"Billion Miles of Data" — How AI Finds Hidden Profit In A Flat Market | Greg Uland, VP of Marketing, The Reynolds and Reynolds
The Dealer Playbook
"Billion Miles of Data" — How AI Finds Hidden Profit In A Flat Market | Greg Uland, VP of Marketing, The Reynolds and Reynolds
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Concept
pricing it as advantageously as possible
They’re talking about changing prices based on what the market is doing right now, not just setting a price once and leaving it. That can help a dealer make more money on each sale.
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doing it in real time
They mean using up-to-date information to make pricing decisions constantly. Instead of waiting days or weeks, the system reacts quickly to changes.
Concept
window stickers
Window stickers (Monroney labels) are the official retail price and equipment disclosures displayed on a vehicle. They create constraints for dealers because pricing and advertised terms must align with what’s printed and what’s legally/contractually represented.
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operationalize the AI
They’re saying it’s not enough to have AI ideas—you have to plug them into the dealership’s actual daily processes. Then the AI can help make real decisions, not just reports.
Concept
inventory
Inventory just means the cars the dealer has on hand to sell. If you manage it well—what you stock and how you price it—you can make more money.
Concept
warranty rate
Warranty rate is how often repairs are paid for under the car’s warranty instead of by the customer. If that happens a lot, it can change how profitable the service department is.
LIVE
I want to ask you this, right?
I think most dealers, when they hear AI,
as of right now, they're thinking chat bots,
some sort of agents, automation,
but from your perspective, what's the real picture
that we should be considering?
Like what should the dealer body actually be thinking
about when it comes to this stuff?
I think the important thing with those types of examples,
though, that can get overlooked is having unified data set,
a unified data layer for your AI tools to use
and to leverage is really important for them
to get it right.
As a marketer, you're the VP of marketing at Reynolds.
Where do you see AI, like I know as a marketer,
with a marketing agency.
There are things I have to reconcile when it comes to AI.
What are those thoughts for you?
What excites you?
What's something that you're like, eh, you know,
how are you reconciling the age of AI in marketing?
When you think about AI or when I think about it at least,
I do think that
one of the things that I enjoy most about producing
the dealer playbook is hearing from you.
The messages that I get of people who are getting
so much value out of the podcast,
applying it to their day to day workflows
and finding a thriving career right here
in the retail auto industry.
It means the world to me.
And you know, one of the ways that we make doing this possible
is through my agency, Flex Dealer.
And of course, in the spirit of providing value,
I think this is a perfect time to head over
to www.flexdealer.com,
to show even further support for you,
my beloved DPB gang.
Right now, if you go to my website, flexdealer.com,
you can get a full free PDF
of my number one bestselling book, Don't Wait Dominate.
And the reason I think it's so special
is that a lot of the topics that are discussed in this book
are even more relevant today than ever
with this surge in popularized AI
and people wondering, well, what can I do next?
How can I have a competitive advantage?
Well, that's all here in this book.
And so I'd love to be able to offer you a free copy of this.
If you go to flexdealer.com,
it would mean the world to me
because that is how we continue to produce this show for you.
I'm fascinated by any time I get to chat with an individual
who sits inside of such a massive mover and shaker
in our industry with Reynolds and Reynolds,
you I can't even imagine what's floating across your desk
and the conversations that you're part of.
But that to me is so beneficial
because it's a vantage point
that few in our industry will ever get to have.
And so I want to ask you this, right?
The AI conversation, it's full steam in our industry.
There's lots of buzz and there's lots of hype.
There's those that are either like all hype
or they're like all zealotry and they're like,
whatever, right?
And here you have so much of a vantage point.
It's almost like I picture you, Greg,
standing on a summit of a mountain looking down into the valley
where most of us are like just kind of looking from street view.
So I want to ask you this, right?
I think most dealers when they hear AI, as of right now,
they're thinking chat bots, some sort of agent,
some sort of automation, but from your perspective.
