverage data in new ways is possible, where before you just couldn't do that.
Speaker 1:Yeah, I think this takes us into where we probably all wanted to go 10 or more years ago in terms of how we leverage data. And I'm not a fan of the word disruption, it's so. There's a lot of words I don't like that's one. I just it's just silly, it's nonsense. But I do like recalibrate or calibrate, and I think that a lot of what you guys are sharing is evidence of where we're going, where there's this recalibration, and I think it's really important because I mean, we're talking about leveraging data and more of it than we've ever been able to even understand up to this point.
Speaker 1:Whether it's McKinsey or NADA or multiple sources all report that a vast majority of dealers collect data, but a very small minority of them effectively use it, and that's not a dig against dealers. They need help. They've literally been buried in layers of technology lasagna for a couple of decades now, and now we're finally getting to a point where there's this new. It's a breakthrough, it's a recalibration, with taking some of what we've had and some of what we now have as new capabilities to go to this place. So it's really exciting. If people don't tune into this to listen to my perspective, I want to ask you guys around that leveraging data point, once a customer's identity is verified, you gain access to all this additional data. Would love to know either or both of your thoughts on how this additional, basically more about that type of information that you can access. I think dealers would be interested in some of that.
Speaker 3:Brian, go ahead so yeah, in the context of core AI and what they're enabling for dealers. Now, listen, there's a bunch of different types of data that you're able to access, right. First of all, just confirmation of who you are. Are you actually who you say you are? That's the key, most important piece right there, right? Is the information you gave me correct, yes or no? Yes, Cool, Okay.
Speaker 3:So now the next question I'm going to ask myself or I'm going to if I'm face-to-face with you what are you? Are you in market? What are you in market for? We have data that we literally have a model that looks at the previous 90 days of vehicle sales, sees what the attributes are of the people who bought those vehicles Cause we can see the sales right and then applies about over a thousand attributes to the people for the next 90 days, and those people who match that get a higher score. That's part of the propensity score we were just talking about.
Speaker 3:So let's say you're, if you're, a nine90, boy, go talk to this person in person, shake his hand and put him in a car because he's about to buy a car, right? But then the next question becomes what are you here to look at and what should we actually try to sell you, right. So you're kicking tires on one thing, but I have some insight now into what you're actually able to afford, what your household is actually able to afford, and I'm able to guide you now. So I'm not going to walk up to you and say, yeah, you can or can't afford that. But what I can do is walk up to you and say, yeah, we'll take a look at this Tahoe. I'm going to show you a couple of different trim levels of it, because I know the payment you're going to want to land on is probably a little bit less than where this one is going to land. So I'm able to have a much more intelligent one-on-one conversation with you as a result of the data that Core AI is providing.
Speaker 3:But what gets really interesting is as you use this longer term. What Core will enable is that the dealer's database it'll almost become predictive, and what I mean by that is this guy, Sean Raines, shows up and he submits a lead and Core bumps against what we call an economic cohort and says, oh, Sean's a J38. J38s right now, for this dealership are frequently buying an F-150, right, so we're going to. You know he's looking at an EV right now, but we're also going to make sure he sees a couple F-150s, because these guys are three times more likely to end up in a pickup truck than they are in a Mach-E is the idea.
Speaker 2:Yeah, and I think if you really build on that in the thinking that every dealership is unique and every dealership is a microcosm, and though you have big data surrounding all of this, every dealership's individual consumer interactions and data tells its story. And we've come from an industry where CRM is one size fits all Every dealership has the same basic CRM and every dealership kind of uses the same follow-up tools and cadence schedules, et cetera. Right, I call it like if we surveyed 500 stores, their follow-ups might be slightly different, but even what they're sending is almost virtually the same. I call it like everyone's copied each other and everyone now looks vanilla and the same. With this data, every dealership actually builds their own personalized kind of cohort ecosystem and marketing plan that grows with them. And I think this is this like what I consider divergence off of where tech is today into this new level of technology that dealers can leverage to what I call a system of intelligence that is working with that individual dealership on its individualness and its customers, which are also unique to that store, and its customers, which are also unique to that store, and all the data is being worked inside that. Now, yes, you're going to have still big data as an umbrella overflow. All of this, but to me, each individual store and they could be next to each other, but the Ford store operates far different than the Nissan store. The data shows it. So I think we're just and this is now because of technology where we're in, with cloud or in serverless technology and AI and just machine learning, we're able to now do things that just no one had the processing power to do things like this before and that to me, gosh, it's worth waking up every day because I get excited because this changes our business.
Speaker 2:Because if you look at us on a graph, the cost to sell a car in the US has just gone up to the right, and average dealer says it's like $200. Nada says it's like $750, right. Average dealer says it's like 200. Nada says it's like 750, right. Because I think dealers maybe don't even account for all the costs that are wrapped into selling that particular vehicle and I don't know how NADA gets to theirs.
