The Evolution of AI in Marketing: A Discussion with Rafa Flores at Treasure AI

Speaker A: Thanks for listening to marketing B2B tech, the podcast from Napier, where you can find out what really works in B2B marketing today. Welcome to Marketing B2B Technology, the podcast from Napier. Today. I'm talking to Rafa Flores. Rafa is the Chief Product and growth officer at TreeData. Welcome to the podcast, Rafa.

Speaker B: Thank you for having me, Mike. I'm excited to be here. I think it's going to be a great conversation.

Speaker A: I certainly hope so. I'm looking forward to it. Thank you so much for joining us as a guest. You've got a really interesting career. We always ask people to give a background to their career to start off with. And you've worked for Treasure Data twice. So do you want to tell us a little bit about your career and, um, why you left Treasure Data and then decided to come back?

Speaker B: Yeah, no, it's, it's a very good question. And I, I do want to take it a little bit of a step further and start about just the start of my career. I came out of school of business and engineering degrees, and at the time, I, I, I decided I was going to be an engineer. However, I didn't know how to get a good job, right? Everybody was competing for jobs. And so I said, hey, you know what? I'm actually going to go and become an engineering recruiter. People thought I was crazy at the time, Mike. They said, hey, what are you doing? You're leaving a lot of money at the table. And maybe I was, maybe I still am. Um, but I wanted to work with the top hiring managers. I wanted to get a sense of what it was like to work at these companies, what it was like to work for that, right? What I needed to have on a resume to get through the initial screening. And so I did that. Right? That's the path I took. I set three months of a hard stop that I said, no more than three months, otherwise I'm going to be stuck on the people side of the aisle forever. And I did that. I quit on the month three. I said, no more. I got one hire. So I was a pretty bad recruiter, but it set me up for the rest of my career. And I'm very happy and glad that I did that. In terms of trash, of data being a boomerang, I am a boomerang. I never thought that I would be a boomerang, but here I am. I was with the company for a little over six years, helped build the company. Right. Uh, so it's very dear to my heart. And at the time When I left, I took on a different job and I never thought I would come back. But one thing led to another. From one dinner to a Thanksgiving tax to here. I've been in the seat for a little bit north of one year. It's been a fascinating year. The speed of innovation that we've become, it's fantastic. And I like to think we're ahead in terms of market dynamics. So I am proud and happy to come back. And I have a fantastic team that I work very closely with on a

Speaker A: day to day that's so positive. I love the way that you're prepared to admit that maybe it's the right time to go back somewhere, even though you weren't naturally a boomerang. I'm interested whether, uh, the Raffa who was a recruiter would have recommended a company to take someone back like that.

Speaker B: I would have said, don't take this guy back. No. You know, when I had the conversation with our current CEO Kosuke Ota, I said to him, why do you want me back? Right? And he said, I need somebody who can just focus on executing and getting the job done, who has a vision and can get it done. You're a doer. I know you could do it right. And we've done it right. I think it was the right decision. It was the right decision for me to join. I don't know if he feels that it was the right decision to rehire me, but it was definitely the right decision for me to join. I brought in a lot of peers who worked with me in the past and they're part of my teams now. And we've really just. We have this new motto for the year. It's our annual theme, Move at the speed of now. Right. With everything going on in the market, how do we move the speed of now? But how do we give a meaning to the term now? Right? The sense of community. What does now mean to you? Is it now in this second? Is it now in where you are in your life, your context, and in the context we're in? I think coming back has allowed me to just give people a little bit of hope that, hey, we're going to be just fine. AI Ah is here to stay. But how do we actually make the best of it and help our customers be superhumans or users, but also ourselves? Right. My job as a leader is to make sure that people can get their next best job after this job. Not currently. Right. I'm a firm believer in that. And so. So that's what I'm here to do Mike. That's why I came back for, for the job.

Speaker A: It's really interesting you talk about this moving at the speed of now because probably nothing is more now than AI, and obviously Treasure Data is now positioned, you know, very much as an AI tool rather than just a customer data platform. So tell us, you know, why did you do that and what did that require in terms of strategy?

