A Fresh Perspective on Automotive AI Strategies

Speaker A: Hi, uh, this is Brian Pash, and welcome to another exciting podcast episode. DMSC is over. And the buzzword, whether justified or not is AI this, AI that. So I decided to bring automotive industry veteran, AI leader, pioneer, and one of the few people who actually has thousands and thousands and thousands of examples of AI in automotive. Albert, CEO of UM, ID Privacy AI. Albert, I'm so excited to just have a conversation to help dealers get up to speed. So for the dealers who don't know you, give me a little thumbnail of, uh, your work, your tenure here in automotive.

Speaker B: Yeah, absolutely. And Brian, thank you so much, uh, for the opportunity to be here. You know, I really, um, have always valued everything you're doing, and talking about a pioneer, I feel, uh, very honored to be in front of a pioneer myself. So thank you. Um, again, thank you. You're very welcome. So, uh, Albert Thompson, um, as you mentioned, CEO and founder of ID Privacy. Um, my background has been, I say 25 years, Brian, but it's been longer than 25 years. I started when I was 16 in automotive and haven't been able to escape since. Since then, um, sold my first franchise, uh, store Northeast, uh, Ohio at 16 and Carfax in the early 2000s and AutoTrader. And from there, um, the background just continues to keep layering on. Went to help launch Trade Rev, um, and took that to Car Global when that was, uh, exited and was one of the first few to also help launch Drive Auto. Um, took that through the Sinclair Broadcast Group and built their digital tech stack till I actually launched my previous company, which is Brian. We spent a lot of time together on that side, which was, uh, the first party, um, identity layer, and was, uh, able to take an exit early 2024. And now here we are with ID Privacy AI.

Speaker A: Great. So, Albert, I've been following you on LinkedIn. First of all, you have the most thoughtful posts. They're not short in any way. You love to write like I like to write. And sometimes I wonder should I make this short or long? But I can't help myself. Um, I wanted to interview you because there seems to be a mad rush for AI solutions. My concern, and I brought this up a number of times, is who's controlling the consent, who's controlling the cadence, and who's controlling the context if there's 3, 4, 5 different AI platforms being used in, in the dealership. So give me your snapshot. What are you seeing? Obviously you're, you're knee deep in all of this or neck deep. But what do you, what's your observation in how the vendor community is approaching AI and selling those solutions to dealers.

Speaker B: Yeah. Um, you know, it's interesting that you actually brought this up. It's one of the biggest pain points and one of the biggest problems that we, early on, when I launched the organization, um, saw as a problem. Right. Um, and if you think about it literally, uh, the thesis, the problem statement, the thesis that we saw in the very beginning, um, especially as to how it pertains to AI and how it's going to, you know, integrate within a dealer operation is we already have system sprawl and we already have data sprawl. Right. We have. Every dealer, I think, has nine to 12 systems today. Um, and here's the problem. Right now we're talking about adding AI tools on top of tools and on top of systems. None of them are talking to each other. None of them are interoperable. And I think you said, right, consent. Um, none of them, uh, have. They all have individualized consents. So there's no unification to this. So my biggest problem, my biggest fear is that we're just going to further fragment AI on top of further fragmented systems. Um, and ultimately it's going to lead to a messy divorce with dealer and AI tools in six months.

Speaker A: Yeah. And, um, you know, we're going to get into that and what your company is doing. But what do you think? One of the biggest misconceptions about AI is for dealers. Because it seems to me that dealers aren't concerned right now about consent, cadence and context. They just see it as, yeah, that would be good. But this guy's helping me with my service, this agent is helping me with lead follow up. This agent is responding to phone calls. What's your m take on the biggest misconception with AI in automotive?

Speaker B: I think there's several misconceptions. Uh, um, and I think you just nailed it. Um, the fact that we're thinking about agents, in a sense that I have an agent for service and maybe I have an agent that's going to do my SMS and then I'll have an agent that's going to do my SEO. Um, I think that's the first misconception. The biggest misconception is that we think the AI or agents is something that you just buy and that you just bolt on. And I get why that misconception exists. I totally get it. Dealers have been buying software their whole career. Right. They know how to evaluate a dms, they know how to negotiate CRM contracts. Um, and they know how to kick the tires and watch the demo and sign the order form and implement. That model works for static software. Uh, unfortunately, Brian, AI is not static. Right? It's not deterministic. It changes, it learns, it adapts. And you mentioned that with, um, the cadence. And to me, cadence is a big word for orchestration. And if you don't have a native AI stack that works across service, sales, uh, parts, finance, and the entire dealer ecosystem, that cadence doesn't work. Right. So, um, now you're, like I said, you're going back to further fragmenting it. So, so misconception number one is that AI is not deterministic. Uh, it's probabilistic. Um, and so I don't think dealers quite understand that. You know, they say you really have to understand that you don't buy it like software, it doesn't implement like software. Um, and it can't just be bolted on. That's misconception number one. Right. You can't just take one tool here and say, that's great, that's my service voice agent, and I'll do this one for my sales and I'll do this one for my SEO. That's, that's, that's, that's a problem in itself. Number two, um, uh, the other misconception is that, that, that dealers tend to think that AI. For some reason, we've all thought that AI should be perfect. Um, and we think, and I don't know where this came from, but I think everybody thinks that the agent should be perfect from day one. And I, I explain to dealers all the time. I have many conversations. I say, listen, if, if AI agent, as you say, is perfect from day one, it's not AI, it's scripted. It's automation. And scripts break the moment the customers go off that context you're talking about, off that cadence you're talking about and say something, um, that the vendor or the scripting tool did not anticipate, and that's that orchestration layer. So in automotive, that's going to be every three calls. Um, you know, my dad actually owns the car. I'm calling because my, uh, truck is leaking. But I also want to trade it in. Can you help me do that? Real agents can handle those scripted ones. Right?

