From Data to Intelligence: Marketing’s Next Chapter with Kurt Ruf

0:00

Welcome back to Under the Brand, where we dive deep into the minds shaping marketing’s future. I’m your host, Valerie Jennings, and today we’re going way beyond the buzzwords to talk about what really powers performance in this AI-driven era: data intelligence, and the people bold enough to lead the evolution.

0:26

Joining me is a true pioneer in data-driven marketing and applied AI, Kurt Ruf, the founder of Ruf AI and former partner at Ruf Strategic Solutions. For decades, Kurt has been ahead of the curve, helping brands like Royal Caribbean, tourism boards, and major advertisers tap into psychographics and predictive analytics long before it was really trendy.

0:50

Today, he’s on a mission to revolutionize marketing once again, this time with AI. Through his proprietary multi-graph identity platform, Kurt is transforming CRM systems into engines of precision, delivering 99.9% match rates, and unlocking new frontiers in personalization, targeting, and ROI.

1:12

We’re going to talk about his journey from building and selling Ruf Strategic Solutions to launching Ruf AI, what it means to thrive or die in an AI-first world, and how marketers and brands can actually win with data, not just collect it.

1:29

This episode is a must-listen for anyone serious about the future of marketing, whether you’re an agency owner, a brand strategist, or a CMO navigating the shift from dashboards to real-time intelligence. I’m so excited to dive in.

1:44

Kurt, thank you for being here. You have such an extensive background in data and marketing, and you’ve been on the front lines of this evolution. But I want to take it back to the beginning, to the early days at Ruf Strategic Solutions. What problem were you originally trying to solve when you built the company?

2:11

Well, thank you for the intro. We were really early in translating raw data into actionable marketing intelligence. I have a few mentors, and I’d like to do a separate podcast on the people who got me involved in this many, many years ago — a college professor and my father.

2:31

But from the standpoint of just database work and doing what is now called AI, we were at the very beginning of all of this, to the point of offering cloud services and modem access to our database service bureau.

2:46

What we did, though, is we evolved. Our core goal is to help bring knowledge and intelligence out of data, because data by itself is just meaningless. You just drown in data. So we went from clients trying to guess what their data was telling them, to giving them decision-based data analytics that helped them understand how to filter and how to communicate to the right person at the right time.

3:20

We saw that brands, especially in tourism, were using just broad strokes to everyone, and we were built to fix that. We were introducing audience segmentation and consumer clustering at a time when household and individual targeting was still novel. No one was doing that.

3:40

Our job was to make the invisible visible — to map behavior, to help understand lifestyles, especially in the travel industry. Who is an adventure traveler versus who is coming for the museums? And then to determine what their intent was down at the household level, so they could be communicated with and actively convert to a customer.

4:03

I just want to recap this for our viewers, because we’re talking about 20 years ago or more, right? You were already doing this with data. People didn’t have AI. They didn’t even have social media at that point. It was a time when you were basically guessing unless you had data. So you were so early with data, targeting, and personalization.

4:39

If we look at that scenario from 20-some years ago, how did you sell this product to your customers? How did you get them to understand it? We’re talking about a time when we were doing maybe impressions or views, or, like you said, broad brush strokes that aren’t always going to get us to the bottom of the funnel to convert. So how did you explain this to them?

5:07

Well, in the early days, our core partner was Experian, the credit bureau, and we were their back office doing all their analytics. And if you can’t trust a credit bureau, then who can you trust? Because of that background, clients would send us their data before we could even get a customer data agreement signed, because they wanted to be ahead of their competition. They knew that we knew what we were doing, because the biggest credit bureau in the country was reselling our solutions.

5:38

So much of it in the data world is a trust factor.

5:43

Yes. And then once you’re able to show a client that you can get information and the match rates of their data, and then understand it and give them just a few tidbits before they’ve even had a contract with you, they see it and they want the rest of it. They realize they don’t want just a small amount of the intelligence. They want it all.

6:04

Right, so you had instant credibility as a pioneer in data. So what did dashboards look like back then? Now everything is a dashboard for this and a dashboard for that, and you have all this visibility. How did you present that information back to your clients?

6:29

We were way early in the game of being a cloud provider, which we were. We were way early in the game of being a business intelligence provider, which we were. And we were a database provider before Oracle even existed.

6:38

So what we did for dashboarding was just ask clients what their key performance indicators were, and we would focus on the top three. It might be their response rate, or their conversion rate. Way before digital, we were working primarily with clients doing direct mail or outbound and inbound calling.