Speaker B: Yeah, no, it was a hard bet, I could tell you that. It was a lot of closed door meetings, a lot of punching on walls and things just to make sure we made the right decision. But as of April 20, we became Treasure AI. So we rebranded the company. We're still in the middle of it. Right. There's a lot of very cool and exciting things that came out of mouse yet, but you'll see a lot of PR in the next couple weeks. But it's a different company now in terms of the why, I think there's two big pieces to it. AI is here to stay. I'm a firm believer in that. I don't think it's going away. I was a part of the Internet of Things with ARM holdings and to me that was different. Right. There was no credible use cases with that AI. There was a lot of credibility in terms of how much it can actually save you time, but also how much it can actually drive revenue for the business. And so it's not going away. So when it comes to moving at the speed of now and AI, if we can actually go and have, uh, a position as a company where AI is not just generative AI, but it's a combination of machine learning plus gen AI, that is our definition of true AI. And so when we look at our company, we're trying to make the choice of do we pivot to become this Treasure AI? It's not really a pivot, it's more of a step in the journey. We've been in machine learning company, we've done predicting, we've offered next best product, we offer next best action. The models are there, we're bringing in new models in. Right. And that's our definition of AI. Uh, so that's the first element of it. We saw it as an evolution, we didn't see it as a pivot, which I think that's the best way to do it. If it had been a pivot, I don't think that's the right decision. Right. And I think unfortunately a lot of companies are now are pivoting to rush to bring AI in and those companies are probably going to be going under in the foreseeable future. The second element as to why we made the choice is we have a very technical DNA as an organization. We're adopting AI in house. We want to be a, uh, company or a business that can actually go and drink their own champagne. So when we put AI in the name, are we agentic by design ourselves? And the answer is yes. Right? All the way from our accounting officer to our marketers, to our product managers to UX designers, not prototyping and pushing PRs. Right. Pull requests. It's fascinating to see that. And so if you bring the element of. It's been an evolution of our definition of AI, not just the market noise, plus who we are as a DNA of a company, that's trust your AI. Right? And that's why, to me, it was the right decision. I think the third piece that I will add too, is when I land. And I got to tell you this story because it's always. I'm sure everybody goes through this, but when I land at San Francisco Airport to go to our headquarters, I live down south of Los Angeles. I see about a thousand billboards on my drive in an Uber between the airport and headquarters, and they all talk about AI right? And AI this and AI Superhuman. Take your jobs away. Don't fear AI. There's a difference between what everyone is doing and what I want to do from a brand perspective. I want to become a lifestyle brand, and it's hard to do that. Right? We're not Nike. We're not. We don't sponsor Steph Curry. However, I want you to feel that if you come and use our product, you're part of something greater, right? You have the sense of community. You have the sense of. I'm part of a community of builders of innovators, right. Of people who are making the best of AI. Uh, that also comes with Treasury AI name. And that is something that I think we're gearing towards. We're not there yet. But that is where my focus is right now. To make sure that Treasury, I mean something to the world, not just to us.

Speaker A: I love that. I love the idea of like, uh, a lifestyle brand in the world of B2B being actually part of something. I mean, can you explain a little bit more about how you're doing that? Is that getting interaction between users? What are you doing? That's a really interesting thing to talk about.

Speaker B: Yeah. So it all starts in the little details, right? So I'll tell you. Swag. The term swag, right? Every technology company gives out swag. Go to conferences, they give out a hat, they give out a custom boot nowadays, do whatever they can to stand out. For us, it's different, right? When I said to the team in the company, I want us to be thinking from a lifestyle brand day to day, right? How can we fit their life and not them fit their lives into our product, we change our swag. We actually have air fresheners now. The air freshener scents are called AI, Artificial intelligence. And our thing to the market is, hey, you can touch AI. You know what AI sounds like, what it looks like, but can you smell it? Right? That's lifestyle. I know it sounds cheesy, but that is lifestyle. Right? And the reason I bring that as an example is it's all in the little details, right? If you focus on all the little details, you slowly but surely start to become more of a lifestyle brand. People will see you differently. Right? And ultimately, uh, that's the whole objective of when I build on the product side, right? I oversee the growth side. I also oversee the product. So left side, right side of the brain. But on the product side, if we can build now to ensure that somebody works less, right? Forget eight to five. If somebody can work eight to one because of our, uh, tools underneath the hood, why not, right? We've done our jobs. And so if you have that methodology plus you focus on the details on the growth engine side, you slowly but surely will become more of a lifestyle frame, right? People will care, people will notice you, you will stand out. It's just a different way of doing business. As a tech company, I love that.