What's the real picture that we should be considering?
Like what should the dealer body actually be thinking about
when it comes to this stuff?
No, that's a great question.
It's great to talk to you again.
And that's a really interesting visual.
I hope I hope everybody doesn't share that visual that you have.
But when you think about AI or when I think about it, at least,
I do think that what you described,
chat bots, agents, those sorts of things, those do have a place
and they do have value
and they absolutely are creating efficiencies.
You know, you think about just a good, simple, tangible example.
You know, somebody calls a scheduled service appointment
and it's 7 30 at night.
They want to schedule that appointment.
They're doing it on their phone because they're driving home right now.
They don't want to have to remember to do it at 10 30
after they get the kids to bed and get ready for the next day online.
So you have an agent answer that call and, you know,
and I can schedule the appointment.
I think the important thing with those types of examples, though,
that can get overlooked is true access to the data
and the information about that customer, about that dealership,
about the technicians available tomorrow.
So having, you know, a unified data set, layer
for your AI tools to use and to leverage
is really important for them to get it right, right?
Because you don't want that agent to answer the call and say,
yep, we'll schedule you at 8 15 tomorrow morning.
Well, lo and behold, you know, you're planning on waiting
for your oil change, but you're not going to get that car for three hours
because everybody else has an oil change at 8 15 tomorrow.
So, you know, making sure that your your agency, your tools
have access to unified data is really important.
So that's that's the first thing.
The second thing it kind of builds off of that is, you know,
we think about what's possible where we're going.
Some of the tools available today are really
in robust operational use cases, right?
How can we really create giant efficiency gains?
And you think about it, where we are as an industry
and how exciting it is to have these tools at this time
because we're pretty much no growth at this point, right?
We're going to be flat for the foreseeable future barring,
you know, some some odd circumstances that, you know,
we've all seen before and we'll bounce back from if they come.
But things progress as they are right now.
We're going to we're going to be in a pretty pretty flat growth area.
So that means, you know, we need to find ways to be more efficient
if we're going to see if we're going to see growth
and if we're going to see sustained success.
So when you we find those operational areas for AI to impact,
that's when you're going to see these big increases in these,
I think, the biggest opportunities.
Hmm, you've got me thinking about how challenges,
let's say a flat market, how there are going to be two groups of people.
There's going to be those that are looking through it and saying,
hey, there's opportunity here.
There's there's actually a tremendous opportunity to differentiate.
And I'm going to share a story there real quick.
And then there's the other group, which is that it's just doom and gloom,
like crap, we're screwed.
But to your point about this, this ability to.
Know more and or present a better experience for customer
leans into the camp of option A, which is there's an opportunity here.
If the market's going to constrict or contract,
then then there's something to do there.
And I think about this, this is the story.
OK, everybody that listens to the show,
I think knows my one guilty pleasure is a monster energy drink,
peachy keen in particular.
If you see me at a soda con with a peachy keen, don't be surprised.
But it's my one guilty pleasure.
And I roll into a 7-Eleven near my office
and, you know, they always have their deal.
It's like three, you know, buy two, get one free or something like that.
So I buy sex just for the office bridge.
And the guy at the counter says, oh, man, you really like these.
These are a good deal. Do you come here often?
This is 7-Eleven. And I'm like, well, yeah, I mean, it is a good deal.
And you're on the way to work.
He's like, I'm going to make sure that I stock fees just for you,
whether that's true or not.
And but I drove away and I'm like, well, that's kind.
Greg, two weeks later.
I roll into that same 7-Eleven.
The guy not only remembers me.
He says, I ordered a whole palette of these things just for you
because I know you come in and buy six and then I bought another palette
for everyone else. Again, whether or not that's true.
The way it may be a 7-Eleven, Greg, over a monster energy drink that this guy is using.
Again, I'm going to tie it back to what you just said.
He's using first party information.
He's using customer centric unified data information without actually
a technical technical infrastructure to support it, which you guys have
to give me a better experience.