7:02

You really just want to be able to log in in the morning, just like you do with the newspaper or with digital news, Google News, and see what the headline of the day is — except with your data. And that was highly valuable, because they could drill in.

7:20

We were able to show not only what their customers looked like, but all of the touch points that led to their customer conversions, and also the factors that led to cancellations or churn. When you understand all these different marketing factors, the dashboards were meant to help you understand the things that create efficiency and give you improvement. And it’s not only for the chief marketing officer, it’s for the CEO as well.

7:44

Right, Kurt. I can’t resist sharing that we used to work together a long time ago. I would say it was probably over 15 years ago that my agency worked with your agency. And I actually remember getting your case studies from your marketing coordinator with all the analytics in them.

8:06

We would take those case studies with all the analytics and pitch them to the industry media. I still remember to this day going around New York and meeting with the editors and pitching your case studies 15 years ago. Back then, people were maybe just getting educated about the power of data.

8:38

And whatever we did together, you would always ask me what the KPIs were on it, and my answer would always be, “This is PR. There aren’t any KPIs.”

8:47

Now, as you know, you can measure PR and social media. But we were early in many industries, not just tourism, but in financial and banking and gaming. We were one of the first companies to bring in gaming data to do analytics, and the same with the timeshare industry, the credit card industry, and automotive.

9:15

We were one of the very few to start doing data and analytics for large auto manufacturers. Once they learned what was possible, they started building 100-person teams internally, and then we would train those teams, and they would do that on their own, and we would be just an outsourced service bureau.

9:30

In the past it was more static and more printed reports. As we started going more to dashboards and helping them find lookalikes using a really large database like the Experian credit file or other data sets, that became the revolution. It’s one thing to know who your customer is. It’s another thing to know how to find more of them.

9:55

Yeah, exactly.

9:57

And target them with your messages.

9:57

So I want to pivot a little bit to building and selling Ruf, because I think that happened a couple of times, and it would be nice to get a little bit of inside scope on what the building and the selling looked like. You can spare us any political drama with the brothers.

10:21

But I would love to hear a little bit, because I also think this is very timely right now. Right now agencies are merging, they’re consolidating, they’re selling, and some agencies are going out of business. A lot of the reasons are pointing at AI, and we’re in a very disruptive era of marketing agencies and ad agencies.

10:48

So I think your experience is very timely to what’s happening right now, especially because you were on the forefront of data. Maybe it’s not all data now, it’s AI, but it’s kind of superpowered data. Here we are again experiencing a lot of disruption. Some agencies are going to rise to the top and some are going to fall to the bottom.

11:12

So what kind of insight can you give us about growing Ruf and selling it, and do you have any advice for people that are trying to scale or transition during this time?

11:30

Yeah, sure. Early on we started doing a lot of work with hedge funds. Companies that were buying other firms became our clients, because they wanted us to do analysis of the target firm they were buying. We would analyze that customer file and give them the lifetime value of that database.

11:50

That would really be what they would call the asset value, because they didn’t know what the value of that customer file was worth for a direct mail firm. And then as these firms that were buying and selling companies saw the value that we offered, they were offering every year to try to buy our firm.

12:05

So we sold early, in the mid-’90s, to Discover Card, and for five years we became a subsidiary in the card industry, building all kinds of loyalty card models and de facto credit scores, or trust scores if you will — who will likely pay their bills, not necessarily like a FICO score.

12:29

We then bought the company back in 2000 and rebuilt it. They weren’t going to let us use all these algorithms we had on the shelf for the card industry; they said we can’t compete. So we chose the tourism industry as our target industry for the next 18 years, and then we sold to a Fortune 500 called Verisk. They’re primarily in the insurance industry.

12:53

Actually, our old website, ruf.com, still leads you to that site with all of our tools and all the platform of data. The same value statements are still there, and a lot of my team members, including my brother, are still over there.

13:10

I transitioned out of the firm and got kind of a sweetheart deal on access to the data, and basically I’m looking to build the firm on a different value statement. And then of course everything continues to be for sale. Everything’s for sale all the time.

13:28

As you find clients and investors and value, and people see value, it’s one thing to work with a thousand clients. It’s another thing to work with one really big one that wants to own you. We’ve been through multiple of those, and I don’t know if I’m interested in that right now.