Speaker A: I think that's a great approach to, you know, building a bit more of an emotional relationship with your customers. I'm going to go and focus a little bit more though, on the product. And how do you let that person that starts at 8 actually finish at 1 rather than work through to 5? I mean, what problems are you solving for customers today that you maybe couldn't solve two years ago?

Speaker B: Yeah, I mean, let's talk about just the verticals. Uh, we serve and ultimately the technology vertical we sit in, right. Or historically have sat in. We work very closely with financial services, healthcare, media, automotive, cpg, retail, right. Hospitality, entertainment, you name it, publishers. And one of the big components of that is we have his birth. We've been a customer data platform. Right? So if you look at those verticals and you look at the verticals that we come in as a vendor, it's often viewed as complex and hard to deploy. Right. I'm trying to change that and I can now because of AI and the products that we have. We just came out with a new product called Treasure AI Studio. Treasure AI Studio is the super orchestrator at the top that allows to orchestrate your equity. Plus the cdp, AKA the Data Foundation. All in plain English. You couldn't have done that as a marketer six months ago, right? You just couldn't. Fixing a broken data pipeline, how are you going to do that without, uh, the technical chops? How are you going to do that and get prioritized by it? You may have a two, three week time span that you're still going to be waiting for them to fix up that broken pipeline. Well, you could do that now with Treasure I Studio, right? And so those are some of the use cases that we actually are able to solve for today via our products that we couldn't offer to the market, uh, even a few months past. Right? How do you deploy a campaign from the ground up in five minutes? How can you be at the gym? I'll tell you a personal story. We have thresherized Studio on web, desktop and mobile. The beauty of Ikea, uh, mobile is that I pan as a CTO and CGL at this company, I usually go to the gym at five in the morning every single day. That's just, I can't sleep sometimes 4 if they let me in, right? But I like to sit on Stairmaster and I just open Treasure I Studio and I ask the questions that I need to know answers right before I start my day. Hey, show me the latest pipeline growth number, right? Show me green space. Show me account health for the following three accounts. Because I have a call with them later today. When I check my founder, I can get those answers. Those are some cool use cases, right? If you are a CMO and you can actually, in a proactive way, go to your team and say, hey, here's what I'm seeing. Here's a little bit of direction. Go about your day. It's fantastic. You're moving again at uh, the speed of knob, right? In real time. You look at the signals at the right time.

Speaker A: I think that's interesting. I mean, it's kind of a reflection of the importance of first party data now. And I think a few years ago, you know, third party data was really the key thing. A lot of privacy regulations come in. My first question is, is first party data really that valuable now? Is that really where people need to focus?

Speaker B: First party data is a gold mine, right? I don't think that has changed. I think the mindset has to change in terms of how you actually deploy the value of that gold mine. And here's what I mean by that. I've sat in so many panels, webinars, fireside chats, you name it, where you have all these big brands and CVOs talking about the value of first party data and the process they're going to go through and what their expectations are. And what I always tell them is, this all sounds great, right? It's like writing a book. You wrote a beautiful book, but in execution you're going to be sitting there for two, three years still looking to deploy your second or third use case, right? Because you're going to uncover the next broken pipeline, the next missing source. You're going to uncover some potential regulation that changes or comes in. You're never going to actually deploy the true value of that data. And so with AI coming into the mix, you can actually deploy much faster, right? And we have the saying at the company that AI is only as good as what you feed it, right? Garbage in, garbage out. First party data sits at the crux of that. You have to make sure that you leverage it with purpose, can try to solve everything at once, Just solve what's your most critical business problem and then scale it, right? Add another source, change a table, check a different pipeline. Don't try to do this pretty book and then try to actually go and have somebody read it. Guess what, they're going to be stuck on page one. They're not going to get past that, right? And you're going to churn. You're going to bring a new vendor, but you're going to have the same book. So then you're going to churn again and it's going to keep, uh, it's going to be a continuous cycle. So it's not the vendor problem, it's you are the problem.

Speaker A: That's really interesting because, you know, as an agency, I see a lot of people with a lot of first party data that frankly they're not using or they're using very badly. And it's interesting that, you know, you're saying it's not the tool, it's really about making sure you can implement those use cases. So do you think AI really is the key to making it easier to make use of that data?

