Ep 118: Reimagining Marketing Operations and Owning the Buyer Journey with Lisa Cole

[00:00:09] Hey everyone, it's Bob. Welcome back to Elevate Your AIQ, your go-to source for insightful conversations, human-centric AI readiness, talent transformation, responsible innovation, and the future of work. Today I'm joined by Lisa Cole. She is the Chief Marketing, Product, and AI Officer at 2X, a global B2B marketing as a service firm, and a three-time author who's just released.

[00:00:32] The newest book, The Limitless CMO, tackles how marketing leaders can scale impact in the age of AI. Lisa and I explored how AI is fundamentally reshaping the marketing function, from the emergence of generalist marketers and new AI-native roles, to the concept of brand gravity, which is the title of her second book, and what it means to be discoverable and selected by both humans and machines.

[00:00:56] We also got into the nuances of when to use AI at scale versus when to keep things uniquely human, and how organizations at every stage of AI adoption can find the right approach without losing their competitive edge. I think you're really going to enjoy this conversation as much as I did. Let's get into it, and thanks again for listening. Hey everyone, welcome back to Elevate Your AIQ. I am your host, Bob Pulver, and with me today, I have the distinct pleasure of talking to Lisa Cole. How are you today, Lisa? I'm well, how are you?

[00:01:25] I'm doing great. Great to have you. Great to be here. I know we talked a while ago about some of the things that you're working on, some of the innovation that you're driving at 2X, and you've got this new book out that I want to dig into.

[00:01:42] And yes, I'm excited for the conversation. I thought we could just start with introducing yourself a little bit about your background, some of your leadership roles in marketing, and what you're doing at 2X. You're wearing at least two hats, I know.

[00:01:56] Quite a few hats, actually. I'm Lisa Cole. I am the chief marketing product and AI officer here at 2X. For those of you that may not know who 2X is, we are a global B2B marketing as a service firm. I go-to-market subscription services firm. We basically help B2B enterprises scale their impact without skyrocketing costs or operational burden.

[00:02:20] I have spent my career as a marketing. I have spent my career as a marketing. I have been in marketing or served as a CMO advisor or been a CMO now four times for all the major moments in marketing.

[00:02:46] The websites, mobile phones, smartphones, social media, and now AI answer engines and AI kind of rewriting how we get marketing done. So a nice long tenure there. And I've had kind of one underpinning throughout the entire career.

[00:03:02] I have long since believed that marketing should be the growth driver, market-making growth driver for the organization, but more often than not, they are nothing more than an overworked, underappreciated, bloated, disjointed, underperforming, order-taking function that makes things look pretty. And I think that's a wild underutilization of such a powerful function.

[00:03:27] Yeah, that's an interesting way to frame it. And then sure, we'll dig into that. We'll also, I'm sure, uncover some parallels between your view of marketing and what I've seen in the talent and HR space in terms of order takers and cost centers as opposed to strategic drivers of growth. So we'll dig into that as we go.

[00:03:53] You gave us a little bit of a flavor of some of your remits across some of these spaces, but wanted to dig in a little bit on the AI piece of it for the organization.

[00:04:07] So you say you're the chief AI officer. I mean, obviously that applies. You're going far beyond the marketing function to look at how do all parts of the organization across domains and verticals, et cetera, how that all gets integrated. And of course, how do you enable the people to work alongside of some of the AI capabilities? So I thought we could unpack that a little bit.

[00:04:36] Yeah. Well, first, going back to the organization, and when you think about it, 2X is basically a large enterprise of about 1,400 marketers around the world. So we have HR, we have finance, we have IT. But by and large, it's a very large organization of marketers.

[00:04:53] And so while I lead marketing for the organization of marketers, the big reason why I kind of wear those three hats is that I have a real understanding of what the market needs, what the unmet needs are. So that's why I kind of own the product strategy, the service strategy. But candidly, I don't know anyone in the world that thinks that marketing isn't being completely rewritten by AI. And in two ways, we're getting that pressure in two ways.