Speaker 2:But when I look at that, systems like we're talking about right now the system intelligence will drive cost out of that operational, absolutely, because it'll allow you to high-speed target the right ones faster and it allows you to keep the ones that are on the fence in the process and it allows you to slow, roach the ones that are man. They're still really high up tire kicking. So it allows you to optimize time, like your people's time, your spend in marketing channels, whether social channels, whether direct mail, whether, like whatever. It's OCTT, like TV, because cable's dead right, everybody said cable's dead. Now it's all these direct source TV shows, right. So I think we're just we're at a really interesting inflection point and you know again, a lot can be done now where even I would say 18 months, 24 months, you couldn't do some of this I like what I like about what you're doing with core and just overall.
Speaker 3:right, like you know, it's such a cliche, but and I hate when I use this as an example but Amazon, right, amazon is the company that if a average dealer could just do 5% of what you see on an Amazon page and process wise, they would be light years ahead of where they are. And you know what you're taught. What you're just saying is Jeff Bezos. When he first started up, he said listen, if we have 450,000 customers, we want to have 450,000 stores, and that's exactly what the situation should be at the dealership. My buying journey is different from Todd's, so treat me differently, engage with me differently, show me different things, and that's what. Now, something like Core AI has the processing power to ingest massive amounts of data and make usable. That's the difference. Yeah, it's the difference.
Speaker 1:Yeah, and as you guys have mentioned, affordability is a bigger factor today than it has been in years. You know the average cost of a car and the average cost of a home, like across the spectrum, all the major industries, everything's jacked through the. You know the atmosphere and when you think about leveraging data around affordability. But also, brian, you had mentioned, there are so many data points that also indicate well categorically you can even back people into hey, the majority of people within all of these points of data also end up buying one of these or these. Being able to capture affordability information and helping steer the customer is massively valuable, now more so than probably ever in the industry. And as we're kind of on this topic of data relative to affordability, curious just maybe top level thoughts from either of you is why is that understanding a customer's affordability so important in the car buying process?
Speaker 3:Man. This was the light bulb moment when I joined Equifax so I'm taking Todd's thunder for a second and when they showed me the marketing data set, this IXI data set. Right, when you think about all the data, I've got 25 years of industry experience working with data. Okay, behavioral data, product data really cutting edge stuff. What you always see is that a lot of the data that's out there is awful, right, it's directional and it's just not correct, right? You know, if I get your demographics wrong and there's risk associated with bad data, right, so there's low risk on demographics. You know I'm marketing a car to you that's for older people, but you're not gonna hate my guts for doing that, right? Maybe I'll just move on. Or maybe I'll look at it. Right, get your psychographics wrong. I have the wrong sports team on the ad. You know, maybe I'll move on, but I'm still not going to. You start getting into behavioral data and the risk gets high where, if Todd is acting like he's going to buy a car and you don't know about it and you don't respond to that, you can't sell him a car.
Speaker 3:But the last level of data that is the key and most important is affordability, and the reason why is? I can get every single thing right. I can walk you into the manager, the finance manager's office. We're going to sign, and you realize I can't afford this car. The whole deal is dead. You have spent all this money and time and effort on somebody who can't afford the vehicle, right?
Speaker 3:So what we do is we take an affordability out view, and that aligns with what Todd is doing, where the first thing we look at is here's people's ability to, here's their total household income, which is directly reported. It's not survey data, it's not. There's not human beings telling us this. This is coming straight from banks and we apply that. We apply against that. Also, what are their fixed costs, like their mortgage payments, their car and car payments, things like that. And we say you know something, if you, you know a lot of the companies I work with they take, let's just and you keep this stuff very simple If I know your income is 120K a year, I'm going to take. What I will do is take an auto payment that's 10% of your monthly income, right? And then that we're going to target you that way, and we have customers now just doing that. We, and we have customers now just doing that. We have partners doing that now who are seeing like a 3x increase in conversions on the outreach that they're doing.
Speaker 2:Based on. I'm going to show you vehicles that I know are within the income capability that you have, that you can actually afford.
Speaker 2:Yeah, I look up enough and pissed off my finance manager by dropping a customer into my F&I department that could not afford that payment and look, that sets up a lot of bad experience for the consumer, wasted time for the dealership and that consumer is just going to go down to the other store and go buy the car they could afford because they're going to save face and they're not going to do that with you, Right? So I think, aligning on affordability this is why you know, I think everyone's pushing so much to have like a, an accurate vehicle payment calculator right On the website, because that's what people, customers, use, because they're trying to figure that out. That's why it's so powerful. On Zillow, right, I need to know can I afford this and what does it really look like? And to me, if we can match and understand the customer's affordability beforehand and then only show him the right vehicles that align with his cohort right, Align with his segment, what he falls in that meets the payment structure that they can actually afford, the propensity to buy goes through the roof.