Speaker B: Well, yes and no. The no and the no is not so much a no, more of a caveat. The challenge with, with first party data, uh, is access, right? You cannot just give everyone the same degree of access. Privacy regulations, governance, extremely, extremely critical. Now more than ever because people tend to want to have more access with AI and so that's the no part. Right? You have to ensure with first party data and using the data you can just democratize data. You have to do it in a governed way. Something that we take very seriously here because we serve global brands. Right. And so we want to make sure that we can remain compliant and keep, keep them true to it as well. However, the reality is people can actually ask deeper questions and get an answer right away. Right? You can go today and ask a question in trust your eye studio. Hey, why is this channel actually not sending more than X number of emails when my segment has the following set of profiles? Well, it's because you're missing a source or you are missing X signal. Right? And then the more answers you get, the more likely you are to go and explore and use more of the data. Right. There's a question on whether you should or have access. Right. But that's just the reality. And so because you can get an answer at the tip of your finger so much faster, you are more likely to be able to use more of that goldmine.

Speaker A: That's interesting. The opportunity for AI to uh, actually help people make use of that data is clearly a great opportunity. But do you think there's areas where maybe companies are overestimating the benefit of using AI, particularly agentic AI in many ways.

Speaker B: Right. And I'll tell you the biggest mistake and this is my opinion, this is not tertiary opinion, but this is me Roth of Laura's opinion. Everyone wants to just rush to deploy AI, right? You're seeing that there's pressure all the way from boards down to sea level and it just trickles down. There's two factors you're going to run against. Number one, there's a credible fear of AI in general. So if you're in the board and your CEO says yes, that sounds great, we're going to go and do X. That person may not, they may be scared of even them losing their job. And this fear just tenfolds as you go down the amount of mid level management that's scared it says yes boss, I'm going to go and talk to this vendor. And then they delay those conversations by a month and then they push the meeting out and then it's six months later and they still have an engage is they're doing that purposely because they don't want to risk losing their job. And so there's that fear element of it. Right. And then on the other side the mistake being made is everyone's thinking about how do we actually save costs, how do we work faster? I have not once, Mike, promoted anyone at any company or team that I've led due to how fast they were. Never. I have never sat in a panel or a meeting where we're discussing promotions and said, well, this person works faster, so they're going to get the promotion. No, it's all about adding value, right? And so when it comes to overestimating AI, people overestimate the fact that you still have to add value. Right? It's not about just saving costs or working faster. It's you can work as fast as the speed of light, but if you're not bright enough in the room, guess what? It's not going to be enough. Right. And so I think that is kind of overestimated many times. How do you measure success of AI? It's not just operational efficiency, it's you ultimately have financial attainment.

Speaker A: I mean, I think that that's a really like, straightforward down to earth approach. You know, you've got to get the value. But obviously we've all seen great benefits from AI. So on the other hand, let's look at something more positive. Are, uh, there some examples of, you know, enterprise AI deployments or applications that you think are going to happen over the next couple of years that are really going to surprise people?

Speaker B: I think digital worker, right? And I know it's hard pivot to go from, hey, we're talking about fear of AI, dude. Digital worker, digital worker. I think the problem with the concept of it is when people hear the term digital worker in the sense of AI, uh, they automatically think we're saying you are going to lose your job because an agent's going to take it away from you. That's not what we mean, right? By digital worker. What we mean is at least us at Treasure AI, hey, the job that you are performing when you go to sleep because you need to sleep, human beings need to sleep. It's a requirement. You eat, you sleep and you drink water, right? There needs to be something in place that's running autonomously and that will allow you to have a better morning the next day and the next day and the next day. And so you are going to see a big rise in the term of digital workers in the field in better supporting the human in the loop. So that it's a team effort, right? And we're seeing that. We are seeing it quite a bit at Treasure AI. We have a lot of companies that we serve today saying, hey, let's talk about digital worker. Let's ensure we can leverage it, right? How do we make sure we can bring it into the mix with our talented teams while still them being the governance in place behind the machine. And so I think you're going to see the rapid rise of that. Unfortunately, I think some vendors and companies are going to take advantage of it and just say, hey, by 2035, all of you are going to be out of jobs. I don't think that's going to be the case. Right. I don't think banks want all of us to lose our jobs because no agent's going to pay our mortgage, us getting a paycheck. But I do see a big rise in the concept of digital workers.

