Marketing 911
Marketing 911, is the podcast where we tackle the toughest marketing challenges at the executive level.
Whether you're navigating complex strategies, trying to reach your target audience, or facing shifting market dynamics, we're here to provide you with actionable solutions.
From digital transformation to customer retention, if it's a marketing crisis, we're here to help you solve it—before it turns into a full-blown emergency.
Marketing 911
Mastering AI-Driven Marketing Strategies: Revolutionizing Workflows and Breaking Barriers
Unleash the hidden power of AI in marketing with insights from Tim Freestone, Chief Marketing Officer at KiteWorks. Discover how AI is not just a tool but a game-changer in strategic marketing workflows, as Tim shares the remarkable ways it reshapes brainstorming and go-to-market strategies. From significant reductions in product launch times to the creation of a deep feature library, learn how KiteWorks is leading the charge in integrating AI to streamline processes and manage marketing collateral. This episode sheds light on AI's vast potential at a strategic level, promising listeners valuable takeaways on staying competitive in an ever-evolving market.
Explore the complex yet promising landscape of AI adoption in sales and marketing. We discuss the innovative trend of daisy-chaining AI models, such as Anthropic and ChatGPT, to tackle intricate tasks like aligning product capabilities with regulatory demands. Despite AI's clear advantages, uncover the barriers professionals face, particularly in sales, where traditional methods often curb AI's full adoption. The conversation reveals both the challenges and the promising benefits of embracing AI, providing a nuanced perspective on how businesses can bridge the gap between established practices and cutting-edge AI strategies.
Hello and welcome to Marketing 911. I'm Brian Backstrand with my co-host.
Speaker 2:Richard Bliss. Brian, a pleasure to be here today. I think today's kind of exciting because you brought us a guest, didn't you?
Speaker 1:I did. And not only is the topic exciting today, which is AI, but we have Tim Freestone, the Chief Marketing Officer at KiteWorks and recently the head of AI for his entire company, not just marketing. So he's on the leading edge and I know you are, Richard, as well. So, tim welcome.
Speaker 3:Yeah, thanks, guys. It's great to see and speak with you again. It's been a while, at least formally.
Speaker 1:Absolutely so. Let me just jump in. There was a recent report done around AI. I just want to read a few things from it. So Anthropic recently published what they call an economic index analyzing how employees across industries are actually using AI, and here's a few bullets. They found a couple of them surprising. Software engineering dominates AI use 37% of conversations. Ai is already a major tool for content creation marketing tasks. Now we know that. What surprised me here is it's only 10.3% of all AI interactions. Of all AI interactions, ai augmenting work 57% of the time and automating tasks 43% of the time. And I know, tim, you have some experience there. And summarizing, they said marketing teams are leveraging AI for brainstorming, iteration and validation, and enterprise-level marketing teams are integrating AI into workflows. So those are kind of the highlights. A couple things surprised me, tim.
Speaker 3:Yeah, I mean, none of it really surprises me too much, other than you know. Actually I'll take that back. The marketing thing surprises me. Actually, I'll take that back. The marketing thing surprises me. I would have thought everybody with marketing in their title at this point was sort of by default using AI. I live in my little bubble. My little bubble is my own marketing organization and two years ago I essentially stood up in front of everyone and said you've got to be an expert in this in the next 12 months or you know we'll have. We'll fall behind as a competitive entity in in terms of delivering marketing um into the uh, uh, into the industry.
Speaker 2:And Tim, I don't think you're in a bubble, because obviously I work with a lot of clients and marketing teams and all of them, all of them are using AI to some degree, every single one of them. Nobody's not using it, and so I also find that surprising. But I guess maybe we're not aware of the deep use that the coders are using to kind of shortcut everything that they're doing.
Speaker 3:Well, also this was Anthropic right, and so Anthropic has access to Anthropic's data, and one thing about Anthropic and the cloud model is that it's heavily leveraged by coders and thought to be the best coding AI solution in the market, so it's also the data set that's being assessed. I would bet if ChatGPT did the same thing, you'd probably see a higher pivot towards marketers, but that would be, I'm just guessing so, other than, uh, what we all know right content, and you know you have some, you're looking for creative ideas.
Speaker 1:You can go into the chat or any of the others and get some. You know feedback back and forth, etc. What else is, are you using Tim that falls out of that content and messaging, et cetera.