Speaker A: Right.

Speaker B: Um, and the other thing is, too right, is we think that these AI agents are going to be perfect from day one, but they have to actually learn. Um, and I think there's a third misconception. Right. Um, and this is an important one for me. Mistakes, um, in software means failure. And that's true. Right. So if you buy a website, it's not loading and you have an error 400 or 404. That's broken. Right? That's true. Mistakes in AI does not mean that the AI failed. Um, mistakes actually mean the system's alive. Um, if your agent never makes a mistake, it's not AI and it's not learning. Um, you know, and this is important because dealers have to go in with a different psychological mindset, and they have to go in with a different understanding of how this is, is going to deploy in their business. And what you should measure is not whether it makes the same mistakes or makes mistakes, but can it learn? Can it get better?

Speaker A: Right.

Speaker B: And, and will it, you know, do these become teachable moments? Um, the mental shift I ask dealers every day to make? Um, you know, you're not buying software. You are hiring a little team member. You have to train it, you have

Speaker A: to coach it, you kind of nurture it. Give it some guardrails.

Speaker B: Yes.

Speaker A: Coaching. Yeah. So, so think about that for a moment. Dealers, um, have primarily the same business model, but how they execute is very different. So when you think of where the industry is heading, do you think that dealership executives now really have to get some training, education on how to train these agentic agents with their mindset, with their protocols, with their processes? Now, I've heard vendors say, well, just give me your employee handbook, give me your training manuals, give me, you know, whatever. And it will just absorb it and learn from that. That seems very optimistic, um, for me. So what expectation would you like to set, especially on this third misconception, AI agents are being deployed. How much work does the dealer have to do in those first few months to make sure that their newbie 247 employee, um, is doing the right thing?

Speaker B: Yeah. Um, let me, let me start off by taking a step back, um, and painting a picture for us. Let me frame this up for years and years and years, right? Think about your general manager, right? That phone ringing meant cha ching, right? That meant dollar signs, um, every time they heard that phone ringing in the dealership. So now I, I literally say this statement to dealers. Um, and now I want you to imagine on a Saturday morning, your sales guys are kicking back, maybe they're playing on YouTube. There's not a soul on the lot. That phone's not ringing. And your owner, your dealer, principal, picks up the phone and goes, why is there only eight appointments on the books? We normally have 20. And you have AI deployed and the phone's not ringing. What do you do? And in real world scenario, right, you have this control, right. You could say, get up out of your desk, you go to the BDC guys, go pick up all the, the sales from the last six months and pick them up and call um, them and you know, whatever.

Speaker A: Yeah. Give specific tactical instructions. Uh, because the human observation is saying we have a problem based on historical

Speaker B: norms and we have a psychological need to try to fix it. Right?

Speaker A: Yes.

Speaker B: What are you going to do? You're going to yell at the AI agent? Probably not. Right. So what you'll do is pick up the phone and fire your vendor. Get it out of here, it's not working. Kick it out.

Speaker A: Right?

Speaker B: That's the first thing you do because that's the first control you take. I'll just put my BDC back in or I'll just put my sales guys on this because this isn't working. I had 12 appointments normally. I gotta tell you, this is very important. Um, this is not something you just roll in and put in there. This is like deploying a dms, this is like deploying a CRM. You have to, you know, you have to have buy in from your teams, you have to have buy ins from the bdc, you have to have buy ins from leadership all the way down. Because these scenarios really happen. And there is another side. There is a there, there. I've seen it, I've got the case. I've seen it literally happen. Every store that just pushes through these moments, but those moments are real and I think that um, a ah, real partner to a dealer is going to set that expectation up from, for up.

