Wally Burchfield, Automotive Industry Expert on AI and Consumer Data 

Wally (00:00):

Things like telematics have advanced quite a bit and to have a vehicle deliver on the brand promise and better quality, because all of that data analytics and the AI crunching it reduces the amount of recalls on a car. How many more consumers do you satisfy? How much safer is a car? It runs really wide. So, I look forward and say, if we're gonna take that kind of technology, or we're gonna use that data crunching power, which is the question I always ask is is why does it burn so much energy to do that calculation? Because that's what you're seeing. You're seeing competing industries looking for data farms and manage either EVs or AI.

Jim (00:43):

Welcome to What If? So What? the podcast where we explore what's possible with digital and discover how to make it real in your business. I'm your host, Jim Hertzfeld, and we get s**t done by asking digital leaders the right questions. What if, so what, and most importantly, now what? Hey everyone, welcome to What If? So What? I'm really excited to have Wally Birchfield on the podcast. Wally, welcome.

Wally (01:05):

Thanks, Jim. Excited to be here.

Jim (01:07):

Well, you've done a lot. You've been around, you've seen some things, but long career in automotive and a lot of sales and marketing, and I've just learned today HR. You really have done a lot of things, but tell us about yourself, how your kind of career got you to this point.

Wally (01:20):

Sure, let me just share with the audience. I mean, I've been in the business really since the late seventies. I started in retail, ulti. I maintained a role for them and ran Nissan United, which is the conglomerate that runs all of their advertising, media buying, and partnerships. I went to work for General Motors in a lot of different positions. GMAC, sales and marketing. Ran some regions, spent time in Canada running the insurance operation, swung back through, ran senior staff for a number of years, was around during the Keep America Rolling campaign, which a lot of people might recognize that from 9/11. We just finished celebrating that last week. Shuffled over to Nissan. Nissan recruited  me away in 2007. Ran a couple of regions for them, all sales and marketing and after sales, senior leadership in both companies ran HR for a bit. Big chunk of HR for Nissan as well as you, as we just talked about a lot, a little bit. And then I ended up taking on a bigger role in advertising as I left Nissan in 2018. I maintained a role for them and ran Nissan United, which is the conglomerate that runs all of their advertising, media buying, and partnerships, sponsorships.

Pretty diverse career, I would say all around the three legs of the stool of the business. I'm not an engineering person or a manufacturing person, although I understand it, ran North American Motor operations at one point for GM. So I understand quality and telematics, but really been blessed with the three legs of the stool. How an automotive company makes money. You know, you build a car, you sell it to a dealer, sells to a consumer, you finance the car, you take care of consumers, you, you focus on the journey, what their experience is like a lot of time with dealers, both in the field and headquarters, all the legs of the stool of financing and selling repeat business, right?

Jim (02:54):

Do it once, do it again, do it again. And again with customer for life. Excited to have you on here. Just have that, I love kinda diverse perspectives for anyone, you know, sort of dealing with technology, dealing with digital technology. Dealing with AI today really helps to have a broad perspective and a lot of lessons learned, which we don't have to go into all the lessons that you learned, maybe <laugh> Sure, definitely want your perspective on a few of those. So, you mentioned then when you started, you know, your career, and maybe today that it's straightforward, right? We build the car, we ship it out, we finance it, put a driver in it and repeat. And for the OEMs, the manufacturers, you know, they have to deal with a lot of the same things. You know, keeping the dealers happy, keeping the incentives, correct model year, change out, all the advertising that goes with that. But, you know, there's like a lot of businesses because of digital technology, because of the proliferation of data. And you mentioned telematics, you know, we've, we've really changed the, and focused on the experience, the experience of the driver, the passenger. You know, we hear a lot of OEMs talk about mobility. You know, it's not really a manufacturing company. We're a mobility company, does the rise of autonomous vehicles and so forth. But what is it in your mind, having seen a lot of these changes and impacting different layers of the business, what do you think has really challenged or changed the industry as, as you've seen it most recently?

Wally (04:18):

Yeah, it's, it's a great question and to your point, you can, you can always summarize things in just simple words and say the internet. The reality, I would say, given all those years of experience in the different parts of the business, and, and again, it applies to a lot of industry verticals, not just automotive, is the consumer and the data around the consumer that supports their experience. You know, whether it's acquiring a product, in this case we're talking automotive, but it doesn't matter how simple that is to do the quality of the product, how the company interacts with that consumer. And it's driven by data and it's driven by their respect, consent with that consumer. Can I talk to you? You know, there's lots of rules and regulations around that. I would say data. And that's where technology comes into play. You know, whether it's technology through the car technology and the big data platforms, again, it applies to a lot of industry verticals, not just automotive, and everybody has a different idea. Everybody has a different strategy and that keeps the market competitive of how we interact with our consumers. Again, doesn't matter the industry, doesn't matter the industry, it's how do we do that? How do we respect that consumer and value their time, value their choice to do business with us? How do you do that?