Speaker 2:The match rate goes through the roof and customer's like, yeah, that's my range right there. Oh, I didn't know I could get that much car or that new of a car. Or, oh, I can get an actual brand new car. I just can't get the top of the line LTZ Suburban. I'm getting knocked into an LT1 at this payment and I think when you automatically match that, you take it out of the hands of salespeople, which is good. And I'm going to tell you why. Because I believe, after since the pandemic, not as much sales training has and maybe people will flame me for this but not as much sales training has gone on to our industry because it has been much more order taking where hey product was far less than demand. So I didn't have to negotiate for things, I didn't have to be a real like quote, unquote sales person. I was more taking orders right and I don't believe everybody has resharpened their skills to do a really good needs analysis on a customer, to be able to ask them all the right questions, to put them in the right vehicle up front front. And I think with what we're doing with data first, it's automatically doing it, it's allowing them to skip that step and saying, hey, sales guy or salesperson, here's a couple cars you should show them. I don't even need to tell the salesperson why to show them those cars. I don't say that's all they can afford. We can just do it automatically.
Speaker 2:We have the dealer's inventory. We know what bucket they live in, what vehicles they should be looking at and what they can afford. That just pops up in front of the salesperson. Now, sales manager. Yeah, they need more context, right? I want to know this guy is going to buy. His propensity to buy is high. He's going to be landed on one of these cars and here's his affordability structure. Right, and then more data, right. But I think this is an interesting time again where our industry is now caught up. We have rising inventory. We have price compression around used cars. Dealers have to relearn to sell and retrain people. That takes a lot of time, or we can leap ahead now with data and put them in a better driving seat and deliver a better consumer experience, and to me that again, this is the world we're heading towards. It will all be driven by this, and this also allows dealers to have the current sales structure and sales experience and still yet perform at a higher level.
Speaker 3:To add one more thing. Just add a little bit of color. I apologize, sean.
Speaker 1:No, keep going. These are great points. You guys are sharing a lot of great stuff.
Speaker 3:Well, my stuff's pretty good. I don't know about. No, I'm kidding.
Speaker 1:I love it.
Speaker 3:What I want to make sure that we underscore for anybody who's watching this or listening to this, right is what we're not saying is somebody submits a lead or walks in and says, I want to look at this car and you say, well, you can't afford that, we're going to. Well, I'll walk you to something else, right, what it is is okay. Well, let's take a look at this car. And hey, maybe they're looking at an LTZ. Their payment would allow them to step up into an LTZ. It goes both ways, right? It's not just showing something less expensive, it's showing them what they can afford, and if they want to spend less, fine, let them do it. But here's what you asked to see, and here's a couple other ones I want to show you, just so you see what's available for you and let them make the decision on how they want to proceed.
Speaker 1:Right, that's a great point. And among all of the great points that you both have shared here in the last couple of minutes, a couple of things that stood out to me as I was listening. Every well, all of us in the industry know that consumers for a long time have been overestimating their ability to afford certain vehicles. It just happens Well, in what you're sharing, you can steer people. Even just what you were just sharing, brian, that steering of somebody is to yeah, if they want to make the decision on they buy something that they can easily afford, or illuminating, or showing them that they're able to actually afford at a higher level if they want to. That is extremely important. And having that in a verifiable, all of this data, so that that also sets up a better experience for the consumer.
Speaker 1:Some of what you were sharing there, todd, that there are a lot of people that end up I don't know, maybe it's 25% of deals end up falling apart or they get denied financing because people have these unrealistic budget expectations. And you guys are sharing all these points that kind of speak to both of those things being able to steer the consumer, which is, ultimately, we all talk about customer experience all the time customer experience all the time. This also helps set you up to provide a much better experience for the consumer and avoiding some of the things that are usually the most explosive when they finally go off in the dealership, like what You've led me all this way, and then it falls apart. Some interesting things there. Before we get outside of this part of the topic and of the conversation, I'm curious to know from either or both of you how is this approach different from the traditional methods of assessing the customer's buying power? Maybe contrast it to the opposite?
Speaker 2:The initial glance of that is let's look at an average retail dealer today. Right Lead comes into the CRM, the first thing they'll do they'll call, they'll email, they'll text. Right, try to get a hold of them. And they're going to get a hold of them. And most likely only thing they're going to do is try to get them in it's appointment setting. We still operate that we're only measured by physical output, meaning how many calls did you do, dials, text messages sent, emails and appointments scheduled?
Speaker 2:Right Customer now comes in and they're coming in on a let's say the lead was a Toyota Tacoma. They come in salesperson's mind is one place Show them the Tacoma. That's why they're here and a lot of times we bypass what drew you to the Tacoma? Why do you like it? What are you going to use it for? Do you have a family? Are they ever going to use it like? Do you drive on highway? Do you drive in city?
Speaker 2:Like we stopped understanding our customers. Now I will say best salespeople on the planet still do this like clockwork. But the majority of salespeople just focus on only what the customer has told them. That's their limited perspective and I look at that and I say, well, using data, we can change that. We can understand the customer behaviorally and help the salesperson bridge that gap without a very lengthy conversation. Now, I still think you ask customers questions because it allows you to build rapport, but the other side, if I have data fueling those questions, they can be far more valuable. They can get me to where I need to go with that customer faster and ultimately, as you just said, sean, deliver a better experience for that customer.