Speaker A: I love that, I love that. Um, you know I asked people on LinkedIn a question. Um, the funny thing about LinkedIn, and you probably know this Albert as well, um, when someone's impacted by something you write or I write due to the politics, they can always comment. So they'll send me a message like hey, read your article. Well that's awesome. I can't really publicly state that or hey, I can't believe people are voting like that. Whatever. Um, so whatever people see on our posts or newsletters is just a fraction of what's going on. But I put up a poll recently asking people in Automotive who should be the controller of compliance for AI outreach. So if, um, the CRM, for example, let's just say um, you have ah, dealer soc, uh, I mean, excuse me, drive centric with Urgentic agents and then you have dealer funnel with some AI agents doing marketing and then you have another AI tool that is running, you know, chat on uh, the website and then another AI tool that's handling service and sales phone calls, right? Yeah, let's just say that's very common to potentially have four different people using some type of AI intermediated communication. So I asked who should control, is it the CRM, uh, is it the dms, is it the CDP or an independent uh, platform? And it was funny when some people said the dms, which is kind of funny because the DMS is like a dirty cesspool of data. So I had private comments, people saying whoever said DMS is dumb as rock. Okay, so, but, but here's the thing that this is just how people vote. It's a reflection of how they're thinking. They, Anybody who says that DMS should be the central repository for um, you know, unified customer communications hasn't really understood how dirty their data is. Um, Albert, what would you say in a world where most CRMs are going to have an AI layer built in and potentially, potentially, um, those CRM companies are not going to be handling in and outbound phone calls. So you might have a second company call review. Car Wars, Toma, Numa, Mia, spine. Ah, I mean the, the list is growing. Um, if you had a future cast, who's going to control the permissioning. Right. Consent, context and cadence, who in a multi vendor world, where should that sit?

Speaker B: Yeah, um, great question. And I think uh, you know, personally, and this might sound self serving, I don't think it's any of those tools today. I think it's actually a system of action. Right. That's purpose built for agents. So think about that for a second. Um, and the cdp, right? Um, is, is built for, you know, giving that unified, it's built for the marketer, giving a unified view of the customer so they can segment, target and activate across the digital pathways, right?

Speaker A: Correct.

Speaker B: Um, the CRM system of record built for the dealer, built for the salesperson managing the leads. Um, and I can see why a CRM would want to have tools that could help to manage leads. Um, ah, but, but a system of record ultimately isn't that system of action. Right. Um, and so this is, this kind of leads into us, right? This is a little self serving but ultimately I think the engagement operating system, um, becomes the, the layer between the customer contact, the conversation and the conversion. Right. Um, and in that middle layer, um, that's where these agents can have context, uh, graphs that understand real time context that's happening with the customer and all of those, it's that unified layer that would Operate across all of the different deal um, uh, profit centers. And that layer would be purposely built to do what it's supposed to do, which is handle um, those customer interactions. So I think in a perfect world I think you'll see um, the CDP underneath. Right. Because uh, you need to make sure that you have that as the foundation. You'll have uh, the engagement um, operating system sitting above that. Right. Where the agents are literally just focused on engagement and customer interactions and then ultimately they'll be able to interact directly in and um, out of the systems of record.

Speaker A: So let's uh, dive into that um, for dealers who don't know what your company's North Star is, what your goal is, um, what's your elevator pitch because it's, it's has many levels of intrigue. But what would you do to ah, kind of summarize for people on our podcast where you believe your unique skill set and vision is to help solve dealer problems?

Speaker B: Yeah, so um, essentially that's exactly right. So ID Privacy is um, an AI engagement agentic, AI engagement operating system. But let me just make simple uh, sense of that. Right. Is that we have built that middle layer that brings uh, in. I don't care if it's a third party lead from Autotrader, I don't care if it's an inbound service call, an inbound sales call. It's the purpose built operating system that sits underneath of all the dealer profit centers to capture every interaction, um, and activate and manage those leads and those customer conversations end to end, um, through sales service and retention workflows, uh, using voice, SMS and email and chat. And with that these agents, uh, they are context aware, channel aware and journey aware. So I'll explain that. Um, and you see today, and you mentioned some of those um, tools, right. There's tools that maybe just take inbound service calls but that falls short. Right. Because there's real context in those service calls that are relevant to a sales agent.

Speaker A: That's correct.

Speaker B: And those agents need to understand each other and that context gets lost if you don't have that operating system in between.

Speaker A: Uh, yeah, and let's just pause for a minute because I always like to give a dealer example what Albert's talking about. If somebody calls to book a service appointment, an AI agent may do a perfect job, but they may also say, hey, by the way, I'm thinking about trading in my car.

Speaker B: Yes.