Speaker A: That's interesting. I think what we're seeing in the market is there's really this question of how big an impact there's going to be. And, um, you've said digital workers are going to be a big thing, but you don't see them replacing all our jobs. I mean, as a SaaS company, you've obviously seen some of the valuations of SaaS go up and down and particularly down recently as there's this idea that maybe vibe coding is going to replace SaaS. So do you think SaaS has still got a future? And if you were starting again, would you start helping people build something custom or would you build a SaaS product?

Speaker B: I would not build a SaaS product. I'll just tell you that out of the gates. And the reason I wouldn't build a SaaS product is there there's no such a thing anymore as an ankle biter. All your competitors, big or small, they can catch up to you very quickly. Right? I think here's what makes the difference. What makes the difference is how do you actually guardrail AI to ensure that you can still serve a purpose and to fit to a, uh, business need in a safe manner. Right? Because sometimes you can run into some serious risk. I'll give you a great example. In the worlds of CDPs, the segments are the engine to everything, right? It tells you who the right people are with the right signal and how to best target them. Well, if something happens to that segment because you have bytecoded it, right? You have bytecoded an application, you put people in there and suddenly the guardrails you have on there, you then think that somebody could potentially go and a bad actor come in and pull that information away. Well, guess what? You may suddenly just have to shut down your operation because you're going to get a major Lawsuit, Right. And you're going to lose that lawsuit. You never thought of it, but you will. Right? And so guardrails are extremely important and I think that's the big difference. Right. You could be a SaaS company looking to evolve to be in an AI first company. The ones that will win are the ones that have proper guardrails. And you're seeing that with some of the big names out in the market. But you're also seeing how some of those companies still struggle. Right? We just saw the big anthropic news with the US government now. Take it or leave it. You can see that in many different shapes of arm, but it happened. Right? And so how do you guard rail to prevent some of that? It doesn't matter who you are. That will come your way.

Speaker A: I think that's a great point. And um, I mean, I guess you're saying that even when you look at, you know, a CDP platform which doesn't seem to be necessarily something that has to be super robust and reliable, actually that really matters because when it goes wrong, the cost is high.

Speaker B: Exactly right. And I think this is a, uh, Going back to your first question of was it the right decision to come back? There was a major announcement last week from Databricks. Right. They've been a partner of ours, Data Warehouse. Obviously a lot of our customers have databricks on the technical side and they use us as their martech source of truth. But now Databricks is saying, hey, we have customer Data Lake, we're the next cdp. Right. Sitting within the data warehouse. What they're realizing, at least from my perspective, is it's not that easy to build a CDP because now you're building something for a non technical user that you have no experience with. Right? And you have to now gain credibility there. And you also forget about that. There's historical friction between the marketeer or the CMO and the IT teams and now you're forcing them to kind of be in one place. It's just different, right? And so yes, everyone wants to be a cdp. I have this running joke with some of my executive friends and everyone wants to be a cdp. Nobody knows what it's like to actually have to build a cdp because when something goes wrong, it could go really wrong. And if you don't know what you're doing, that could really affect many, many different things down underneath the hood.

Speaker A: That's such a great point. I mean, I'd like to kind of finish this discussion on um, Data and the CDPs with something a bit Positive. So I'm interested to know, have you got an example of a particularly innovative or, uh, creative or effective campaign that you've seen that leverages technology and data

Speaker B: from us or just in general in

Speaker A: markets, just wherever, uh, something you think is great?

Speaker B: Well, I'll tell you, and I don't think I'm great by any means, but I am going to give my teams a shout out here. One of the things that I. I decided to deploy a couple months ago, it just came to my mind. I said, well, what if you can actually go and try a CDP as soon as you land on the website, right? The concept of plg, hard to do, not easy to do it. There's a reason nobody had done it before. But I believe that nowadays when you go and you think of a campaign, people want to. They want to test it right there and then, right? Don't just send me an email. Don't just show me a, uh, demo on render. I actually want to see it. Give it to me. I want to try it. If it works, I may buy. If. If it doesn't, then maybe not. And if it doesn't exist, then I'll know right away. If you. If I ask you, hey, I want to try it right now. And they say, no, I know that it doesn't exist. And so we decided to roll out PLG on our website. If you go to Treasure AI, uh, you can actually do it now. You can actually go, click try now and it takes you to your own CDP deployment, right? You can bring in your own data, it's governed and save, or you can actually use some sample data that we have, depending on the vertical and the Persona you are. And you can go and run and get an email with the latest information you need or how to deploy your next best journey. Right. For Omni Channel Orchestration. To me, those risks are bets worth taking at this point in time to meet the expectation of who a buyer is and what they're looking for.