I don't get that when I buy a 100000 dollar truck.
Yeah.
So what are some examples you're seeing from your sphere
of how this unified data feeding into AI
actually can benefit the dealer and create that spread of difference for them
in a moment when the markets are contracting or doing what they're doing.
So let me build off of that example you just gave.
Right. And let me let me say like, OK, so this this clerk at the 7-Eleven
or the owner, you know, whoever you were talking to, he's, you know,
one guy and he knows you and it's a one to one relationship.
He's got that first party data you talked about in his head or, you know, wherever.
But what if he had all these other inputs, right?
What if he knew that based on market conditions
and based on the calculations, he's going to make more.
If he prices these at, you know, buy three, get the fourth free,
he's going to sell a lot more, his margin is going to be higher.
And he knows that, you know, because of demand right now,
if he asks, he'll probably get a better deal if he buys three pallets instead of two.
And so he starts going through this.
And what if he didn't have to do all that, right?
What if he had an agent that could analyze every single particle of data
that he owns in his sphere, he knows everything about the buying conditions,
he knows everything about the selling conditions and that I can dynamically
decide how much to buy that monster for it and also dynamically decide
how much to price it at or what be able to put on it so that it generates
the most revenue and ultimately the most profit possible.
And you can translate that to, you know, a vehicle, right, to inventory
on both sides of that transaction.
How do you make sure that you're paying the least for it
and how do you make sure you're pricing it as advantageously as possible
and doing it in real time, not once a week, right?
And probably not once an hour either.
But, you know, you got the complications, window stickers and things like that.
But, you know, there's some real implications where if we can start to look
at our market in a much more dynamic way, both from purchasing
and merchandising, essentially selling, that opens a lot of doors.
And so, yes, you might not sell another unit because we're in kind of a
flat growth market.
But if you can start to maximize on the edges, you know, you mentioned a
100000 dollar truck, what if it's a hundred and 1000
dollar truck because that's what it'll pull in right now?
You know, you spread that across a hundred vehicles a month and we're talking
about, you know, pretty massive, pretty massive impact.
So, you can start to look at those.
And that's when I mentioned operational efficiencies.
That's really what I'm talking about is how do we operationalize the AI?
How do we leverage AI to help us make the most profitable decisions possible?
And like inventory is a really interesting one.
I mean, you think about service as well, right?
And how do we make sure?
And I think the impact there, there's so many interactions, right?
It's so many transactions in service and each customer pay transaction has an
impact on what your warranty rate is going to be.
So, you know, how do we maximize these across the board?
And there's a lot of opportunity.
But again, it's only going to be effective if that AI has a unified
data layer to act on or to build off up to pull from.
Because if it's operating on its own little data set over here in the corner,
there's going to be missing information.
There's going to be duplicate information.
There's going to be an accurate information.
And then it's going to go do the wrong thing.
And that's not helping anybody.
And that can have pretty big implications too.
Yeah, you'd be like that.
What is it?
There's like some car rental company or something recently.
The agent deleted all of their customers.
They're like, no, I love this because the thing
that's fascinated me most about AI.
Sure, the analysis piece, but going one step further.
Because I think most people are going to say a clot or a GPT or whatever.
Sure.
And they're giving it one piece of data to your point.
Maybe maybe they're doing a CRM export and they're they're saying,
hey, tell me about this.
To your point, though, this goes back to one of the first conversations
I think we had it was on auto collabs and you it somehow came up that
Reynolds prints like a billion miles.
OK, it was like some crazy number.
Was it a billion miles or was like stacked to the moon or?
Well, so I think it was 30 37 feet of paper per deal.
And then I think we did the math on it.
And if you figure 16 16 million cars times 37 feet, whatever that is,
it's basically like enough you had to get to the moon and back or something
like I bring that up because the amount of data.
That no human could look at in their lifetime and then draw conclusions
where AI, the fascination here for me is.