13:48

The key value that a typical investor sees in you is going to be your experienced team. Our team members are really the highest value, because you spend so much time training people to understand analytics and AI and database. We were built around flexibility, productivity, and adaptability, but you can’t find very many resources or people like that.

14:14

You can build all the AI agents you want, but you still need people who have the experience of the past to know which direction not to go.

14:25

Technology changes, so do clients and the formats, and the companies that win are the ones that have the ability to be adaptable and flexible — not so married to their tools, but solving problems. That’s what made the mindset of Ruf Strategic Solutions possible.

14:40

And that’s why in my new firm, Ruf AI, RUF.AI, we’re going to be a transformation partner, not just a data vendor. We’re more data neutral now, and more platform neutral and CRM neutral, versus offering all those services as a service bureau.

14:57

Right. Well, let’s talk about an industry that we both love, which is tourism — specifically psychographics in tourism and beyond, and how segmentation has reshaped destination marketing. You were using advanced segmentation for tourism boards long before agencies were doing it. How did that change or disrupt the destination marketing industry?

15:37

One of the advanced things that we did early on that really helped change the tourism industry, I think, was that we became members of the tourism marketing research organization, which my brother is still on the board of.

15:51

We did groundbreaking studies where we got a lot of partners to cooperate and share data with us as the neutral arbiter. We call that kind of co-op marketing, but it was the ability to bring in data, create a novel approach to do the analytics, and then help all the partners around that. That was one of the big changes.

16:17

We also did groundbreaking work with lifestyle data related to travel. For instance, who has passports and who will likely travel by air versus ground? What mode of travel will they take, how long will they stay when they get there, what brand of hotels do they like, and what is the economic impact that their family can provide to that destination?

16:42

A lot of these calculated data points that we could build were way ahead of their time. We had built a whole variety of propensity-based data sets working with the airline industry, and we had origin-destination data. So we already knew factual data around who would travel from which airport to another airport.

17:01

We used that to build models to help estimate the lookalikes of the people who were already flying to those destinations, so you could find more of those. And then the destinations wanted that data, because we taught them how to create value with it. The reports that they could show the governor on the value of spending money on marketing became self-evident.

17:24

I wanted to add a little color to this discussion about what we’ve witnessed as an agency working with tourism and luxury destination marketing brands. Ten years ago it was super easy to launch a new business. You’d put up a website, you’d run some ads, and turn on some other display or whatever. Really easy.

17:54

And voilà, you’d have a business, you’d have customers, and it was pretty cut and dry. It is so complex in this era of marketing — and not just because there’s more competition, but because the behaviors of tourists have changed with social media.

18:11

There are a lot of younger people who want luxury experiences with their travel, and they are persuaded by influencers and their peers, Instagram, TikTok, and so on. We’ve had some recent experiences where startup tourism brands have approached us and thought it was going to be really easy to just throw a lot of ad dollars on Meta and Google and get people converting on a booking site.

18:50

But when we looked at what they had spent and what their conversions were, it was really pathetic. And they thought they knew who to target.

19:04

So I go back to this data and what you were doing early on. I feel like right now, in this era of marketing, it’s even more critical that there is real data paired with persona models, with the right type of creative being delivered on the right type of platforms.

19:30

The other thing this data helps brands get a handle on is who their audience is, and what type of messaging and what type of information are going to persuade them to buy. What I mean by that is, constantly we get sent stuff where the value proposition is very big and super high level.

19:54

They say, “Well, our customer is kind of everybody,” and they give me these broad demos, and then, “Oh, well, they might have money, but you know.” It’s just this yes and no, and it’s very complicated, and there’s no clarity, and they’re still trying to deliver a product to all people.

20:10

A lot of these brands don’t have access to data because maybe they’re a startup. So they need access to data, or they have done a terrible job managing their data, so they can’t even analyze it to really cut through and figure out who their persona is, what the exact message is, and what type of credibility they need to have.

20:37

Is it a set of influencers? Is it user-generated content? Is it testimonials? Is it third-party endorsements? I bring this up because I feel like what you were doing back then in revolutionizing the industry is even more do-or-die now, not just with tourism but really with all brands.

21:00

And a lot of brands are getting it wrong. They don’t understand their audience, and they’re putting together ad campaigns that misalign with their audience.

21:17

So if we fast forward from what you were doing then to what you’re doing now, what is the right method or approach at a high level for tourism brands right now, because it’s so saturated? What advice would you give them, even if they’ve been in business a long time but they’re not getting the messaging right and they’re still trying to be everything to everyone? What steps would you take to help these tourism brands address that problem?