Speaker 3:Yeah, I mean, the biggest thing for me as a chief marketing officer because I don't do a lot of content myself is strategizing with someone or something.
Speaker 3:In this case, you know I used to schedule a meeting and get you know some product marketers in a room when we'd sit on a whiteboard and we'd talk about stuff and, you know, 17 days would pass and we might finally get to some sort of creative approach to bringing something to market. I pretty much skip that now. To be honest, I work with a couple of AI systems that I have some baseline prompts and I look at problems that I might be having in terms of execution or where the industry is going, and I just will sit there for an hour and a half to two hours and brainstorm ways to get around these issues or ways to be creative to go to market and, you know, save myself tens, if not hundreds of hours of multiple people's work. So strategizing on approaches to going to market at a CMO level, I think, is probably the most underutilized part of AI systems, you know and then go ahead.
Speaker 1:No, I was going to say a hundred percent and I have been reading that brainstorming absolutely is a piece of what folks are doing, but I don't believe a lot of doing at the strategic level. You mentioned something to me last week which I found pretty fascinating. So all of us who have been in marketing or are in marketing, when a product launch is around the corner, it becomes all hands on deck and the weeks and weeks of work that it takes to get the content, the messaging, the collateral out, et cetera, we're all very familiar with. Why don't you tell everybody how you have dramatically reduced that process, which is a huge piece of what marketing teams do in the IT space?
Speaker 3:Yeah, sure. So at the core of any sort of go-to-market or product launch is a set of features, right? And once you know that, that's the baseline for everything, what we did here at Kiteworks is we spent about five or six months building what we call a deep feature library of every feature of our product, and then that served as the baseline that we either update or edit as new products are released. So it's you know, let's say, 200 rows or more of what's the feature, what does the feature do, and we have them grouped by some core tenants like these are all the features that help us control data. These are all the features that help us track data. This is all features that help us protect. Those are the three features that help us track data. This is all the features that help us protect. Those are the three tenets we group the features under.
Speaker 3:Then, when a new product release is happening, we just look at all the new features that are happening and we update that deep feature library and that becomes the sort of source of truth that we apply AI to to create messaging.
Speaker 3:So when a new set of, let's say, 10 features come out in a product release, we add it to the deep feature library, we subset it as released 8.4.5, and then we start working with the AI systems and say, all right, now help us understand what the value of these features are for our ICP or our customer profile, and it will create the entire sort of use case scenarios and value propositions of those new features to that particular market. And that takes let's call it 30 minutes, you know, let's call it 30 minutes, you know. And once you have that new set of use cases based on those features, you can then have that as your new foundation for all of the other artifacts that we all know and love when we do a product release everything from a press release to social media, to presentation decks and that just makes everything go significantly I mean significantly faster.
Speaker 1:You know, I just think of go ahead, Richard.
Speaker 2:No, no, go ahead. You got a thought there, Brian.
Speaker 1:I was just going to say I just think of all the times in the going back and forth between product management, engineering and product marketing around what should be the key messaging, what's the headline, what's the subtext? What really is the key messaging? What's the headline, what's the subtext, what really is the value? And leading up to any launch was the back and forth and changing, et cetera. This kind of just circumvents all of that because it's the hardcore information that's been plugged into AI and it is pumping out what should be the value prop and the messaging and the content.
Speaker 3:Right, Because it's pivoting on way more knowledge than any individual person in any given role in a company can have. So you can't kind of argue I'm a product manager, right, Like yeah, but this is a product manager, a product marketer, a customer, a use case generator. It's hard to say, well, that's not correct.
Speaker 1:And the other piece of that, too, is because it knows the information that you've been putting in and it remembers a lot of it. You can then say and how does this compare to the messaging, positioning and use cases of our top five competitors? And it'll spit out the strengths, the weaknesses. Obviously, you need to take a look at that, but again, there's always debate internally. Without this capability around, we're really differentiated from the market. Is it a me too? Is it new? And this kind of eliminates that?
Speaker 3:Yeah, 100%. At some point it's a little bit frightening, right? You know there was a line from Mark Andreessen 10, 15 years ago where software is eating the world. Well, now AI is kind of eating the world and we'll all adjust and pivot Um and there'll be laggards and followers and innovators. But I think, by and large, the idea that you can go to market faster with your product, if you leverage this over and above um squads or, you know, collaborative internal tiger teams, as we used to call them everybody's going to be better off. Yeah.