Speaker A: And I'm not sure how much these repairs are, so I may uh, consider a uh, trade in, well a AI agent just built for service will book the appointment. When you have agents working together, then there would be a handoff and say hey, look, this customer is coming in for service. But they're also thinking trade, maybe start reaching out to them and finding out what you know, vehicle they want to trade into, you know, and, and what you're saying is having all of those agents working together in an engagement layer, um, is what makes the magic work.

Speaker B: Yes, that's exactly right. And, and I think that that's in. And that's the big difference between say like a chat bot and say, um, you know, great, that's good information. And then it basically just takes it and it's a passive system. So take that same scenario, right? Somebody calls in for service, um, you know, and you've seen it today, right? Are you new returning? And then you know, hey, I see you have this vehicle on record. Great. And the customer might even say hey, actually I sold that car and that's a big problem for us. Right. Um, that car is not no longer. So the agent would still just book the appointment and go through it. And then maybe the customer does say, but I am still thinking about trading it in, um, or maybe looking at an opportunity that that appointment might just get booked and it's just passive. That's it. That tool stays static, it's done. It sits onto the side. And that is ultimately um, there's, there's just no interoperability in ah, an engagement operating system essentially that would come down right to that, that, that context layer and that context rich response would then pass over to a sales agent who can then you know, put all of that together, actually take out the vehicle that the customer said I don't have anymore. Right. Which then becomes this living, healing, intelligent graph. And then update it to validate the vehicle. That's, that's their, their, their car. And then update them as a, as a, as a, a um, trade intender. And then that next outreach might say hey Mr. Smith, you know, I saw that you reached into service and said you had a rogue you were interest trading in. You know, it'd be really great to talk to you about the new rogues. You know, do you have 30 minutes this week to get you in? And that's a context rich approach to the agent reaching out. Yes.

Speaker A: So Albert, you know, there's a lot of claims about the benefits of AI.

Speaker B: Mhm.

Speaker A: Um, whether it's taking inbound phone calls. More recently, people doing outbound phone calls, uh, obviously the lead handling 247 again, I always worry about you Know this idea of, um, compliance, context and cadence. But you have published and shared online a number of examples in scale, meaning nothing insignificant, for dealers who are really looking for a partner for an agentix solution and they want to understand what benefits they could have from dealing with your company. Can, can you give me one example for variable ops for the sales people leaning in and one for the fixed ops, because we are getting more and more fixed ops directors listening into our podcast. So could you give me two examples and would you also give us the context of how long it takes to kind of ramp up to speed? Right, so, uh, you just said, you know, you said earlier, Brian, I want people to know that there's some training. So when you say, hey, this Toyota dealer book, you know, what was the context was that? Okay, in their first 90 days I got everything perfect. And then that fourth month they rocked it like this. Give me, give me an example for variable ops and fixed ups.

Speaker B: Yeah, so, um, you know, so our system, you know, really, you know, first commercial agents that went out are the sales and service agents, right? So very simply put, um, you know, our systems are bi directionally integrated into Most of the CRMs and most of the service schedulers in the platform, right? So you would deploy. Let's just start with variable ops, right? So you would deploy an inbound and an outbound sales agent. And I say inbound and outbound sales agent because they're two different things. Uh, you know, I've heard a lot of other companies saying, oh, we should have one agent that does it all. And that's actually fundamentally, just doesn't actually make sense, right, because there should be agent to agent handling. But, um, as an example, if there was a GM or dealer principal listening right now and you wanted to actually deploy, uh, an agent, uh, with ID privacy, um, we would essentially integrate directly into the CRM. Um, we would, uh, deploy an inbound agent for voice, uh, sms, email and uh, chat. All of them interconnected and talking to each other. Um, so if somebody comes to the chat and here's an example and says, hey, you know, I'm looking at this vehicle, you know, is this, um, OEM still offering 0% financing, engages, disengages, maybe the next day they pick up the phone and call, then the agent would actually be able to take that call and know who that person is, right? Be able to have that conversation. Hey, are you still calling back about that vehicle with that 0%? And then essentially on an outbound perspective, right, if that appointment doesn't book because the goal of the inbound agent would be to essentially get through vehicle of interest, identify trade, opportunity, finance interest and then uh, ultimately book the appointment. Um, and also that, that doesn't matter if it's from autotraders. As soon as it hits a CRM or if it's an inbound call, the agent can work that inbound. On an outbound, it's going to work that first quality response. It's going to maintain brand voice, um, tone, uh, the important things that matter for the continuity of that brand presence. And then of course just work out outbound, sms, email and um, of course outbound voice as well. And I'll explain how we um, handle that from a compliance perspective as well. But uh, in terms of timing, let's just talk about from sales timing. Then I'll switch over to fix ups. Um, you know what I always recommend dealers is 90 days. We've um, seen dealers go from first, uh, start to like record months in 90 days. And um, and I call this the first time to first value. It's one of the, it's one of the KPIs that matters. I mean this predicts whether or not your deployment will survive or it'll fail. Um, and I think that most of the dealers want to hear that it's going to start right away. It does. By the way, don't get me wrong, day one, within hours you're going to be booking appointments. There's no question the outbound agent is going to be making calls, booking appointments, but it's going to have um, you know, where it might say 460 instead of GX 460. Um, and this is where we have to understand that the agents learning and I call these teachable moments. And we shouldn't focus on the minors, we should focus on the majors. Did we get month one lift? You know, did you do 80 appointments last month? And now we did 96. You know, this is stuff that we should be thinking about. And then month two, you know, did we do better than that? Did we do better than that? Are we closing and then using the humans? And I want to be very, very uh, open about this. You know, we don't believe that AI, uh, you know, should take humans jobs. Humans, um, should. If you were a great salesperson, you're going to be a stellar salesperson if you do this.