Jim (05:28):

I hear this all the time. I need hyper-personalization. I need one-on-one personalization. Is that really necessary? You know, do you need to know everything about a customer or prospect, or is there sort of a sanity check there in your mind?

Wally (05:42):

That's a great question because the industry at least, we’ll focus on automotive for a moment, but you could say the same thing for others. People use words like AI, or the two letters – AI. They use words like hyper-personalization, they talk about one-on-one. Those are more marketing industry kind of terms that talk about how do I talk to Jim and do I know too much about Jim? You know, does that help me craft an interaction with Jim that Jim is excited about? When you talk about hyper-personalization, and I'll pick on auto for a moment. If we're searching for a product - let's say we're searching either for a service on a vehicle or to buy a vehicle. Today in the internet world, right, everything is in the internet world, although signals just snowplow, all these different companies coming at you. And we all know that. And take any device you use, the more a company can serve you exactly what you're seeking, the faster and the more crisp that experience gets, and so that can be considered hyper-personalization. That can be considered one-on-one. To your point, look at the insurance industry and I'm, I won't throw names out, but a lot of 'em will snowplow heavy advertising because we're the best, we're the cheapest, we can do this. And they just are trying to catch everybody with a big net. At the same time, if you want efficiency and a consumer wants a personalized experience, and I do think consumers want that. They don't always raise their hand and say, talk to me one-on-one, Jim. But if a company in servicing and trying to capture and retain you as a consumer delivers that to you very concierge, like well what does that mean? Well then Jim steps into the relationship and that relationship then becomes one that you can retain. because It is important selling a product first and then retaining the consumer through a high quality experience for the next repeat if they need to buy that product again. That's critical because the more you do a good experience, the lower the cost of acquisition of the consumer like you have to pay the first time.

Jim (07:45):

Yeah. Well that's like trust, right? Trust takes years to build and seconds to lose, right? And so you gotta get it right. I mean, do you see brands that they have more data? Is it fair to say that brands have more data today about their customers than they did five years ago? It seems obvious, but maybe the data isn't that clean, maybe the quality isn't there. How would you react to that based on kind of what you're seeing?

Wally (08:08):

It's a great kind of poke into what is the right data, how much do you need? And then how do you use the data? I do think big brands, big industry verticals have more data and I think an AI platform allows them to digest and use the data at an accelerated rate faster than a lot of human beings. I think they have more data. I still think there is a significant challenge in having, and I'll just throw out the word, a truckload of data. <Laugh>. How do you really use that to meet Jim's expectations? And when you get down to it, if you can crunch the data, if you can leverage the data in the right way, you know, you can deliver the consumer the experience you want, you know, and consumers have to agree. It's kind of interesting to listen to people talk about subscription services in vehicles and where that takes them, right?

Yeah. Am I selling my data? Is there a consent? I mean, all those things go across this whole waterfront. But yes, there is more data out there. And I would say your big, big data companies, your data broker companies, are accelerating at what would be called identity resolution. So, who is Jim? Who is behind the device? Is it your laptop? Is it your phone? Is it your tablet? And you're using all of those different devices to interact with a company. You know whether you're looking for insurance, credit card, buying a car, looking for a service. And it's then how they use that data, how do they use that data to serve up an experience for Jim that makes him wanna do business with him? Grows. Trust your point earlier, a lot of times in the industry we talk about convenience, value, and trust. You always hear those three words together and trust is the hardest thing to build. But building trust, you, you have to; people will go past convenience. If trust is higher, they won't necessarily go past convenience just for value. Sometimes they won't just chase the dollar, right? So those are kind of interesting. Trust is number one. Trust is number one for sure.

Jim (10:10):

That's good to hear. And trust I think is back, I would say back in the news, it's back in the dialogue just with AI.

Wally (10:19):

Oh, totally.