[00:05:22] One is how findable and chosen you are by both humans and machines. AI is changing the way that we're buying. Two, it's also kind of forcing us to reimagine how marketing gets done day to day. But for my organization, the ability to apply AI across these use cases enables us to not just create and protect a competitive mode, but also scale as we move forward. And to scale, you have to do so in a sustainable way, right?

[00:05:52] And AI is what's kind of unlocking the potential of the organization to do that. So I sit at the intersection of all three, which is super fun. I'm happy to share what I've learned through that process. So when we think about the changing role of marketers, right? And you've got 1,400 of them, it sounds like, and in different sort of specialties. Yeah.

[00:06:15] I thought we could kind of put that into more context for the listeners, just in terms of just how much it's changing, how fast it's changing. Everyone may agree that it is fundamentally changing the marketer's role, but how does that evolve?

[00:06:34] I know you've talked about, you know, what are the evolving roles of, you know, across the marketing function and where does that position people in terms of their skills? Well, it might help to start off. We're very human-centered in our philosophy in terms of how we apply AI.

[00:06:54] And so when we think about that as being kind of the anchor or the guiding compass, the underlying belief there is that, one, it can take just an employee's strengths and magnify it in such a way that they can do more of that strength faster. The other thing is that, by design, if used effectively or applied effectively, it also addresses a gap or a weakness that those employees can have.

[00:07:19] It can help get them 60 to 70 percent of the way on the gap that they, you know, couldn't be able to support before. So we are seeing a shift to more generalists. That's kind of the first thing that we're seeing. We are, you know, when we think about recruiting talent, we recruit about 80 to 100 marketers a month because the nature of our people being embedded in other organizations. We now have to really focus on soft skills, right?

[00:07:46] So are they open to, do they do well in an ongoing changing environment? The capabilities of AI, it's not advancing once a quarter. It's, I'm sure you've seen this. The technology's advancing every couple of weeks, like meaningful step changes. The things that you literally can't accomplish today, if you hang on for a couple weeks, chances are you'll have an entirely new capability. This is especially true in marketing.

[00:08:15] So we are looking for those that are comfortable in an ever-changing environment. We are looking for those that are very, very passionate about just ongoing continuous learning. Whether the company mandates it or not, they actually lean in and make a fairly significant commitment to just educating themselves. They're tinkerers by design. And these are people that like to test and learn by design, regardless of the roles that they're in. They apply their learnings in a very real way.

[00:08:45] So these are kind of the big things. The new emerging roles that we see in marketing, they're fairly fascinating. They're the builders. And so we are seeing anyone that managed automation before becoming AI engineers or AI automation specialists. They might have been managing marketing tech stacks or technology integrations before or sending the email, so to speak.

[00:09:11] Now they're actually shifting to building these hyper-automated workflows in N8N or in Cloud Code, as an example. We are seeing people that were formerly copywriters and content writers that are excellent prompt and context engineers. By design, they know how to give really good, clear instructions to help a model be able to execute a task or a series of tasks.

[00:09:36] Additionally, we are seeing data scientists, so data analysts now are, you know, with the help of AI, now they can up-level from maybe data enrichment. And now they're thinking about building these knowledge layers that are informing what AI models are doing on your behalf. So we're seeing a shift. There'll be some body of work that'll be fully automated where humans aren't needed.

[00:10:02] We are seeing new bodies of work, new capabilities and needs that are leading to these new jobs. And people are kind of getting up-skilled or re-educating to move into those new roles. And we're also seeing even the skeptics becoming those that are providing human oversight to make sure that nothing that gets up to market is slop or inaccurate, right? Protect the organization from risk. So that's just how I see it evolving so far. And I think that's probably true in other functional groups.

[00:10:32] Yeah, I think it absolutely is. It's refreshing to hear someone talk about how they've got everyone sort of moving in the same direction. As you bring out new talent, you're already sort of vetting for some of those competencies, I would say, as well as having the right sort of learning and growth mindset so they can hit the ground running.