Speaker A: Right, right, right.

Speaker B: You should augment, right. Let the AI do the redundant, monotonous work. So imagine all of a sudden now the agent is working all the inbound leads and the outbound leads doing all the texting, SMS at scale, um, we build our own orchestration layer. So let me explain this a little bit. This is very important. We don't use third party tools like you know, um, N8 ends of the world or makes of the World to stitch workflows. That's actually one of our biggest, um, secret sauces. Took us about two years to develop and to get right. But the key is the agents can decide and reason and act autonomously based on context, like you said, um, compliance, guardrails, um, policies and then ultimately you know, the conversations and um, the signals and then it can decide what the next step is. So if John Smith says, hey, I'm interested, can you give me a call Tomorrow back at 12, that agent will look at, you know, are they open, is it Sunday, are they closed? All these different things, right? The guardrails, and then decide, you know, if that's the best move and then it'll make that decision. So you've got agents working your leads 24, seven, um, obviously not calling people or anything like that at midnight because that's the guardrails. Right. Um, and then, and then when they become an active hand raiser, then it pushes it back to the human as an alert and then that's where these humans should be focused, you know, focus on when the agent gets them to the point where they're ready to act, then you engage and bring them in for the showroom. And then dealers that actually follow that um, methodology are seeing incredible results. And on service side, um, if they were.

Speaker A: Albert, before you go to service, I was just thinking something and I don't know if this analogy holds water. I'll let you uh, react but a few times. And I'm not a student of the best super salesman in um, you know, automotive retail, but there have been some amazing people, you know, who are selling like hey, I'm, I'm selling 80, 90 cars a month. And you're like, you know, and then of course I have to ask, well, how are you doing that? It's kind of like um, I have an assistant and some of these people have two assistants. And what they've figured out is the tasks that they're really good at that add value and keep people engaged and the tasks that they're really not good at. And by having these assistants, their throughput instead of 10 or 15 cars a month or 80, 90 cars a month, maybe we should be using that analogy more that the. Right. The sales people who have a vision to do more, to serve more, to grow more, um, can look at AI as their assistance to take care of the tasks that are not adding value and focus on the tasks that really bring value. Um, how does that sound to you?

Speaker B: That sounds like spot on. That's exactly how this should be looked at. AI for the assist. Um, you know, the thing is, is. And I've even coached dealers, right? You know, I think this is something actually even mentioned right now. Um, you know, you'll sometimes get dealers and they'll knee jerk, right? Because maybe the AI is answering the calls and all of a sudden somebody calls in and complains. Ah, you know this, you're using AI whatever, right? And you're going to have complaints. And dealers, you know, they'll get nervous. They'll be like, oh, this is, you know, you know, it's an AI. The reality is this is, of course it's going to get complaints if it's doing 100% of your calls and service or in sales, for example. And a humanizen, you're expected to get mistakes. But, right, going back to what you just said, the response, the proper response to that customer will be like, but you know what, Mr. Customer, Mrs. Customer. We value you so much in showroom. The experiences that we want to provide to you when you walk into our showroom and when you're buying a car here, we feel that, you know what, it's better to have, uh, an assistant, A, uh, digital assistant answering our calls so that we can put all of our time and energy to you when you're here at the dealership.

Speaker A: Come on, let's go. I love that. Albert. Let's talk about fixed ops. For the fixed ops directors or for the general managers who are looking to just get a little better education on what's possible on the fixed ops side. What are you seeing for your customers?