Speaker 2:And I look at our business today and we're still kind of caught in this like analog processes, right, and we're trying to throw technology at it, but in a wrong way. And I think we're trying to throw technology at it but in a wrong way, and I think we're trying to apply old world technology to modern stuff and it's just like a clunky disconnect. And this is where I always zoom back conceptually that let's start like we'll go the Elon Musk thinking of first principles and rip it all the way down to pure fact. And fact is only you have a lead and a customer has an interest, doesn't say they're going to buy a car. How do I use data to understand that in total, 360 view? How do I put the right information in front of my salesperson to empower that customer on a journey that is personalized and unique for them and that's far different than the processes we see today in any store.
Speaker 1:That's a great segue, because I want to take you guys a little bit into personalized vehicle recommendations, brian loves that.
Speaker 2:That's like his favorite thing in the world.
Speaker 1:There's a study from Capgemini that states that personalized marketing increases conversion rates by about 20%, and I know a lot of people talk about personalization and marketing and automotive and I think there's a few different interesting conversations relative to it. But you guys have even mentioned, on this a little bit, using cohort data. So question here is using cohort data to determine top three, maybe top three types of vehicles that a customer could be interested in Is there? Could you explain that process, maybe, how that works, break that down a little bit.
Speaker 3:Yeah, so I'll dive in on this one. So you know it's funny. You talk about personalization in all of us for the past 25 years, 30 years. Every company out there is claiming that we've got personalization, we'll do one-to-one marketing. And then you get the automated emails from them that say dear, open bracket, close bracket, because they forgot to put the name in and it used to be like you know that was state of the art, right, Having your name on the email being sent out to you, right and what we're saying is the email that's being sent out to you.
Speaker 3:You shouldn't just say, dear Brian. You should say, dear Brian, here are the cars we know you're going to be most interested in, right, and here's why we know you're going to be most interested in that. So, listen, this just becomes a. At some point, you become kind of a black belt in using data, and systems like Core AI make that happen automatically, and what I mean by that is we mentioned the economic cohorts, so that's the unimaginative name we at Equifax have given our affordability cohorts, right, so we have 71 segments, and what it is, though, is the first thing it looks at is your affordability level, right, meaning your income, so what's the income of somebody in this segment? But then it layers in all the marketing kind of I call it gobbledygook, but it's valid, right, which is hey, how likely are they to be married? How likely are they to have children? Do they go skiing, do they? Do they like to be, you know, first on the block with the new thing, or are they laggards, right? All the marketing stuff we've all been raised on, but the first thing it does is it looks at your affordability. So let's just say now leads are coming in. Oh, and actually let me take one step back. Let's just say, now, leads are coming in, oh, and actually let me take one step back.
Speaker 3:The other thing that happens then is that the entire database can be appended with what that economic cohort is. So now imagine this we take a look at the last year of your sales and we say, hey, you are doing unbelievably well with the J53s that I mentioned earlier, right? J53s? Are you know young urban achievers? That's whatever the segment is that I mentioned earlier, right? J53s? Are you know young urban achievers? That's whatever the segment is that we call it? Right? They make on average, $178,000 a year. Only 22% of them are married, no, or have children, excuse me. And then here's all their psychographic information. Right, but now you know when somebody who comes in, who's labeled or appended as a J53 on the lead as it comes in, in real time, you can do that.
Speaker 3:Right, we got to offer the J53, these vehicles, because most of the time, this is what they end up buying. This is just, and people think, well, so what's your algorithm? There's no algorithm. It's looking at your. This is where the value of your first party data comes in play. Is we're just going to take a look at the data that's sitting there, fallowing your data set, and a system like Core is going to put its AI brain on it and say listen, when this guy, sean, shows up and he's a J53, they're five times more likely to buy this type of car than this, so let's make sure we throw that in the mix. There's nothing more complicated than doing that. It's just that you need a giant brain that can do it all automatically for you on the fly, and that's what something like core ai can do yeah to me.
Speaker 2:I look at the same. And then there's also another aspect taking the website visitors, de-anonymizing them and then knowing, once I've de-anonymized them and I can ID them, you can put things in front of them that feels like minority report, Like hey, it looks like you gained five pounds and you need new jeans, Todd. And I see that world of like crazy personalization, Like this is going to be the new driver. And listen this to me, I just had to look. It goes all the way back to 1993.
Speaker 2:I read a book called the One-to-One Future by Martha Rogers and Don Pepper. They were direct marketers because there was no real internet right and how they used to deliver one-to-one marketing at scale through traditional things. So that framework has existed now for over what are we talking? 30 years? None of this is real. That piece isn't new. But by being able to put those kind of what I call almost traditional models, break them apart, use the attributes of them now on AI, you create a whole new level of what's possible for personalization, and it's the same understanding of a thing that Libby did back in the 60s with direct marketing.