[00:10:58] And then you mentioned where there might be some skepticism around what's actually being produced. I was going to ask you about on the client side, since you are providing this as a service, any concerns or pushback from clients in terms of who or what is creating some of the content? Or you've built enough trust that you know how to do it right?

[00:11:25] Well, whenever we start working with any client, we start full disclosure and we follow their lead, right? We have three, and I think this is true of all organizations. I think organizations fall into one of three categories. There are those that are already leaned in. And let's not take AI native companies yet, but there are those companies that are really truly shifting to being AI forward. They probably already have an AI strategy. They've got data usage guidelines.

[00:11:54] They might have even invested in their own technology, like their LLM of choice. They've already made some critical decisions. They've brought training and development in. And in that scenario, when we start working with them, we follow their lead. Our people operate within their environment, with their strategy, with their privacy and guidelines. I think the important piece is it's full disclosure, and they dictate how we work to ensure that it's consistent with the org.

[00:12:22] The second environment, these are the companies that are still trying to figure it out. They're usually in some sort of panic state, like I need to do more with AI, and I don't even know where to start, and I have AI everywhere. In that scenario, it's a, here are the use cases that we can apply AI to. We have access to the tech to do that, or you can go and get your licensing, and we operate in your environment, but we have to have that conversation up front.

[00:12:49] And then there's a third category where companies do not want AI used in any way, shape, or form, particularly for marketing, where they think about IP. They think about, you know, they're really protective of their brand. There's real belief that what goes out in the market, that's their competitive advantage, and so they don't want to use any AI. And so in those situations, we brick those laptops. Like, you quite literally, you can't go to the domains of the core LLMs,

[00:13:20] and that's, I think that's what we have to do. It's the right thing to do. So it comes back to full disclosure before we actually use it. Yeah, I mean, trust is everything, as you know. So, you know, you've got to, I think that's a pragmatic approach to just kind of follow their lead. I would imagine as they get more exposed to the responsible use of AI themselves,

[00:13:47] in other contexts, you know, they may change their tune and shift from one of those categories to another, at least with some trepidation, but perhaps optimism that there's efficiencies and perhaps even some, you know, increased effectiveness that they can have if they start to move in that direction. And that conversation basically is, we started with, well, what should be uniquely human? Like, what, from your perspective?

[00:14:15] And then of those things that don't need to be uniquely human, what role should a human provide in oversight? What does that look like? QC checks, you know, periodic review for errors and output, stuff like that. And then over time, we find that there tends to be comfort once they have been able to kind of shape what's uniquely human, what requires human oversight, and then, you know, how you would monitor that for ongoing, you know, performance and output.

[00:14:45] Once they see those kind of guardrails go in place, they tend, and this is true of anyone that's using AI, believe it or not, the guardrails are what's actually unleashing it. It's the absence of guardrails that people are just so afraid. Right, right. Now, when we talk about AI, obviously there's just a definition of that can get sort of muddied these days.

[00:15:08] But when you say they're apprehensive about AI use, is that like generative AI use in terms of the copy that's created? Or is it everything that might include, you know, automation in terms of, you know, outbound, you know, communications of some sort and things of that? And they're nervous about even that, sending the wrong messages to the wrong people, that kind of thing. Yeah, I think it's actually all of the above.

[00:15:37] So it tends to start with how is AI used to surface actionable insights and how reliable those actionable insights? Can we rely on that? And what role should the human play in that? The second is gen AI. And when you think about just the copy and imagery and all those assets that might go out in the market. The third is it tends to be automations where there are direct interactions with your target audience, right?

[00:16:05] The humans that you're intending to influence and build trust with and drive engagement with. I would offer that it kind of moves in that direction. We have some comfort with data analysis, assuming that there's no proprietary data or confidential data that gets used, that the AI model gets access to. They tend to get pretty comfy with production or creative production of assets.