Speaker B: Yeah, um, I think, um, well, there's a lot of things that are happening. Um, first off, let's talk about consumer adoption with AI. I think that's important. Um, these last two years have been really, uh, interesting. Um, we've seen millions of interactions. Um, I think we're just shy of a million plus calls. Um, over 130,000, um, service booked appointments. So we've seen a lot, and I've seen it go from customers immediately. Really, most of the time wanted to transfer to a, uh, human not wanting to talk to an agent to. Now all of a sudden, you know, 70, 80, 90% of the calls are booked with the agent, um, and the customers are happily to, you know, to do that. And I think what's what's ultimately happened is the consumer adoption is to the point where now they're like, hey, my time's valuable. If this agent actually isn't going to be wonky or clunky and actually get me through the process and get me through quickly and actually solve my needs, um, the consumers are okay with it. That, that is, that is absolutely 100. I think to this point there, I mean you might get one out of 30 that might say, you know, I don't want to talk to an agent now. It's, it's incredible, especially if the agents are doing a good job.

Speaker A: Albert, I, I want to piggyback on that. I have so many of my friends, men and women, that are just like, hey man, I'm using chat GPT for everything. I was just talking to a married couple. It's like chat GPT is the greatest thing. Are you using it? You know, so number one, I'm seeing that. Number two, because I like analogies to bring people back to where we are. I'm uh, 64. So when I first started traveling by air, you went to a travel agent and you got paper tickets and you got them mailed to you and if you lost those paper tickets, you were out of luck.

Speaker B: Right?

Speaker A: When the Internet first opened up, the booking portals for I was mostly flying United time were kind of clunky and hard and you would try and you got frustrated and then you ended up calling. Today I am the expert travel agent. I can do multi leg flights. I'm looking for discounts, I'm looking for seats and plane configurations. I don't want to talk to anybody at uh, United or Delta unless I have a major problem. And I wonder if we're in that transition, right, that um, over the last year or two we're throwing up some AI models hoping to solve some gaps. More and more people are working through them. But I still think we're in the early days. And so like you said, dealers shouldn't give up because the revenue lost is invisible.

Speaker B: Yes.

Speaker A: Because you don't know if people are calling, you don't know if people are doing the work. With the AI workflows, you know, the work is being done. So in effect the calls are being made, the emails are being sent, the texts are being sent. Uh, and now for the first time you could see, you know, where maybe your process isn't, ah, scaled properly, but this um, is a time of transition. So what are we seeing in service? What's some exciting news about filling gaps that have been in fixed Ops for a long time.

Speaker B: Yeah. Um, well, first and foremost, I love what you just said about, uh, seeing and identifying processes. Um, and I think this is, this, this spans across variable ops and fixed ops because, um, for the first time ever, right, you have a different set of lenses that you can operate off of as a dealer. Never in the history of automotive. Right. Have we actually had the ability to look, listen, and learn from everything that's happen. Our dealership at scale. Because not only do these agents, uh, take the calls, right, but you're pulling in that intelligence from the transcripts, what the customers are saying, um, why they're transferring, what the transfer was about, um, are they upside down on a trade. You know, you're picking up the signals of, uh, I had a soccer mom the other day picking up her kids, and so you're learning she's a soccer mom. All of that nuance. And so really the technology, the moat, Brian, is not the calls. The technology of the conversations, like the text and the emails and the voice. The real moat is that data intelligence behind it. Yes. The exciting things is that the exciting things is what you can do with that data. The second part of it is, um, having agents, um, that are working together as a team. In the background. Imagine a call comes in. Um, person says, hey, I've got a Tesla I want to schedule for a change in my battery. Um, and said, I want to come in today. Well, that's great. Uh, I can certainly make that appointment happen. But maybe that battery is not in stock. Right? So in milliseconds, you need to have another agent that's looking in the parts, looking for availability, saying, oh, you know what? I don't have that part, but just sent off an order right now, put the order in for the battery to come in. All this is happening on a call where the customer in seconds doesn't realize it. Agent comes back, says, you know, Brian Love, um, to get you in today, uh, however your Tesla battery needed to be ordered. It'll be here, um, Friday, April 23rd. Um, why don't we look at the appointments that day at 8:30 and 11:30, which works for you.

Speaker A: Yeah.

Speaker B: Now you're talking about customer csi, uh, at a whole level. You're not bringing them in there for parts that aren't available, um, you know, setting proper expectations. And these agents are all working together. And then on top of this, this is where I keep going back to that context layer. That's real time signals. So you know what I love about the cdp, right? The CDP is the foundation um, and you and I, we'll talk about this later. But that CDP being the foundation and having that clean data layer on the operating system layer, right, that system action layer, you're picking up real time signals. So now all of a sudden, hey, this guy's got a Tesla. I know. He's got a battery. I know he needs to order the battery. Right. You know, he's at 43,000 miles. There's equity opportunities. All of that is real time signals that need to go back to that cdp. So it needs to make its way to a context graph. It needs to make its way back to that cdp.