Speaker 2:I have the book, which is super cool because it's so out of print you can't even find them anymore and it was called Recency, Frequency and Monetary Value and they used to code databases with a three-digit code A 111, someone who wasn't recently in, not a frequent user of your business, spent the least money, and a 555 would be your recently in frequent user of your business, spends the most money. And then you have quintiles. You have people all across the gaps, right? You have a one, two, fours and a four four ones, and you have all these things that they create quintiles, but it allows you to target and market to them all differently. And to me, now, that is like the prehistoric way of what you can now do with AI and so much faster and in real time.
Speaker 2:Because think about this and just think about in one category. Let's take oil changes. So in dealerships they constantly send out low cost oil change offers to their database Right, yeah, low cost oil change offers to their database Right, yeah. But there is a group, a segment in their database that'll pay full price, Right? So you?
Speaker 2:lose that money instantly, because the full price guy is like ah, coupon, I'm going to use it. So to me, it's that concept of like maximizing through understanding your audience. It allows you to create the right personalization to activate them into action. And this is where AI is just going to blow the doors off of possibilities. And we're only seeing, our engineers are only seeing the beginning of what we're already doing with web data and then the muscle of Equifax data. The acceleration is going to be not only incredibly fast. I think we're going to get to a point where, like, that guy only gets this because we already know so much about him. Like this is how you keep his what I call loyalty loop moving, while this person's loyalty loop moves completely differently. And now magnify that over a 25, 50, 100, half a million customer database in real time. That's the new power, right when we couldn't even. We couldn't have processed that two or three years ago. It would have been impossible.
Speaker 1:Yeah, it's. I mean, personalization is actually getting to be real, as opposed to just a word that we use to get dealers attention about some new thing that's taking on. I wanted to ask you guys about. You know, it is a personal thing in terms of vehicle recommendation. It's a personal thing when there's an availability issue and people are like I really want this. People are like I really want this, and so I'm curious to know you know, how does access to real-time data inventory from the dealer factor into the vehicle recommendations and opportunity? Obviously, that's a very personalized thing. How does that factor in?
Speaker 2:Yeah, look, I think we run mostly stores on like a 15-minute, so accessing dealership every 15 minutes.
Speaker 2:A lot of it depends on the dealer right. Some dealers may only be updating their inventory once a day. We don't think that's the best right. Some are twice a day. I mean 15 minutes.
Speaker 2:When you have a store or a group that is selling a decent amount of cars, meaning stuff is constantly moving or being added into the mix, the faster you can create that match the better. So I think that creating a decent data update cadence and what you're looking for, you're not really rerunning a whole database. You're only looking for changes in the database like what VINs were dropped, what VINs were added right, and there's probably a future and Brian might know more where, as we dive deeper into the data and you understand what customers buy and you understand the attributes around that vehicle, you may be able to reapply those attributes to different vehicles, meaning this customer always buys leather, sunroof, convenience package, car play right. Once you're in a VIN level like understanding, and the machine learning will know and it's just like well, I can declassify these cars out of inventory instantly, beyond affordability, because the consumer has these preferences that are hard-coded in what we see them purchasing and that's where we're heading.
Speaker 3:Yeah, those are all great points, todd, and just one point of interest you made me think of here we actually have OEMs using the same data Core is using to actually better target inventory allocation so they're able to understand the population across the US and who's going to buy what ahead of time as they're coming into market. That's the second piece they're looking at. They're saying we got to have more vehicle X over here and more vehicle Y over here, so they're optimizing their inventory mix using this data, which is what Todd is actually enabling to at the deal level.
Speaker 2:So it's funny you say that, brian, because I think right now a lot of the manufacturers have misbuilt things.
Speaker 3:Oh, absolutely.
Speaker 2:So every manufacturer listening should probably give you a call and have your data, because there's definitely a huge amount of product mismatch in the market today where they built things and wrong configs to the market. But I mean, when you break that down, brian, now you got me thinking like the value to an OEM to deliver the right cars into a marketplace to not have to move them or discount and incentivize them to move from that dealer ground is incredibly valuable.
Speaker 2:So when I had my Chevy store, I only ordered black Tahos and Suburbans, mostly all LTZs, because I knew I could trade for any other terrible color at the time that was being produced, including that Bermuda blue that I remembered so well. So I took the complete opposite strategy and said well, everyone in New York always needs black. So I took the Henry Ford advice at my Chevy store and that's why I ordered almost all black, and of course they would have to throw me the occasional beige, white or that horrible ruby red thing. But I avoided a couple of those other colors like man I. I remember bermuda blue hit my lot and I was like, oh god, I'm gonna have to put a huge, freaking discount on this.
Speaker 1:I might as well make it a demo for six months and drive this horrible color as long as you can't tint windows in new jersey.
Speaker 2:So I I refuse to do that.