But now that AI can look at that billion miles of data.
At once, understand it all at once.
And to your point, with that unification, know exactly what to do with it.
I just love the possibility of that.
This is such a crazy moment in history that we're living in that today.
An AI, to your point, with all of the access of data that you guys have
can look at it all at once, analyze it all at once, cross reference it
to the nuance of your dealership in your market and your, you know,
the economic drivers, the social drivers, the customer household nuance drive.
Like that to me is such a tremendous feat.
And here we are in an age where that's possible.
Yeah, yeah, it really is.
It really is pretty unbelievable.
And you start seeing this stuff work and you sit back and it's really interesting
because you hear about a flywheel in business and that term gets used
in different contexts, but I see it when we look at AI tools and we start
to see these tools working and we start to see what's possible in the wheels
and the gears just spin faster and more and more
use cases pop up and it's like, well, what if we could do this?
And what if we could do this?
And lo and behold, you can, right?
As long as you have access to all the information.
But like, yep, we can make that happen.
Yep, you know what?
Instead of you spending or having somebody spend six hours pulling
14 different reports and downloading them into a CSV and trying to put them
together and have them formatting issues and then you get in the report
tomorrow morning when it's a day old, you know, I can just get you the
information right now, right?
And so you have that and then you start thinking, okay, well, if you can do that,
you know, what else can you do?
Right?
And these use cases can be piling up and compounding and compounding.
And that's what makes it really exciting.
I think it, and we're the perfect industry for this too, right?
You think about the entrepreneurial spirit inside of auto retail.
And that's certainly the dealers, but I mean, everybody that works in this
industry at their heart is on some level an entrepreneur, right?
Every salesperson out there is chasing the next car.
And that spirit and figuring out ways to get things done.
You know, I think we're the perfect industry to really leverage artificial
intelligence and help it take off and find these use cases because we have
the personality for it collectively, right?
All the people inside of our industry, I think, have the right personality to
really leverage these modern tools to create new ways of doing things.
Let me ask you this then.
There's the possibility side and then perhaps the watch outside.
What are some watch outs for people?
What, you know, because like, I think, okay, maybe this is a selfish question.
I'm so bullish on AI because I, you know, you and I, I'm guessing are around the same age.
So we lived in the transition from print to web hype, from website hype to, you
know, SEO and Digian and all of the different things.
And here we are today.
There's kind of another reset here with AI level playing field.
And in some ways, it's like, we don't know what we don't know.
I'm really bullish on this and being part of it.
But what are some watch outs that we need to consider as of today?
And, and where do you see those evolving into the, into the next, I don't know, six months?
I think those are going to come about as fast or faster than the new use cases that we
come across.
But a couple of the pop into my mind, you know, I think our business, automotive
retail has, has always been, I think always will be to some extent, you know, about
people, then process, then technology in that order, right?
People process technology and whatever that technology is, right?
It can be, it can be an electronic ledger, you know, it can be a DMS, it can be a CRM,
it can be an AI agent, whatever the technology is, it starts with the people, any other
process, and then the technology enables it all.
So not forgetting that, I think is really important, right?
When we find these use cases and just making sure that we have that base, that
understanding, or we at least have that mindset, because we're going to, we're going
to be able to, and in some ways we can today, leverage AI to create the process, right?
And that can help.
But we got to think through it, and we got to make sure it's logical, we got to make
sure it fits the business, customer, and it takes care of both sides of
the transaction.
So I think that's, that's one thing is ensuring we don't lose people process
technology kind of in that order.
The other thing that really stands out to me right now that I don't know, might feel
a little off topic, but when you said the watch outs, it's really in the cybersecurity
arena, the speed with which these artificial intelligence tools can work.
And this is kind of outside of the scope necessarily of sort of the dealership
software and AI world.
But when you used to, we used to live in a world where you get an email and it looked
a little fishy and an email would go out to 100,000 people and a hacker would be
hoping that one of them would click on a link.