Speaker A: Yeah. Uh, and this is why I wanted to have you on, because you have had a jump start, uh, on the CDP world, um, marketing activation. You've been really ahead of the things that people know me to write about. And I saw you were doing all sorts of things with AI and started publishing, you know, dealer success stories. I'm like, no one else is publishing ever. It's like already, you know, through, uh, you know, the trial by fire, you know, getting all these workflows to work together and, and, and that's, that's exciting. And that's why I think, like, in the future, um, at mrc, I think it would be great for us to figure out how do we work on something that really educates the dealers. Like, you know, something meaningful. Like we did the CRM, um, survey, uh, of dealers, Dealers really like that. I'm wondering if we really should be doing some. Almost like an AI playbook, you know, what, what, what should, um, the dealers be thinking about? Like when I publish the guide on CDP is, you know, uh, I think you have a wealth of information. Um, one of the other pieces before we close today, you, you mentioned it. Time to value. When I was working with Telium on the CDP project for Morgan, value engineering was brought up and you know, when dealers normally buy software that's never brought up. And Tealium was very good about, let's set up a plan so we can show you the value engineering. What's important to you, what are the goals and how long is it going to take? And I was like, that's really good exercise. But you, you also brought it up. So you're in an enterprise mindset. Um, I think I want to dive into that a little bit. When dealers ask you whatever your platform costs. And I, I don't think cost is what I'm interested in.

Speaker B: Right.

Speaker A: Um, I'm talking about how do you explain to them the value engineering piece? Like, hey, if you trust me with your engagement layer, with this communication layer, with the agents that we've built. You mentioned in and outbound for sales and service and parts and uh, warranty and recall and f. And I. All the agents that you've built, how do you talk to them about the value delivered for their investment? Right. They have to, you said management has to buy in and the buy in people have to push through learning curves. Um, we understand that this is an ecosystem that is learning and refining and improving over time. What's that conversation normally look like for a dealer or dealer group?

Speaker B: Yeah, um, great question, right? Um, because I think a lot of it is, is discovery, uh, first. Right. Helping them to understand exactly what this means. Because like I said, I really, and Brian, I really want to echo what you said in the very beginning of the call about these stacking tools on top of tools. We're seeing that today and I'm nervous to see what that's going to look like, um, down the road. Um, because I think the unfortunate thing is, yeah, you can get some instant value, right? You can start to see booked appointments. Um, but there's a bigger conversation that you need to be having with the dealer groups and the dealers and that's that that long term isn't going away. Uh, A.I. is not going away. It's here. Right? So, um, we really need to sit down with them and I, I, I like what you said about the operational, uh, mindset because I think that's how we need to be thinking about that from a dealership perspective. We need to be talking about operational maturity. Um, anybody can sell you a demo. Um, but we really need to be thinking about, you know, predictable timelines. Um, you know, what does this look like and implemented with the BDC team? How does this look like with your sales? Um, so we need to sit down and you know, what's important to them, right? You know, when we talk about first time to first value, um, they're counting the clock, right? And they need to see measurable value. So what is that? Measurable value, right? Is that, hey, I need to see my, my appointments booked, you know, going from here to here. Okay, that's fine. Um, do I need to see, you know, my, my data layer, you know, being, you know, uh, more robust and having more signals so that I can activate better. Um, I think all of these AI deployments need to have some sort of, um, KPI matrix and it's, every dealer is different. I think, you know, we start scratch with every dealer and that's the other too. It's, this isn't the. Set it and forget it. Um, I found that, right? You can't just set this into any store and say, okay, here you go, here's your service agent. It's going to answer all your calls and you're set. That's not going to work long term, right? You have to, um, really sit down and do that. So I think the answer is it's every dealer's different, but it's all built off of the same framework. Right? Um, we know that you ultimately have some pain points. What are those pain points? Because just think about this for a second. You have, um, the in service, for example. You now have coverage. You have bandwidth. Before you were bandwidth constraint. You know, Brian, think about this. How many times have we talked to dealers and they just want to buy more leads, more marketing, more leads, more. Because everything comes to bottom funnel. And that's what their sales people can handle. They can get more leads. And more leads ultimately they think means more sales. We, we fundamentally think differently. Uh, you don't need more leads, you need a better process to manage those leads. Right? And so that's, you know, resetting the mindset of the dealership and saying, hey, you now have a tool that can do all of these things. Um, so where is that value? It's not maybe more leads, it's how do we want these agents to work those leads?