Speaker 1:So you guys are making this easy. I was going to ask about some kind of in real life scenarios, but you just shared a couple that I think are massively valuable and I think we'll probably end up talking about them even on future episodes. And before I move on to, kind of, the last category that I want to pick your brains on, I can't help but maybe just emphasize one more time that all of this leads up to so much benefit for the dealer. Right, there's just so much. It's the expansion of opportunities for them to be more profitable, for them to, you know, better efficiency. There's just so many like this whole operating system, getting your mind around that. It's expansion of opportunities through all this data that can be leveraged in ways that it hadn't before, but it absolutely is pretty much at the center of the target, when utilized correctly, going to make the experiences for consumers better too.
Speaker 1:That's why I say these win-wins, where we've wanted these things and we've almost believed whoever the Pied Piper is leading everyone off the cliff. There's been a lot of those types of people trying to take those messages to our dealers and to the industry, for, I don't know, at least a decade or 15 years now that didn't have all of this, and now we have it, and these are just different conversations that I think are really, really powerful for dealers to be paying attention to. So I want to take you into the last kind of section of today's podcast, and that is basically the underutilized potential of data in our industry. In our industry, you know you, you've stated that data is incorrectly valuable. Right, it's incredibly valuable, but underutilized. Why do you think that is the case, is it? Well, I just want to know, just off the top why one word and Brian, you jump on this word.
Speaker 2:I'm going to go siloed All right Siloed.
Speaker 3:Let me go backwards one step before we get to siloed right.
Speaker 1:Yeah.
Speaker 3:I think what there is. This is already a cliche too, right, but data is the new oil, right? That's one of my previous companies. A CEO would always say that, and I just always liked that slogan, right.
Speaker 2:Which I think you stole from my presentation. I literally can pull the slide up. I'm trying to get out of your presentation Probably 15 years ago that data was new oil, so I'm going to pull it up.
Speaker 3:Here's the problem, though okay, that a lot of dealers have gone through and I went through myself A there was a lot of bad data out there. There are a lot of fly-by-night data providers, and once you burn somebody once, they're not going to touch the stove again, and that's a lot of what we fight right now. But I had a lesson taught to me the hard way, right? So I used to work for this company that we were behavioral data pioneers, and I was in talking to an OEM VP and they were one of the OEMs that used our data, and I'm presenting all of this data to him and it's incredible and I'm in love with it. Right, this is 20 years ago. I'm in love with the data. I'm just like wide-eyed and teary-eyed looking at it, and he finally said to me he's like Brian, I love all this data, but now you have to tell me what the F I do with it. That's exactly what he said his term and it hit me like just between the eyes, right, like I'm in here showing them all this beautiful data and I'm not telling him what to do with it or how to use it, right?
Speaker 3:So that's the difference now, which is that you have, like smart people like Todd and a bunch of other people have realized I can't just walk in and tell you to use the data or you have access to this data. Now you've got to have this system has to also automate it, so that I'm going to get the data for you and then I'm going to execute against that data, and it's not going to be something that requires you to do anything. I don't want your salespeople going into the system and touching anything. The system has the brains now and processing power to do this without you thinking about it. And if you don't believe me, just go on Amazoncom and see what happens every single day, because there's not humans there deciding what to show to you, it's a computer it's SkyNet, right?
Speaker 2:Yeah, I totally agree. I think, when we looked at it, the same that dealerships look, they want you to in a lot of cases they have limited amount of time. They're always open and willing to try new things, to sell more cars, but it can't change their process and they kind of want to use the same infrastructure that they have. So I think for us it was understanding that okay, when we deal with those constraints, we need the CRM data we need to get on the website. We need the DMS data. We need to aggregate that. We need to now process all that. Now we need to bubble up the opportunities in a way that could feed their existing things and that could be their agencies. Right, it could be their direct mail company for some of it. It could be their BDC for the really like people that, hey, these people need contact, like right now. It could be back to their CRM for a piece. It could be some other service they use. It's crazy. I was just talking to a dealer and I'm like do you use your CRM to send stuff out? And he goes well, I go build the email template and design it in some service, then I bring it back and then I put it into my CRM and then I send it, but I don't send it to everyone and I was like what a crazy. I was like this guy. I was like that is an entire two days of something that if you had MailChimp it's like 36 seconds right, hit a couple of buttons, pick my lists and I go. So I think, like for dealers, yeah, as Brian says, less is better and they just want the benefits of it. Right, and I think dealers are not in the data business, but dealers have to start considering themselves in this business, because it is the lifeblood of their business.
Speaker 2:Though inventory is important, though their facility is important, their ability to collect, organize and understand their data is what's going to propel them. And what we've talked about today is one sliver of the data. We've talked about sales and marketing data. There is multiple layers of system of intelligence. Where we talk about operational data how do contracts in transit move? How much time do things take? There's all the internal data that the organization is creating. Because of technology.