Jim (10:20):

Maybe not so obvious reasons, but you know, am I getting the right result? Is it, you know, is it, it's a two-way street, right? Am I, do I trust the results? Do I trust the direction? Do I trust the response? And, you know, can I trust the provider of the platform with, with my data, with my information? You know, what are you doing with it? With my own privacy, with my own proprietary content. There’re some rough stories out there right now. So, I think good, good to keep in mind. And again, just keep reiterating the value of trust every day. Integrity, you know, is another one. Can't lose sight of that. You know, when it comes to this, you mentioned by the way, couple visuals, truckloads and snowplows. So, I have this sort of visual already. There's a truckload of data and there's a snowplow of data put be pushing data around. So, with all this out there, with these trucks on the road, we're just gonna keep this all automotive.

Wally (11:09):

Okay, that's fine.

Jim (11:10):

So, you got the road, you got the trucks, you got the snowplows, and you got data everywhere. It's like a bad winter in Michigan. <Laugh>, what are sort of the key challenges that, that you see? You mentioned trust. You and I have talked before about incentives as well, and you know, where are the incentives for me? So as a brand, you know, what are my incentives to use it the right way? I get that use case, that interaction. You know, do I choose the right one? Do I use not just the, choose the right data or handle the data properly, but am I gonna use that in the right way to deliver the right experience and not turn off the customer? What is some sort of challenges or risks you've seen? Maybe some good, the good, the bad, and the ugly and, and how data was used or misused, or maybe created some unexpected outcomes?

Wally (11:56):

Yeah, I mean, it's a great question. And there's a lot to unpack there a little bit. We'll go on the negative side first where people break that trust. And so, there's current litigation across the country. Won't, won't get into, people can go explore and look it up. But in a data world where companies use data the wrong way, they contact the consumer the wrong way. You know, in the old days, and again, I'm, I'm old. So, the old days of buying a car was bait and switch, right? You brought people in and I thought I knew you, and next thing you know, well that car's not really on the lot anymore. Buy this one. All those kinds of things, those are examples of how data can be used wrongly. Not only how it's collected, but how from a marketing standpoint, thinly disguised kind of motivating and pushing people to take a step.

And, and you lose trust, right? People will figure that out. People feel like, you know, they're getting bombarded by robocalls or whatever those are. And there's some good regulatory stuff that's in place at a state level and a federal level. And so, your best data companies are really good at filtering through that and making sure no, they're hyper compliant because you've got to value the consumer's consent. What I think sometimes we don't understand as consumers is when I do an event, if I sign up for an event, I've, I've agreed to do a lot of things. Do I take the time to understand they can reuse my data? So as, as in consumers paying more attention and being educated around how do I want my data to be used is important because in the speed of the technology world we're in, we have a tendency as human beings to rely on speed and convenience.

And it's fast, and it feels good. And kind of as human beings, we have low patience, right? And so we accept things and then later on we are not sure why something's coming at us. We're not sure why we're on some mailing list. Well, you agreed three weeks ago that that was okay. On the other side, I think there are major brands and, and you can see in, in their results not only their financial results, but consumer, you know, consumer reputation, you know, things like that. Because of how they really value trust. They, they value consent, they value that you're gonna give me a good experience because I've shared my data with you, right? It's, it's in the marketing world, it's good trade. It's a fair trade. If, if you and I both like the same watch and I'm wearing it and, and you want to buy it, marketing really had nothing to do with it.

You value Wally's opinion and you go buy the watch at the same time. You know, you can do the snowplow marketing where it's just, let's just snowplow a big message out there, and we're just gonna catch whatever comes into the, into the funnel. And that, that's not a bad strategy. If companies want to do that, it's not a very efficient use of media dollars. Not a very efficient use of the consumer's time. Because things stay very generic. When you mentioned earlier, the hyper personalized, the more you can help a consumer understand that. I know you, and I hear you, and I see you; those are words in today's society. People hear those words for a lot of other reasons. But the reality is being authentic, making sure that I understand a consumer's desires and what they want, which comes from data and how you use the data, I can then meet that expectation, you know, and I need to listen to the consumer and use the data in that positive way.

Jim (15:23):

So, while you were talking about sort of making sense of lots of data, and there's a lot of tedium that kind of goes through that. And I was talking to somebody last week about a very tedious activity where they had to sort through a bunch of entries and, and we talked about using AI for that. You know, like, well, there's a lot of, I've got reams of, of, of information. I gotta make sense of it. It's gonna take me at least a week to do it. And so, I suggested AI. They weren't, hadn't quite taken the leap yet. So <laugh> so we constructed a prompt that I think was gonna turn this into a 20 minute job. I'll have to follow up with her later. But it, it begs the question then, with the data coming in with the challenge of sorting through, making sense, being responsible with the data feels like a great AI use case for marketing and advertising. Let's just do kind of an AI reality check. So you're, you're in the middle of it, you've seen it 10 different ways, a hundred different ways, you know, where do you see AI sort of making the biggest impact? Is it automation? Is it creative content generation? We talk about trust and authenticity. Is there a threat there? Just love your take on how AI is shaping the world of marketing, advertising, and from your world.