Speaker A: How do we, you know, Albert, you, you bring up this more leads, better process. I want to tell a story because I want dealers to remember certain things about our conversation. Until urban science started showing the defection data, dealers didn't know if their processes were broken. And I'm going to come back to that. Just as you said before, AI dealers never knew that their process is being fully executed 24 7. And they could see, yes, if that process is scale tested or volume tested. But let me go back to urban science. When dealers see their defection data and what day the person defected and, and the context for the dealers here, if they don't have this data, it's the most valu data. Um, if a lead is in your CRM, Urban science, as soon as that person buys from another dealership, they're going to send you a signal into your CRM. If you have both sales Alert and Traffic view, they're going to tell you if that person bought from the same, uh, brand and was it a local. So imagine you're a Honda dealer. You think you have your processes locked down and then all of a sudden you see in day 14 through 21, huge defection rates. That is an elite problem. That's a process problem. And then my brother Glenn goes into their CRM and says, yeah, your workflows are really, uh, for the first 14 days you stop in your mindset. You know, your process kind of goes on Autopilot after day 14. And look at all the people who bought from the Honda dealer down the road. This is going to be a beautiful time, I think, Albert, when you are able to guide dealers using data sources to refine the processes. Right. The AI models and workflows we have today are going to change over time. But here's the cool thing. We're going to start to get in these external signals so that we can get better at lowering defection rates. Having contextual messages, as you mentioned, cross department. This is an amazing, amazing time, um, for dealers who are leaning in and saying, this is the first time I heard somebody talk common sense about AI. And um, let's work through the business needs. Let's do a value engineering, you know, timeline. What's the best way for them to get in touch with you or, or visit your company website? What's that? URL?

Speaker B: Yeah, thank you, Brian. I appreciate it. It's www.id privacy. Um, just like your ID. It's actually. And by the way, I'll take an opportunity to say this. Intelligence data, private focused AI. Right, that's it. That's not id, like, uh, a driver's license. Intelligence driven privacy AI. Um, so it's id, Privacy AI. Um, and that's where they can find, um, uh, find us or.

Speaker A: And what if they wanted to send you a direct note, Albert? How do they send you an email now?

Speaker B: Yeah, Albert, A L B E r t@iv privacy, uh, AI.

Speaker A: That's so easy.

Speaker B: All right.

Speaker A: There's so much we're going to have to put, uh, our heads together because now that DMSC is over, we are going to set our sights for November for modern retailing. So why don't you put your head together on what you think dealers need most to help them navigate through the AI transformation of their business and to avoid some of the potholes. And then, um, let's work to, uh, do a presentation in November. How does that sound like to you?

Speaker B: I think it sounds fantastic. Uh, Brian and I want to leave you with this, um, because, uh, you know, I know we're coming on time, but the last piece here that we just touched on, this defection piece is so important because if you actually think about it, um, and this is A learning lesson and it's a very exciting time. I did not break your process. I revealed your process was already broken.

Speaker A: Yeah. Come on. And this is the, it's exciting. Now I'm. Here's what I'm wondering. I'm wondering when we really get these workflows, right? The, the feedback signals from companies like Urban Science and what we lost. Um, what, what's the limit to the conversion rate of lead to sale right now? You know, dealers will say, man, we're crushing it. We're doing 17%, you know, lead to sale. Um, you know, 35 appointment to sale, whatever their, you know, their stats are. Um, it's amazing what the future could be like. I, I wonder only can guess what it could be.

Speaker B: Well, we just did, uh, we just did an OEM case study. I won't say the om. I'll see if I can get permission to get you that, but we did an OEMK M study. Tier one. We managed all the tier one leads. The agent gave 30 minutes to the dealer for the first 30 minutes to respond to the lead. Um, from, um, our agents took over. Right. And what we found in this particular OEM m. Now everyone is different in this particular one. It's a, you know, compact, you know, economical, um, you know, oem. But leads would come in, consumers would engage day one. And then there was about 60 to 70% of this audience that would just stop, stop engaging agent would follow up, follow up, follow up, follow up. About six to seven weeks we saw 40% of this audience re engage out of nowhere. And then in about two to three weeks, purchase. So there was a lag of about seven to eight weeks from four weeks of zero interaction. 0re engagement touched once. Seven to eight weeks later, 40% of this group would actually then come back and they would buy. And when you were able to extract the data signals from within came down to pretty much one thing. That particular audience was liquidity constraint. They everything came back to, um, I'm getting a bonus, I'm waiting on taxes, I'm waiting on money to come in yet. They started shopping in Thanksgiving.

Speaker A: Yeah. What a, what a great reminder that with AI we don't have to worry about an agent getting tired or burnt out or quitting. Um, especially with some of the third party tools, even uh, data from companies like Client Command that can see people when they're back out shopping. Feeding that into an AI model. I mean there's so much, yes, so much in the future. It's going to be awesome. Albert.

Speaker B: Yes, sir.

Speaker A: Uh, CEO ID privacy. AI Albert, thank you so much for being on our podcast. And now that DMSC is over, we need to be providing clarity for dealers who want to, uh, upgrade their tech stack and leverage AI, but do it in a safe way. We'll be talking more of this with future shows and getting ready for mrc. Thanks everyone for watching. Albert, thanks for being on the show. And finish finish the month strong because we're going to help you sell more cars in a digital age. Thanks.

Speaker B: Congrats.