And, you know, one of them would and they gain access and they'd do the bad thing.
But in today's world, right, they can send out 100 million emails and different
iterations of it and they be tested in real time.
And, and now even if, even if the email isn't any better, which it will be because
it's being written by AI and tested by AI to see what's, what's going to get the most
clicks, you know, quote unquote, convert better, their click rates going to be higher.
They can send it to more people.
So their tax surface got a lot larger.
And I think just a higher awareness and a higher alertness when it comes to cyber
security is, is a really important thing.
So email is the easiest example.
You know, it's the one that we've all seen and we've all, we've all heard about.
And the flip side of that too is, you know, making sure that kind of if and when
somebody inside your store does make a mistake, you have the tools and probably
honestly, the partners in place to, to help you react in a really, really quick
manner so that you can isolate that incident, isolate that PC and, and get
things remediated and then you're back up and running.
Cause if, if you don't have those kind of partners in place, those tools in place
to isolate it immediately, it can mean a lot of money.
It can mean a lot of downtime.
And, and that's something that to me is just, it's a, it's a scary proposition,
but it's a very, very real one right now.
Here's one I want to reconcile along these lines.
Because, you know, it is early, sort of early.
I mean, early in that we've been developing AI for 80 years, I think
cause 80 years ago is when they first started playing with the early ideas of
this, but early in the sense of like broad adoption or broad scale adoption.
And you've got cybersecurity here.
Like the first thing that came to my mind is, oh my gosh, are we back?
Are we going back to a time when a dealer has to have its own server run on site,
handling all of this stuff?
And if so, then what's the infrastructure around that hiring, you know, hardware?
Are we going in that direction?
And, or cause I think some dealers might be thinking, did, you know, every
time new technology comes out and we promise to lasso the sun, moon, and stars,
it ends up costing me more money.
Are we there or is there a way to reconcile it on the backside and say, no,
yeah, maybe there is some money up front that we're going to have to all consider
spending, whether it's security infrastructure or whatever.
But the backside benefit of this is far outweighs it.
Yeah.
So I think, um, yeah, the question about sort of on-prem and having staffed that
and whatnot, I, I don't think that's where we're going.
You'll probably see, I'm guessing what we'll see.
And then somewhat near future is, is we'll, we'll land on the most effective
way to manage this being some sort of, um, some sort of device in the dealership.
It won't be the server, right?
But it'll be a device that connects to the server in the cloud.
Um, for some applications, most will be just through a browser, but, um,
that there's going to be some sort of, uh, network inside the store that's
going to connect to, to the server in the cloud.
And, and, you know, a lot of the way that cloud infrastructure is built
out today, um, certainly the way that we handle it.
But I mean, a lot of it in general, you know, is it's, it's, it's segmented off
where everybody has their own instance, um, for, for us, at least, where, you
know, your, your risk is truly isolated, right?
And there, there's a lot of ways to go about it, but I don't think that we're
going to see, you know, kind of that reversion back to, you know, on
Prince Armors and, and having somebody to, to manage it on site and all that
type of stuff.
I mean, it'll be an option for a very, very long time.
Uh, don't get me wrong.
And it's one that, you know, can certainly be supported, but I don't
see that as necessarily the future.
Got it.
Okay.
Now, as a marketer, right, you're the VP of marketing at Reynolds, right?
Where do you see AI?
What, what are some things you've had to kind of record?
Like I know as, as a marketer with a marketing agency, there are things I
have to reconcile when it comes to AI.
What are those thoughts for you?
What excites you?
What's something that you're like, eh, you know, how, how are you reconciling
the age of AI in marketing?
Yeah.
Well, we were just having a conversation last week with our team and, you know,
it's, it's overwhelmingly positive the way our team views what's possible.
Right.
I mean, and if you think about, you know, people are in their job, whatever it is,
we'll use marketing as the example, because that was the question, because
they really like doing certain things, right?