Speaker A: I love that. And I think that that's different to what a lot of people say on the podcast. And it's great that you're not only calling out one of your own products or, uh, your own campaigns, but you're also talking about something that's really about building an experience for a customer. So thank you for that.

Speaker B: It's always fun to build the next best campaign. You gotta be different nowadays if you wanna stand out.

Speaker A: This has been fascinating, Rafa. I mean, before I let you go, there's a couple of questions that we like to Ask everybody. And, um, the first one's really simple. What's the best marketing advice that someone's given to you?

Speaker B: It just happened. I was a con at the Festival of Creativity and I was having a conversation with a friend and we were walking this person through, uh, a new product offering regarding Pig Media AI Suite. Right? How do you actually optimize this big dollar spent that you have for all your ad requirements? And this person said, we are at an era where performance marketing and brand marketing are just becoming one. They're not really separate. They need to become one. However, the concept of brand marketing versus performance marketing still stands. Where marketing is there to build a brand that people love, but you are there to drive conversions to secure targets as a business. Right? And I thought that was just such good advice because oftentimes we try to separate the two and we report separately on them and we speak of them. But you cannot build a brand you love without knowing what you need to actually secure in the background, and vice versa. How are you going to secure targets if you don't build a brand you love? And how do you bridge those two together? To even have a dashboard that shows you our lovability score, but also our pipeline, Right. Those don't really exist. You don't really think of it that way. Well, I'm changing my mindset, I tell you that after that conversation, and now I want to have a dashboard that shows me that. Right? Tell me the people love our brand and are we actually going to be able to hit quota? Show me in one single view.

Speaker A: I think that's a really fascinating idea there. And, um, you know, obviously the more people love the brand, the easier it is to get performance marketing to actually deliver results. So I think that's brilliant. The other question we like to ask people is around the future, and I mean at, uh, Treasure AI, you're right on that bleeding edge of this rapid change we're seeing in marketing. If you were talking to a young person who maybe just graduated from college, was looking to start a marketing career, what piece of advice would you give them?

Speaker B: Yeah, and we're seeing this, right? I mean, I always go on stage and I say, hey, don't fear AI. And then I will get an answer from, from the audience of, well, how can I not when my kid cannot get a job fresh out of college? And it's a reality. I'm a parent of four, right. I completely want my kids to, to be able to be employed when they finish, but I do want them to go to college. But what I will tell a young marketer who is just graduating, looking for their first job, go and actually use AI. Uh, go. Learn all about it. Go speak, reach out on LinkedIn to all the AI experts. Reach out to yourself, myself, whoever, right? Try to get advice so that you can actually develop your own perspective of how AI can be applicable to the jobs that you want to apply for. So that when you go through that interview process, you come to the table with something. Don't let companies put everything at the table and ask you, hey, what do you think? How can you actually add value to us? You tell the company, here's how I can add value, because here's the three or four different key use cases that I see of how AI can be applicable to me at this point in time, with the limited context that I have. That would be my advice to them.

Speaker A: Uh, I think that's brilliant. Bring something to the table is probably, you know, one of the best bits of advice that you can give a young person. Rafa, this has been fascinating. I feel like we could have spent a lot longer talking about AI and Treasure Data. But if somebody wants to find out more information, where's the best place for them to go?

Speaker B: Try the product. The best way is to try the product. So, going back to the PLG concept on Web Treasure, that AI, go in there, you'll see a big button right in the center of the screen saying, hey, move at the speed of now. Do you want to try now? Try now. Right? And if something's broken, you don't like the UI, uh, something's missing. Find me on LinkedIn. Let's have a conversation. All feedback is good feedback.

Speaker A: Uh, that's amazing that the head of products being, you know, giving you an offer to actually give product feedback directly. I love that. Thank you, Rafa.

Speaker B: No, thank you for having me. What a pleasure.

Speaker A: Thanks so much. I've really enjoyed this. Thanks for being a guest on marketing B2B technology.

Speaker B: Thank you. Happy to come back anytime.

Speaker A: Thank you. Thanks so much for listening to marketing B2B tech. We hope you enjoyed the episode. And if you did, please make sure you subscribe on itunes or on your favorite podcast application. If you'd like to know more, please visit our, uh, website@napierb2b.com or contact me directly on LinkedIn.