21:56

Wow. That’s a multifaceted problem, of course, and it’s the same regardless of the client, whether it’s tourism or financial or retail. We’re working in a variety of different verticals.

22:20

But my go-to answer to a lot of that is, if you don’t have your own customer data or your own first-party data, companies like ours can build a proxy or mimic that, because we already have a variety of ways to model in the laboratory who the likely visitors to a destination are, or who the likely buyers of a pizza are for a pizza restaurant. Those are straightforward, where we can get three-quarters of the way there without customer data.

22:45

But if we have data that we can input into our analytic system — whether it’s forms that have been filled out, or immigration cards, or booking data — that changes things. One of our brilliant case studies that really changed a lot in the tourism space was what we did with Scottsdale tourism.

23:00

We built a novel approach where, although it took a long time, we got all the hotels to share their booking data and we built an intelligence cooperative, because they trusted us as the intermediary. We weren’t going to share that with their competitors, and we built an aggregate intelligence model that everyone could use.

23:16

If any one of the partners, like the Phoenician, wanted to do a further drill-down on their own data, then they could delineate their customer profile from the others, so that they have a benchmark of the whole of Scottsdale and then a delineation of just their own brand.

23:39

It was really a first of its kind, harmonizing hotel booking data and matching it to our psychographic and clustering data for regression studies. And we found that high-value visitors aren’t just from New York and LA. They were from mid-market metros with a high discretionary income.

24:00

Once you applied all this technology, the partners were able to get a 20-to-1 return on investment, and the destination showed significant economic impact. So this really set a gold standard for how we could activate.

24:17

At the time, the advertising they were doing was a lot more TV, streaming, and Meta. Right now, as we’ve evolved, we’re doing it with programmatic — targeted programmatic ads — and some direct mail. They do send their visitor guides out, but those are expensive, and you want to make sure you’re sending a high-value visitor guide to the right person who’s actually going to come visit.

24:45

Destination marketing organizations can cut waste by 50% using these techniques, and you can lift conversions by 30%. The turnkey AI tools and agent-based solutions that are being offered help you get economic impact that is measurable, and especially at a time like this when travel budgets are being cut due to tariffs or economic turmoil.

25:10

It’s no different from 9/11. Those are the ideal times when you need to really understand who your visitor is, who your audience is.

25:17

Yes. This is not the time to cut spending. This is the time to double down on the research.

25:26

Yes, I will echo that. I know during the pandemic, and then even recently, our agency has doubled down on advertising and we have experienced a big uptick in leads, and we’ve refined our messaging.

25:42

Because you’re right — it doesn’t matter the industry. There are certain types of buyers that respond well to brands that are putting themselves out there and that are first and foremost sticking to their messaging and their value. The experience, the sales cycle, might change. It might be a little different. It might be more rigid.

26:08

But if you know what you’re doing and you know your value and you can back it up, you should be out there running ads and being very vocal. All of our clients we advised to keep their marketing going during COVID — keep all of that going, pivot the messaging, but stay out there. People will remember that you were present.

26:34

This is a different situation. We’re talking about more economic instability, but I did a podcast a couple of months ago on the same topic, and it was just what you said: this is the time to double down. This is not the time to shy away.

26:50

And your ad costs are actually going to be less, because you don’t have as much competition out there right now. People get scared and they pull back and retract, and they say, “Well, I’m going to wait.” Quite honestly, we don’t want clients like that. We want clients that want to be aggressive no matter what is going on. And that’s how we are. So I echo that advice. I think it’s really sound.

27:16

There’s actually a lot of statistical and historical research dating back over decades, across different highs and lows from a multitude of economic factors, that shows the brands that commit to consistent advertising and marketing regardless of the economy always end up winning when the economy rebounds. And there is a lag period for those that do not participate during that time. So there’s lots of data out there to support that.

27:48

What do you think travel brands are still not getting right today? Are they still missing the mark, or do you think they’ve evolved?

28:04

I think the travel brands, hospitality especially, are using more leading-edge tools, and so are airlines. Destination marketers are doing good research, especially the big ones. But I think too many are still marketing by standard demographics and they aren’t using intent data.

28:28

The ability to generate intent data through digital means is one of the things we’re finding works very well, especially when you combine that with persona scoring.