Speaker 2:A hundred percent. So one of the challenges. So a couple of questions, tim. One of them was you talked about taking this. Are you storing the information persistently in an AI or are you storing it outside and then reloading it into the AI when you do the feature update?
Speaker 3:That's a good question. So we have both. We have an internal AI system that kind of has the persistent data and we use that for different kind of use cases. But by and large we'll use Claude, because it's just better at sort of distilling the data in the use case that I just talked about than something like a chat GPT or an internal private system. So we'll take the feature set of the deep feature library, we'll upload it into Cloud, right, and then we'll take the new features and we'll upload it into Cloud and we'll say everything I'm about to ask you and everything we're about to strategize on from a messaging standpoint. Only refer to these two documents, right, it creates those guardrails, right.
Speaker 2:So have you looked at it? So Gemini's out there, notebook LM, which is allowing you to load up multiple sources and then kind of keep coming back to it. Are you seeing a shift there, with maybe the addition, not the replacement, but the additive nature of kind of a daisy chain where, okay, this AI tool looks at this piece of data, this is what it's optimized for. Now let's have another one. Look at it from this perspective, because it can create something, or you pretty much stay in with the anthropic model.
Speaker 3:For that particular use case. We pretty much just stay with the Anthropic model. I will daisy chain and some of my product marketers will daisy chain different models together. For other use cases, like we have a compliance product marketer and she'll get a regulation from like Qatar that's got 400 pages and 275 requirements. Well, chatgpt's O3 model is way better and almost, I'd say, 100% accurate now at distilling all of the requirements into a table. And so then you take that table and you move it over to Cloud and then you upload the table and those features, that deep feature library, and say, okay, now align our product requirements or our product capabilities to all of the requirements of this Qatar regulation and tell us do we align, yes or no? If we do, what features align to deliver that particular requirement. So she'll put those two together. It's a two AI daisy chain, but I think that gets what you're asking.
Speaker 2:It does, because I'm starting to see more and more as I work with it and as I see other clients, where you're using ChatGPT for one thing, you're using deep research or Gemini deep research for another thing, you're using Claude, which I prefer when it comes to the pros and the ability to kind of reason, to put that out there, and then what works is you kind of start putting these all together and each one is optimized for its own ability, and then, if you start to get that feel so starting to see more and more of that, yeah, Go ahead.
Speaker 3:I just to close off on that. What's then now happening is that's a skillset I'm learning this the hard way that that's a skillset that needs to be trained, and there's not many people that have the skillset.
Speaker 1:Therefore, there aren't a lot of trainers, and you know, you know it's interesting about that, and you and I talked about this Tim around. It's one thing to know something, it's another thing to do something, and if you go, you know, for all of these different strategies and tactics that we're using AI for, unless you have the expertise in marketing, from the standpoint of what are the questions, you need to ask chat in order to get to the answers that you're looking for, and so I think there's going to be a. I can see playbooks around how to get to, if you want to get to this answer. These are the types of questions and the path you need to go down, and if there is a daisy chain until things are more unified, you're right. I think that's a huge skill set that isn't available for most today.
Speaker 2:Yeah, one thing I wanted to ask the two of you, because you both have been doing this for quite some time, and that is marketing. Go to market. One segment that didn't pop up is sales. Do we see Tim in your case, because I talk to a lot of salespeople and I talk to them about AI and how to use AI to do research on. They're going to meet with the CIO of a major financial institution Using AI to go find out about that individual. What are the things that they have focused on? How do I talk to them? They're running my competitor's product. Okay, how do I? These are really specific tactics rather than that overall messaging. But, okay, how do I approach that individual using AI to do that? Are you seeing a hesitation, or maybe even a missed opportunity for sales to start using AI for their own roles? What do you see in there?
Speaker 3:Yeah, I think there's hesitation and missed opportunity, but I think it's again mainly because there's a persona for that particular job function that isn't aligned to the knowledge set or the the infinite knowledge available to that particular persona, like we have, um, you know our head of sales in the west. By the way, our sales organization is flipping fire. They're fantastic, but the the, the uh leap from what I currently do to be successful to how can AI augment is just too heavy. And our head of sales on the West says look, we need to be out shaking hands and kissing babies, which isn't wrong. You know you've got to build relationships to get six, seven, eight-figure deals, but the leap to go, you know six, seven, eight figure deals, but the, the leap to go. Hey, before you go into that relation or into that conversation where you're going to shake someone's hand and kiss their baby, go here first and ask these four questions. Just doing that for some reason is a is a real barrier.