[00:16:30] They tend to, the last frontier is the direct interaction with their audiences and not having a human in the loop there. So SDRs or through chatbots on websites, they tend to, that's usually the last frontier where they would rather those interactions be like human. Yeah. With the underfearble, that's like the last frontier, that's where the brand perception gets defined, right? It's in those interactions. Yeah.

[00:16:58] I mean, I think we all see that every day in our inboxes. We think we can tell when something was written by AI or, you know, I'm critical of even someone that didn't sequence their messages properly. They're following up too quickly or, you know, anything like that. I just kind of know as personal as it may sound, there's no way that a human should have set up this, you know, three part, four part. Hi, I'm Carmen Hudson.

[00:17:27] I'm the host of the Recruiting Book Club and we're starting our second season. I'm so excited to bring to you another set of guests of recruiters who have written books. We are excited to have some very special guests this season. We've got Shally, we've got Craig Fisher, James Ellis and quite a few other people that we're going to bring on board to tell us about what they wrote, why they wrote it. And maybe we'll veer off into a conversation about recruiting on all types of topics and subjects that happen in our industry. So I hope you can join us.

[00:17:57] I'm excited. You know, outreach sequence in this way. So I'm skeptical kind of across the board. So I get it, especially if I had a more valuable brand than my personal brand to worry about. But one of the things I also obviously think about when it comes to marketing is, you know, these innately human attributes and skills around storytelling and curiosity and creativity and things like that,

[00:18:24] that all play such an important role in the marketing function that to displace or even discount that is, you know, I think that can inadvertently and perhaps indirectly, you know, lead to, I guess, a lower level of trust. Yeah, absolutely. I agree.

[00:18:44] When you think about, and that's back to that, you know, having the conversation around what should be uniquely human, the deciding what to say and how to say it, those point of views that you're putting out in the market and how you say it in such a way that actually when somebody consumes it or they hear it, that that continues to build trust between the brand and that human. That should be uniquely human. And, you know, by the way, that's your secret sauce.

[00:19:14] That's your source of competitive differentiation. So not only should it be uniquely human, it should also be in-house. It's also not something you should be outsourcing. Like, that's your secret sauce. Now, what it takes to build real, I call it brand gravity, and it's the strength of the brand in such a way that you are both findable, understandable, and chosen by both humans and machines.

[00:19:40] And their moment of interest, likely when they're researching how to solve a challenge. They're doing so anonymously. To get the kind of brand gravity you need to reach those people when they are anonymous and to be findable in all of these watering holes and understandable by both the agents they might be using or themselves. There's a level of scale there that usually a human team can't do without AI.

[00:20:08] It could be taking this core big rock asset that has your point of view, your white paper, your research that you put in market, the way that you think. Anything that kind of demonstrates the way that you think and how you act. That asset needs to then be repurposed in a number of derivative assets that then need to be presented in a variety of formats so that both humans and machines can read it and understand it.

[00:20:36] This was true even with traditional search, right? That's the smartest way to think about what's uniquely human versus where can AI help do that at scale at a much lower cost and much faster. And if you're smart about it and you kind of go through that decision, that's where you apply AI. It's in that second piece. Yeah. So you had already been working on this. I guess I wanted to shift now that you've introduced the concept of brand gravity.

[00:21:06] I wanted to congrats on the book. And I wanted to dig in a little bit further to what you wrote about and all your experiences that led to this, everything you were just starting to go through in terms of the concepts, the fundamental principles there. And then how does this drive, how does this in conjunction with AI sort of move you towards this sort of marketing reinvention, I'll call it.

[00:21:32] There's two books, the first one's Brain Gravity, and it was written about a year ago. It was written in response to four studies that were published by Winter, Sixth Sense, and a couple of other research firms that had finally done an updated view on how do companies actually buy from other companies.