28:40

You can’t use static, once-a-year visitor profiles. It’s going to be a huge miss. You have to be dynamic, and that goes with the changing of the environment — like what we see with Europe and Portugal, where things get over-marketed and then the locals rebel and say they want no more tourists here. Or Bezos comes and puts his wedding on in Venice and there are protests everywhere.

29:05

So you have to look at the pros and cons and the benefits of things, and aim for consistent visitation numbers and not surges that then lead to big gaps.

29:20

Yeah, it’s common sense, but what you’re advocating for is basically saying that the visitor changes based on economics, trends, politics, and seasonality, and that you need to be able to plan for that — to have different types of messaging ready to go based on what’s going on, and to respond quickly to that.

29:46

And to recognize that you can’t run the same ad really more than a month on Meta, right? Because it already starts to have fatigue with it. Maybe an ad is delivering the vast majority of leads, and then all of a sudden it stops and you don’t have an answer why, and then you’re struggling to make something similar. But that’s still not it. So there are a lot of variables at play all the time.

30:13

We do luxury destination marketing for a ranch that’s on the border of Kansas and Colorado. It’s been such a fun, rewarding program, where we were able to put a full digital marketing strategy in place to generate leads through paid Google, Meta, and SEO. We booked half the ranch, so to speak. We almost put ourselves out of a job.

30:47

But they did not have any customer data to start. They just kind of had a general idea of who their audiences were. We were able to take at least enough of that information and use AI to construct buyer personas across the different audiences that they were catering to. Now we have customer data, so we’re at least able to do the lookalike with your new company, Ruf AI.

31:18

You said very clearly that this is not just a data company, this is a transformative business. What are you offering now that is different, or that supercharges what you used to do, and how does that fit into today’s marketing world?

31:40

Well, good question. In the past, we saw that traditional analytics could help with an overall understanding of the audience and who the traveler might be to a destination, or to a theme park, or to a restaurant for that matter. But an annual analytic process can’t keep up with the speed of audience change.

32:02

Now the demographics, lifestyles, and influencers that pop up — before you know it, jeans are important. Who knew jeans would get so political?

32:09

You didn’t know blue jeans were a thing?

32:12

Things change so fast. You have to understand that dynamic, be able to deal with it in real time, and then take advantage of it, so that an event that happens organically, politically, or otherwise newsworthy becomes something you can play off of and leverage to your advantage.

32:29

So what we’re doing is dynamic modeling of persona behaviors, who they follow, and the media engagement that we know will convert them in real time. We were born to go beyond dashboards. That’s what I’ve invested in building this firm to do, and we’re building an AI layer that drives decisions.

32:52

We have a specific series of edges that I think we offer over what we used to do, and primarily that starts with the experience. Being in this industry so long, I’ve picked the very cream of the crop thought leaders to be my contractors.

33:07

We’ve also built a multi-compiled data graph. So not just the Experian file, but all of Experian’s competitors too, all into one big unified graph. So we’re getting the best value for the most accurate emails and the most accurate identities — name, address, and phone numbers.

33:22

We have unique, much better ground-truth demographic data that helps us understand age, income, credit, and all these other factors that are really important for modeling. We call this model fuel data.

33:39

And then we’ve really moved toward automation. That helps with what used to take us, back in the day when you and I were working together, 30 days to do — and now it can be done in a day, or in 13 minutes.

33:56

I know, it’s crazy.

33:58

Triggering an agent flow using APIs and Web3, the speed of turnaround is just amazing. Also, for me to do things without requiring 30 different software developers like we had before. So we intend to be a one-stop shop to meet all the client objectives without a lot of middle layers of friction that slow things down.

34:21

It’s truly incredible what AI is capable of doing, and I think we’re just on the cusp of it. We haven’t even gotten to the full capability of all of it. But the speed and accuracy of the data analysis is really empowering.

34:44

And I know there are a lot of data privacy and security issues, and you have to be so careful what you upload on AI. People kind of forget that sometimes. They’re not mindful that maybe ChatGPT isn’t a totally secure environment, and you shouldn’t be putting patient information or financial information up there.

35:12

So I think there definitely have to be some boundaries around what marketers can do internally, and when that needs to be turned over to a group like yours that is really handling this with white gloves, because a lot can go wrong and you don’t want to be violating any data privacy laws.

35:38

I don’t know if there’s anything you want to add to that, but I always bring it up because I think people get so comfortable on something like ChatGPT that they start putting their entire lives on there. And they’re like, “But this is just my space.” It’s not.