Wally (16:36):

No, it's a great question. And it's interesting to see even the last probably five plus years, I would say things have moved from machine learning to quote AI and kind of those things overlap. And can technology, in some cases, lift the burden off of the analytics, right? Trying to understand the data and then can it execute? There's a whole wide range. You went from content creation, right? All the way to just, you know, doing things that would be heavy manual labor. Can you speed it up? And, and there's, there's tons of AI that, that works in robotics and things like that. In manufacturing. When you think about just the consumer side of business the consumer side of the industry, again, I'll go back to my comment earlier around data, being able to filter through tremendous amounts of data. And when I say a lot of data, I'm talking like, I have a couple of clients that, or at least one in particular that does 60 billion plus webpage touches a day - a day.

So, if you talk about scale, that's big. You can't do that with a human being. You have to do that through AI. Sure. It's like how do you, how do you use that? And again, if you're thinking about trying to give a consumer experience and understand what they're, what they're doing, it, it can drive the efficiency for marketing. Because in marketing you can do things historically from a very predictive standpoint. And what I would say is, you know, you didn't have AI, but some of your big financial companies would say, well, the average consumer that's doing a 72-month purchase agreement is gonna be ready to buy a car halfway through. Because they're gonna have equity in the vehicle, so they should be in the market.

Jim (18:19):

Yeah, yeah.

Wally (18:20):

There's a big difference between predictive and using things that are behavioral signals. That's where AI can come in and you'll still use AI to do the calculations around predictive, you know, kind of modeling and things like that. Again, we're probably getting into the weeds a little bit there, but the reality is that's what AI does in a goal-based kind of way. Kind of have an SMS platform that interacts with Jim in a way that it can answer all of his questions about service scheduling. And Jim doesn't know that it's AI because it's only texting. And if it answers Jim's questions and it schedules his vehicle for service, Jim feels like that's a good concierge experience. Why would I not continue to do that? I don't wanna phone call. I have no time for phone calls. So, the variety of use cases are vast, right? I do think you still get back to consent, trust delivering on that experience.

So, the consumer says, I will walk this journey with you because what you're bringing to me, it values me, is the end consumer. And then I'm, I'm willing to spend money, I'm willing to spend my time, whether it's my eyeballs, my ears, my resources, my financials, because it, you, you've helped me accomplish something I need to accomplish. It may be a task as simple as buying insurance and doing all the comparisons, you know what I mean? And so, there's a lot of different use cases. So, AI will continue to advance that. I think it's important for the industry and I don't care what it, what industry it is, it's important to always keep the consumer in the middle. You always have to keep the consumer's trust, consent, authenticity, and experience in the middle of how you're thinking.

Jim (19:59):

I think that's still tough today, Wally, because I would love to hear you say that, but sometimes I worry these very operationally minded people who are, you know, again, they're, they're under budget crunches, they're under time crunches. It's, it's hard to do that sometimes. So, I think that's, it's a good reminder for everybody because, you know, it's really easy to get caught up in, you know, I'm stream streamlining my day. You gotta be mindful of the impact it's gonna have on the customer.

Wally (20:25):

Absolutely.

Jim (20:26):

Curve ball question for you, Wally. So, you know, if you look back on all the tough jobs and, and heartbreaks that you've had and things you didn't want to do, things you didn't look forward to doing, and you could, you could go kind of turn back the clock or maybe look at, look at all of those things or maybe look at forward to those things today. Where, where do you want AI to make your life better?

Wally (20:46):

That's a, a tough one. When you think about backwards, there could be a lot of things. Because things have advanced, you know, whether it's budget planning and all those kinds of things. because You're crunching data, statistics, actuarial, stuff like that. Okay, that's there. So, it makes those things easier from a forward perspective. I want AI to help whatever business I do business with, I want it to drive that business to value me. If I'm gonna do business with Jim, I want it to do those things. And it could be in their analytics of understanding what I desire. It can be in how they communicate to me. It can be in what services they provide to me. Not everybody needs in-vehicle subscriptions for things. At the same time, some things like telematics have advanced quite a bit, and a vehicle deliver on the brand promise and better quality because all of that data analytics and the AI crunching it reduces the amount of recalls on a car.