There's a lot of people that really like to write.
There's a lot of people that, that love doing design work.
And there's a lot of people that, that love doing video production.
And they're really good at it.
A lot of, in a lot of cases, because they love it, right?
And it's a two-way street, but, but for all of us inside of our jobs,
there's things that we have to do that we don't love, right?
We may not hate them, but we don't love them.
There are those things that they got to get done.
It's part of the work, but, you know, it's repetitive.
It's not, it's not at the top of my list every morning that I'm like,
you know what, I get to do X, Y and Z today.
I'm so excited.
And we can start to leverage, in many cases, AI tools to help us
with those types of things, right?
So we get to spend more time, more energy, more effort on the things
that A, we're really, really good at, and B, that we really love doing.
And our output ends up increasing because some of that minutia
that we don't like doing, takes a lot of time.
We have tools that can handle it for us.
So there's a million different examples of that.
But that's what I think we're most excited about.
At least our team is the opportunities that are there to really focus on
those things that you just, you really love to do.
And it's different for everybody.
But if you could focus on those things, and you're good at them,
and you're quick at them, and you can kind of offload some of the other pieces,
your output's going to increase, you can be more efficient,
and you can be more effective.
Well, thank you.
You've talked me off a ledge.
No, this is fantastic.
We've talked about unified data.
We've talked about the possibilities.
We are living in the greatest time ever to be on this planet.
I don't care what anybody says.
The possibilities are endless.
I thought they were endless with Web 2.
And now here we are with artificial intelligence and everything that's possible.
Greg, how can those listening and watching connect with you?
You find me on LinkedIn.
You can also check out our connected podcast.
We got to get you back on connected.
Michael, it's been like two or three years, I think.
But every other week, we put out a connected podcast.
And a lot of great guests always love that.
So always have a connect there, or like I said, on LinkedIn.
Greg, thanks so much for joining me on the Dealer Playbook Podcast.
All right, thank you.
Thanks so much for joining.
About this episode
Dealers aren’t getting AI wrong because of the tools—they’re getting it wrong because they’re thinking “chat bots” instead of building a unified data layer. Greg Uland explains how AI agents can handle after-hours service appointment calls, but real value comes from true access to customer, dealership, and technician data. The conversation connects AI to operational gains in a flat market, faster reporting, and even real-time pricing decisions—while also flagging cybersecurity and the need for isolated risk in cloud setups.
Original notes
Are you leaving money on the table in a flat market? While some see limited growth, others are leveraging technology to find profitability others miss. The key isn't working harder, it's working smarter.
In this episode, Greg Uland, VP of Marketing at The Reynolds and Reynolds, reveals how unified data and AI can transform your dealership's operational efficiency. He breaks down how AI goes far beyond chatbots, tapping into every data point to maximize profit on every single vehicle and service interaction.
What you will get from this episode:
- Understand how robust AI provides a competitive edge in today's no-growth automotive retail climate.
- Discover how unified data is the non-negotiable foundation for effective AI strategies that impact your bottom line.
- Learn how to identify hidden profit opportunities in your inventory, F&I, and fixed ops departments.
- Gain insights into reconciling new AI possibilities with the "people, process, technology" mantra of dealership leadership.
- Anticipate future cybersecurity watch-outs and infrastructure considerations for AI adoption without fear.
Greg Uland is the VP of Marketing at The Reynolds and Reynolds Company, bringing a wealth of knowledge on automotive technology and data integration.
Follow The Dealer Playbook so you never miss an episode.
Timestamps
00:00 Dealers and AI Reality
00:18 Unified Data Foundation
02:18 AI Beyond Chatbots
05:01 Flat Market Efficiency Play
08:41 Dynamic Pricing and Inventory
12:50 AI Flywheel Use Cases
19:33 Cloud vs On Prem Future
22:01 AI in Marketing Workflows
24:36 Connect and Closing
The Dealer Playbook
Michael Cirillo
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25:21