35:55

I even read something the other day that if you go on there and tell AI you broke the law, they’re going to report you. That’s not private information. Apparently people are going on there asking for advice and admitting to committing crimes. That’s what I mean — people really need to be careful how they’re using it and what they’re putting up there. What do you say about that?

36:23

Well, we are big believers in ethical AI, for one, and that’s using AI for good. There’s a lot of things that can be done. You’re always going to have the black-hat hackers.

36:36

Yeah, you’re always going to have spam. Email is good, and then spam is bad. You’re always going to have that 10% of bad actors that are out there. So I think we definitely need to protect against that.

36:50

But you also have to recognize that you can’t just go on the open AI platforms and offer up your whole life. We keep our AI kind of separate and on our own servers, so that it’s not shared across the open AI environment, and so that the AI is not actually taking our private PII.

37:13

We have a high level of compliance around healthcare data, for instance. We do a lot of work with patient data and financial data, which have high levels of compliance. So we sign data protection agreements, we train all of our staff on how to protect data. But we definitely can’t just load data into a cloud-based environment and think it’s going to be safe. So we take all types of precautions.

37:37

And I think brands just need to recognize that AI is not a plugin. You need the right inputs and the right kinds of modeling and decision logic. If you’re putting garbage in, you’re just accelerating bad decisions, and it’ll continue offering up bad decisions.

37:52

So you need to have clarity on what you’re even going to load into AI and filter those things out. Otherwise, the bad part of your business process will be incorporated into the AI recommendations.

38:07

This speed of change is disruptive, and everything’s changing every six months. So you’re trying to keep ahead of the game, but if you’re not continuously building a framework for change, then you’re going to be stuck down a rabbit hole.

38:20

And there are a thousand companies working on every business problem you can think of right now. So you’re not going to have the unique business problem. Believe me, you have competition out there thinking of it. You just need to be adaptable.

38:33

That is great advice. Do you think brands — and travel destinations specifically, because that’s what we’ve been discussing today, though we’ve touched on some other industries as well — can survive today without data and AI?

38:57

Well, you think that they can’t survive without AI?

38:57

I’m asking you. Do you think they can survive without using data and AI?

39:05

If you aren’t using data and AI now or very soon, you can always wait for the big providers to come up with the end-all, be-all solution, because we’re in that period of time where a lot of things will change.

39:13

So if you want to wait things out — when you see technology disruption, I’ve been through five of these cycles before with technology, so I know I don’t want to go too far down some edge product and then find out that Microsoft has already developed it, or Google.

39:38

So I just think that you need to build the framework of it, and you need to have your team. I would definitely encourage my staff to learn everything they can about the value of the tools, and I would incorporate the tools within the practice.

39:56

I think the places where there is risk on certain job titles are real. There are certain places where you just need to upskill yourself and train. Use AI to actually educate yourself. Use AI to build tools for your own internal team, so they can have an area for integrated help where the AI can actually be helpful for delivering the outputs that you need in the moment.

40:22

Yeah, you touched on something really important, and it’s the training and education with the AI — constantly keeping your staff updated and apprised. We’ve started doing regular all-team trainings on knowledge share, and we’ve even asked different people on our team to take an AI solution, train on it, and then present on it when we do our team training.

40:49

We already tested the Lovable AI website platform, where you can now have a website without a developer and it looks gorgeous. It’s insane. So we have the same thing that you’re talking about, but for us it’s even more about speed. We’ve always embraced it.

41:14

But what you’re talking about is, if businesses don’t invest in their teams and keep them updated and educated, we’re going to end up with a very large displaced workforce. And I don’t think there are any national programs right now that can rapidly train people who are going to be displaced in the next six months to a year across all business areas.

41:40

We’ve already seen layoffs with the robots coming in, and now the announcement that we don’t really need web developers in the future. So what we did was offer our web developers an opportunity to learn and train on these new AI website platforms, because we don’t want to just displace them, we want them to evolve with the technology.

42:04

We also recognize that websites aren’t going away right now. We still have all these websites running on WordPress, and we need web developers to maintain those. Meanwhile, we’re going to start embracing AI web tools like Lovable and get them trained on that.

42:26

So all this stuff is happening, all these tools are emerging, and we’ve got rapid adoption and speed. It’s a capitalistic business society. We’ve got ethics. But we’ve got all of the right ingredients for a high-stress, tumultuous business climate where some people are going to make a ton of money and others might come out of a job.