How many more consumers do you satisfy? How, how much safer is a car? So again, it, it runs really wide. So, I look forward and say, if, if we're gonna take that kind of technology and we're gonna use that data crunching power, which is a question I always ask, it's why does it burn so much energy to, to do that calculation? Because that's what you're seeing, you're seeing that you're seeing competing industries looking for data farms that can, can manage either EVs or ai. When you think about it, it's, it's, it's a real interesting challenge and you, yeah, it's, you need more than the normal electrical grid to do that. But I, as I look forward, that type of innovation, it's, it's not about necessarily replacing resources. It's about can I take what the consumer needs or the employee or whatever along those lines and can I give them more time to do what they need to do better because I've provided this underlying service for them.

And again, whether it's quality, whether it's crunching the data, you still need humans and you, and you need humans to innovate and to think and to, of letting business just run fast for the sake of running fast,, and to do things. It can do a lot of things from a data crunching perspective, but I want it to think about meat. I want it to be focused on meat and consumer. And I want that business to think that way. Kind of. We've talked about that all the way through this, this conversation. I, again, I, and I'm with you. I think it is something you always have to guard against of letting business just run fast for the sake of running fast and only focus on the bottom-line dollars at all costs. I would say today, at least in the auto industry because I've spent my whole life here, I've been in the auto industry 50 years.

Those, those folks that didn't do well at that have either had to restructure, reschedule, some of them have gone out of business, a lot of mergers over those years. Yeah. And, and in some cases you can talk about, or you may not have measured it back then, how much of the poor consumer handling and reputation drove that problem? Could you use the data to take care of the consumer better? I would venture to tell you, and this is a long story around the tree, when you're taking a vehicle and other products to market, you do all those pre-tests before you push it into the consumer realm. And you can't stay in the study world forever. You gotta get it into market to make money. Yeah. But everything that comes out of that data will tell you what problems you're gonna have later and how you handle those and how fast you fix that or adjust to that issue affects the consumer and those that do it better than others, win those that are slow to listen and respond lose.

Jim (24:34):

Well, I think you're answering my last question, which was, you know, what can we, what can people do right now to bring that thinking to their business? I think you just answered it. You just gotta, you gotta put the customer at the center and to put the customer at the center, you have to listen, you know, and, and I'm, I'm guilty just as we're having this conversation, I need to listen to you finish your question, but I get excited about it. You can tell my energy around that. I still stay close to the industry that I love because I do think we can do better. I think we can deliver better experiences and it's fun to be a part of that. It's fun to not waste a consumer's time. It's fun to help a company who supports a consumer be more efficient. But you gotta listen to the consumer, you gotta keep 'em at the middle, you gotta keep 'em in the center. You gotta use the tools that can help you listen and respond, accelerate quality, things like that. And that's the differentiator between company A and company B.

Well, I think the question that, it's an old question, you probably heard this before, you know, what do you call a person that wants your product to be better, cheaper, and they want it faster? All that – a customer.

Wally (25:37):

Yeah, it's a customer. I mean, they want all of that, right? I mean, because again, they want a competitive price. They want it to deliver on what they think they need. I do think the consumer at the middle, listening to the consumer, it's fun to see salespeople in a lot of industries and the difference between those that are just pushing products versus trying to educate the consumer and understand what the consumer's needs are and matching those needs to the products or services they sell, you know, and, and it takes a little patience. And again, as human beings, we don't have patience, we just don't <laugh>. And so, it's like, how do you weave that stuff together on behalf of the consumer?

Jim (26:19):

Sounds like it's a never-ending journey. And that's, you know, that's why we've, of course, in this industry, we, we talk about KAIZEN, right? Constant never-ending improvements. So absolutely. Yeah. That makes it interesting. Wally, thanks for sharing a lot today. I appreciate you being on the podcast and good luck out there chasing whatever it is you've been chasing all these years. Keep going, <laugh>.

Wally (26:38):

Thank you. I appreciate it. I love the industry I'm in, and I thank you for your time and the opportunity to share. Thank you. Take care.

Joe (26:45):

You've been listening to What If? So What? a digital strategy podcast From Perficient with Jim Hertzfeld. We want to thank our Perficient colleagues, JD Norman and Rick Bauer, for our music. Subscribe to the podcast and don't miss a single episode. You can find this season along with show notes at perficient.com. Thanks for listening.