Speaker 2:Organizations throw off so much data, but most are barely getting their arms around any of it to utilize, understand and then optimize, and I think the only competitive point of the future is dealers to get more efficient, Because everyone has the same cars. You're not going to outsell somebody based on pricing your inventory right. You may get slightly better salespeople and train them, but it's not going to be so incrementally different than your competitors. Facility is facility. So what are you going to do?
Speaker 2:And your ability to operate more efficiently than your competition is the true to me only place where real money is going to be made, where, if it costs me as a dealer, $100 per vehicle retail and it's costing you $250, $500, $700, and my competitors, I win every single day. 500, 700 are my competitors. I win every single day. Even if I'm $200, $300 less per vehicle, my PVR is less, I still beat you every day, and I think it's a change in the game. It's a cerebral change of what game are we really playing? And yes, we sell cars, but the cars are an output Like for Amazon. Do you think Amazon cares about selling books? Amazon cares about understanding you and what you will buy and when. And they've perfected that, hence making Jeff Bezos literally the first or second richest guy on the planet, because he put his effort in the customer experience by understanding you and all the products. They're just bonus.
Speaker 3:He doesn't care you know that Amazon for 2023, they attributed $16 billion of their revenue directly to the personalization they can do as a result of data $16 billion for one company.
Speaker 2:So think about this Zero, for today, dealers are zero.
Speaker 1:Yeah, great point. Yeah, it's amazing.
Speaker 2:Think about that. It's all uphill, it's like perfect. Now is the time for dealers to get in, build a system, to get in, build a system and the other. One other thing I want to leave with is dealers treat data. The nicest way that I would put this is they're not putting thinking through it all the way. When you hire a vendor and I give them your data and then they go off, clean it, do stuff with it, and then it stops working after time for whatever reason. So you fire them and then you hire a new one and now you re-give the same old data to the new one. He cleans it.
Speaker 2:Dealers need to have control of that data center, and that was a big thing with Core. We wanted to deliver was look, we're going to organize your data, it's going to live and now you can connect it to whatever vendors you want. We don't care, but we also want to see what went to them and where, because that's going to be a big thing with compliance where. What data was sent to that vendor? They got hacked. Okay, I have to understand my data schema of responsibility. Dealers have no idea of that across the board. Many stores are sending data to providers who they're not even contracted with any longer. I see that all the time. But dealers need to have a nucleus of data that is never going to change and it will become, through time, by far the most valuable asset of their organization. And that is not going to happen in a CRM, it's not going to happen in a DMS.
Speaker 1:Man, this is a great spot to reel you guys in a little bit. It's a really really good episode.
Speaker 2:I mean real me, I know, I know, I know.
Speaker 1:Just really, really good stuff. I want to give you guys both um, maybe at the end of this just I got a couple things to ask one I love both of your uh takes on what you think the vision in terms of future of data utilization is going to be. Um, we've kind of covered a lot of that. But if you guys want to kind of give a your concise thought, if you put on your what's happening next year, five years, you don't have to go to 10 years, but what's the future?
Speaker 3:We're so knee deep in the future right now that it's hard to say what's happening, like what's happening. I think we talked earlier. You mentioned don't like the word disruption, which.
Speaker 2:I agree with right Disruption.
Speaker 3:The highway is littered with the bodies of previous disruptors. But what I think we are in is an attitude adjustment is what I would say, and the attitude adjustment is that data is not something, data process and customer experience are not something, that I can be on cruise control anymore and listen. I mean, look at the mega groups, right. If you don't get good at doing what they're doing, they're coming for you, right? They're going to put your smaller stores and your smaller groups out of business if you don't get it. And here's what's really cool is that the product, the tools that Todd has created, can be scaled for a mega group or it can be scaled for an individual store. You can have the exact same capability as those guys. It's kind of a democratization of capability in data is what's happening is where I think this is going. More are going to have access and see the value in using this type of data in their sales processes.
Speaker 2:Yeah, listen, I live in probably two-week increments. I'm like a fly. You know my cycles are really fast because I live with our AI engineers and they're like, just when I think I have something, they're like, hey, look at this, this. And then two weeks later I'm like what's that? Oh, they're gone. No, no, we had this. That architecture is gone. And I was like what do you mean? It's gone. They're like oh, no, no, no, this has been released. This has changed this.
Speaker 2:So I think we're living in an insanely fluid time, and that means infrastructure that's being built today has to have that capability to be incredibly flexible. And the challenge is in our industry. Almost all our industry is built on archaic architectural structure, fixed database fields. So we have to rethink some things to be able to kind of start turning on these new business opportunities. And it's just looking at things from like to me, that first principles view versus you know, you're not going to get it out of a CRM today. I mean, they would have to gut it and rebuild it, and nobody's willing to do that because it's just too expensive, right.