Speaker 1:There are tools, though, that you know they're on the road. They have their phone where you can call a number and ask the question. Hey, I'm about to go into a financial services company. You know, here's the person I'm meeting with. What's, what should I be, what are the pain points associated, etc. Aren't there tools like that out there?
Speaker 3:Absolutely, and there's getting to be more of them. My sense is it's a persona shift from what sales used to be, what it meant to be a sales rep before AI, and what it means to be a sales rep after AI. And folks are not making that shift Because, again, back to your, about like not knowing what to do and then actually doing it. You know, we can give a sales rep with a 2020 mentality a phone number to call before they go there, but when they just knowing that there's a phone number call, for some reason there's a disconnect between actually calling the number and asking the questions you should ask before we go into that.
Speaker 2:Part of it, I think, is so many of our salespeople have found success through a certain system that they have developed a personal system, an external system, a Sandler system, whatever that system might be. And when we start introducing these AI tools, it's so far outside of the system initially that it's much more bigger effort than it is for us, who are spending our lives sitting around playing around with AI tools all day, because we have direct applications in marketing to use it right now to solve problems, save time because the process is augmenting the process, not breaking the process. And I think AI for salespeople, in some ways it's breaking their process. As you said, kissing it's hard to scale shaking hands and kissing babies, which is what AI has helped marketing do right To scale, to grow this, and I think that's some of the challenges that they're faced with.
Speaker 1:Yeah, I think it's going to be a stepped process, right? Maybe, before they leave the office and a salesperson's going on a call, have the marketer show the salesperson hey, real quick, let me show you what you can do with chat and pull up the information and I'll print it out. That's step one, so they see the value. And then maybe step two is now you can go to this phone number, because that phone number is absolutely critical. It can be so helpful for salespeople who are on the run.
Speaker 3:Yeah, just in time, positioning based on the very specifics of what you're about to do. I just can't imagine someone saying that's not going to be useful.
Speaker 2:As you said, it takes a level of expertise, a skill set and to build it. That comes repetition, that comes familiarity, that comes success. Success breeds more success and right now they're still trying to close deals by the end of the quarter and finding ways to do that. So where do you see In marketing? You're seeing all this adoption. You're using this as you're applying this. One of the things that you said to your team two years ago was hey, we got 12 months. Now we're in 2025. We're just starting off. We're in our first quarter. What do they need to know by the end of this year? Your team and what's going on? Is it accelerating and changing, or are we at an iterative standpoint? Where get the basics down and there aren't going to be any seismic shifts like there have been over the last two years?
Speaker 3:No, I think it's a great question. I think there's another seismic shift, which is around automation and agentic AI to power automation, and so we're actively looking at some technology and resources to basically look at every function across my organization and say what are the top three things that you do manually that take the most time out of your day and how many hours a day does that take Like every single role and then say, all right, we're going to start with this particular responsibility in your role. That's manual and we're going to use agents to automate it. And as we go through that, what it's going to do is it's going to free up the time of the people who are spending manual resource doing manual things with low impact and elevate the creativity and innovation of the whole organization. So I stood up and I said what I said two years ago. Now this year. This year is about automating the manual activities you do using agents, and we're going to do it by the end of the year. Damn it.
Speaker 2:Oh my, oh my. I think that's a great thing to end on that. Do it by the end of the year. Damn it yeah, hammer down.
Speaker 1:Tim, as they say yeah, that's great. Listen, this has been terrific. I think we could do part two and part three on. Ai as well. So, tim, thank you so much for joining, really appreciate it. Great insight. And, richard, anything you want to say, no, this is great.
Speaker 2:Tim Really appreciate it. It's always great to catch up and to kind of hear the perspective from out in the field of those who are actually implementing it, putting it into practice. So thanks again for being with us.
Speaker 3:Yeah, thanks, guys Fun.
Speaker 2:You've been listening to Marketing 911. Brian Baxter and myself, richard Bliss, have been the co-hosts, joined by Tim Freestone, who is the Chief Marketing Officer at KiteWorks. Hopefully you found something innovative, interesting and insightful. I know that I have, and so hopefully that you have. Thanks for listening. Take care.