42:58

What do you think the next 10 years are going to look like? And if you don’t want to do 10, maybe do five. Because right now we’re sitting here and we may not even know what those things are — they don’t even exist yet, whatever is going to come to fruition in the next 10 years. So pick whatever you want, but what do you think the landscape is going to look like in the near future for the marketing industry?

43:27

Well, we’re going to have continuing rising costs, and we’re going to have a continuing need to communicate directly to prospects and customers through a lot of noise. Because if AI is expanding and the number of blogs and podcasts is expanding, there’s going to be a lot more data and information out there. So we have to be very targeted with how we communicate.

43:52

But I see the next 10 years as being much more efficient, where you’re thinking with smaller teams that are very, very agile — smaller, smarter hybrid teams with fewer silos. There’ll be a lot of AI agents embedded in daily decisions, and you’re going to be focused on strategy and ethics and the brand voice.

44:17

But I see major disintermediation for the large agencies. Agencies, brokers, middlemen, fractional consultants, and so on — they’re going to be disintermediated. And I think if you’re not building your interfaces now to be Web3-oriented, where you can integrate with smart integrations and efficient execution, you’re going to be really left out of the future.

44:52

We still are going to need a lot of people. It’s just that people need to be educated on how they manage these new flows. As a matter of fact, we may even need more people. There are just going to be millions and millions of agents.

45:05

You have to think of it differently, and not every agent is a robot. They’re functional across a series of needs.

45:13

Yeah, I agree with a lot of that. Those are very sound predictions. I think that we as a country can definitely overcome the workforce education, but it might look different. Education might look different.

45:30

It might not be a four-year degree, which actually might help a lot of people for whom maybe college isn’t the right path, or it’s unaffordable. But because of AI and the tech, they can be trained on it. It’s just a matter of getting that organized and being able to create a mainstream process to give them the practical skill sets to do it.

45:57

I sent out a team-wide email and said, “We are not going to leave anybody behind in this AI revolution that’s going on, but we do ask that you keep an open mind to changing the way you do your job, or what jobs you are doing. We will facilitate the training and the education.”

46:20

But we might come to you and say, “Hey, web developer team, we don’t need web developers for websites anymore. Do you want to learn the new AI?” I mean, what are they going to say? But really, I don’t want to just say, “You’re fired.” Because with AI, it is possible for people to transition.

46:47

When you talk about efficiency in smaller teams, I agree with that. But I also think that AI is so vast and complex, Kurt, that it could even become a more complicated business model in our relationship with AI and how those teams evolve.

47:10

We’re just now starting to understand how AI can contribute to our economy. I’m not an economist, but I believe in supply and demand, basic economics. And you’re right — if that technology is there, it is going to take a large workforce to support it. But we have to be able to train and educate and scale that workforce, and the education is going to look different than a four-year degree for probably a lot of these jobs.

47:46

It’ll look different. It’s hard to anticipate what will be possible when this mixture of experts and AGI starts taking over, when that happens in the next few years.

48:03

Yeah, it is. Well, Kurt, it’s been a pleasure having you on. One last final thought: what would you tell your younger self today? You’ve been through all of these transitions and ups and downs, and building and selling, and now AI. What would you tell a younger version of yourself today?

48:29

Knowing what I know now, of course I would build toward an AI backbone from day one. But I think the best advice I would give my younger self is to trust your instinct on data and get better at partnerships.

48:46

I would try to warn myself not to wait too long on moving down these paths. But knowing me, I probably wouldn’t have listened to myself.

48:54

Well, at least you already know that. You could tell yourself, “I’m not going to listen to you anyway.”

49:05

Well, that is also a perfect personality trait for navigating all these disruptions, right? You’ve got to have a little bit of a rebellious spirit and be willing to break the rules a little bit. Because always doing the same thing over and over again and playing it safe is not going to benefit business, and it’s not really the spirit of an entrepreneur either. So I share that sentiment and appreciate you saying that.

49:36

Again, it’s been a pleasure to have you on Under the Brand. And to our viewers, thank you for watching. I hope you enjoyed today’s episode — a real inside perspective on navigating this very exciting but tumultuous time in marketing. Thank you again for tuning in. I’m Valerie Jennings.

49:57

It’s my pleasure, and thank you very much for hosting. Awesome job.

50:00

Thank you. You’re welcome.