Speaker 2:And it's weird to say that, because the new companies are going to be the ones that grow and ultimately then become the old companies, and I think you're just going to see that cycle move faster. Today, where it took, you know, let's say, in auto, it takes probably 15 years to go from a, or it did from, like my startup, my previous startup, my chat company to being like a good size in thousands and thousands of stores Right, and now you can do it in three years. Right, and soon you're going to do it in a year, like because infrastructure enables that. And we're just dealing with a new world of AI infrastructure that part I mean.
Speaker 2:Right now, 27% of our code is written by AI inside core. It's writing itself at a small level, but it is taking care of itself too, which is mind-blowingly crazy to think, like Skynet is really turned on and what happens I don't know, but it's very interesting to watch it unfold. And I mean, listen again, I love this stuff. I'm super excited, you know, not only for data, but I think the passion has always just helped dealers do what they're already trying to do sell more cars operate more efficiently. Help dealers do what they're already trying to do Sell more cars operate more efficiently, and think about the future from a perspective and a roadmap that they can get behind and want to execute on each and every day.
Speaker 1:I got one last question for both of you. So you've got a dealer standing in front of you. They've listened to all of this conversation and they you get to give them your advice. They're considering this more data-driven approach. Um, what advice do you give that dealer?
Speaker 2:Go easy. Yeah, what do you got? You have an answer.
Speaker 3:My, my, no, no, no. My answer to the dealer is don't overcomplicate it. The stuff we're talking about here. Everybody wants to come in and tell you they got a black box. They don't right.
Speaker 3:When you ask somebody how does it work and they say, well, we've got an algorithm Run, Because if they can't explain what they're doing, you're not going to understand what they're doing right. So what I'm trying to say is understand two things. Right, You're going to have people talk to you about AI. What's AI right? Ai, again, not a black box. Ai is simply, it's something that has massive amounts of computing power that can look at all the different variables that you could too. But the problem for you is that AI can do it in about a second and it'll take you about 45 years to come up with the same number of variables that AI could. So that's the first thing. So it can help you with decisioning, but the second thing is the data itself isn't hugely complicated. What we're talking about with Todd here is somebody walks into your dealership. We can tell you what they can afford. It's that simple. Would that help you sell cars, yes or no? Yes, Okay, Hurry up and sign up for Core AI, because they're going to help you do that.
Speaker 2:Yeah, listen, as Brian says, like AI just gives you the power to have tables of billions of lines and instantly see patterns and correlations that humans just can't recognize, and it does it at a speed that is unbelievably fast. And because retail lives in a faster cycle, you need that and I think for dealers, as Brian says, forget all AI. Forget all of this. If you look at the 20, 30, 50,000 people you sold cars to, if I could tell you which ones are back in market today, is that valuable to you? If I could tell you the ones that are back in market today and what they can afford and, most likely, what they will buy, is that valuable to you? If I could look at your inbound leads and tell you which ones are real buyers again, what most likely they will buy within reason and what they can afford, will you be able to close more leads? Because of that, I can't answer those questions. You, as a dealer, answers those questions right, and if you can answer them in a way that you go, yeah, that makes all the sense in the world. Then forget the tech. Like it.
Speaker 2:To me, it's business. It's always think process first and then the tech that supports your process. Do not go finding tech and adapt your processes to the tech. You will fail. Because to me, your processes are always the most important. Because, in a good example, when I first consulted, did a ton around CRM back.
Speaker 2:I know this will date me 2000-ish dealers always ask they're like well, who has the best follow-up program? Todd, just put that follow-up program in my CRM and I'd be like that's the fastest way to fail. And they'd be like what are you talking about? I was like that's their business. Your business is different. What you should do is don't do a lot, do very little. And does it work or not? Then correct, Add a little more, take a little off this, put a little bit more farther out, put more close. You have to build your own and that's what people don't want to do in our business. They want the genie lamp comes out. Give me my wish selling 300 cars a month, boom, I'm done. Yeah. But the reality is the smart dealer takes the road that it's built off their process. They've leveraged, they're now leveraging tech to accelerate their processes. They're the ones who are going to win this every single day.
Speaker 1:Todd Brian absolute, amazing episode, Great insights, excellent advice to end it. I just want to thank you guys for absolute, amazing episode, great insights, excellent advice to end it. I just want to thank you guys for a fantastic episode To the audience. I think it's self-evident, but you may be one of those dealers or somebody listening and, by the way, thanks for spending some of your time with us but you might have misconceptions or fears about moving in this much more data-driven direction, and I just want to say that's okay.
Speaker 1:Technology has been moving so fast for all of our lifetimes that it's almost impossible for us to keep up with as consumers, let alone fitting it into how you operate your dealership. So it's okay, but you need to meet people and know people that can actually tell you the truth about these things and how to put it all together, and I can't think of a couple of guys that know this better than Todd and Brian. So make sure you connect with those guys. Jump on LinkedIn and follow Todd and Brian so you get more insightful information. If you're watching this episode on YouTube, hey, hit the thumbs up, subscribe to the channel so you don't miss any new episodes, and thanks again for tuning in. We'll see you again soon right here on the Core Conversations podcast.