[00:21:49] And the data that basically came through in all four completely independent research was that most of the research, evaluation, and decisioning is happening long before they'll engage directly with your brand. And it's happening anonymously. And I mean, it's something staggering to the degree of 85% of the companies that really, by the time they reach out to you, they've already got their finalist list.

[00:22:19] And it's like 92% of the time, they end up buying from the preferred vendor at the top of that finalist list that they had baked before they talked to your sales rep. And I thought, okay, that's pretty telling. So if you're not findable, understandable, and chosen before they even talked to your sales team, then what are the implications for marketing?

[00:22:41] And that's where Brain Gravity came into saying, okay, if we know that this is true, and we believe four different research studies have demonstrated this, the basic concept is this. You will need to build a significant amount of digital mass in all of the places your buyers could potentially be asking questions so that you can draw them to you and keep them with you until they make their decision and they raise their hand.

[00:23:10] Well, in order to do that, you effectively, one, you obviously need to be clear about what you want to be talking like, what questions need to be answered and what your point of view is. But then it's a matter of, and that's where you need to gain insight. These companies launch into orbit, and I'll just bring in the digital universe here. You now need to have visibility when they get there. And then once you're there, you need to make sure that you have enough digital mass that answers all their questions, makes it easier for them to kind of get to it.

[00:23:40] Aha, that's how I should solve it. And then it's a matter of making it easier for them to engage with you and then validate what they've learned through the research process when they're talking to sales. That's the premise of gravity, brain gravity. The book I'm about to release, it actually releases next week. It's called The Limitless CMO. And that is talking about how do you actually scale marketing so that you can execute on this without skyrocketing costs.

[00:24:10] I mean, most marketing leaders have, and I'm sure this is true of HR, finance, IT, you have much fewer resources than the expectations assigned to your function. And so how do you think about, in the age of AI, how can you actually use the limitations that you face and turn them into the things that free you of all your constraints?

[00:24:32] So can you leverage AI in such a way for scale so that you can build enough digital mass and at the same time for your in-house people to put out more smart and helpful content to build your brand? So that's how the two work together is one's an operating model for how this stuff gets done. The first one is, all right, if you know that the world has changed, what do you need to do differently?

[00:24:57] So the other functions within an organization, I mean, I feel like there's some overall enterprise, there's data and perhaps AI maturity that would coincide with that sort of enablement. Right. Because now you've got to pull in context from those other domains.

[00:25:20] You've got to think about perhaps, you know, incentives if necessary to make sure that people are sharing, you know, data that's in context. You know, the insights that you're gaining from the market, obviously, you've got, you know, customer success teams and various other places.

[00:25:39] And so, I don't know, I feel like you've got almost like an embarrassment of riches, like having everyone, like we talked about before, like sort of rowing in the same direction. They're on board with what you're doing, but you've also got the purview to pull all those, you know, originally disparate pieces together to, you know, sort of move forward in a cohesive strategic direction.

[00:26:07] Do you, am I off base? I mean, it seems like larger organizations would aspire to be able to do that. I don't know that I feel like I have an embarrassment of riches, but I can appreciate what I do now for. I have, so I have a small marketing team of 16 within this broader organization of 1400 that are embedded in enterprise orgs.

[00:26:32] So, those, I lead marketing for the company of marketers that are actually doing the work of other enterprise orgs. So, I have insights to what is happening, what's working well, what's not working, right? And I'm working with those embedded marketers to help them influence how those organizations are applying AI to their workflows. So, I appreciate that, those insights.

[00:26:56] Now, I think the things that I do get to benefit from because of the org size that I'm in and just by design wearing the three hats, I get the market insights which inform the product strategy. And then because of the market insights and the product strategy, knowing that AI has to be such a big part of how marketing gets done and what we really are as an execution engine for those B2B orgs, they work well together.

[00:27:25] I don't have to deal with silos to be able to execute against those three strategies. I think that's the thing I benefit most from. But I don't know any organization that finds it easy to build that knowledge layer. There's a lot of unstructured data embedded across an org, call transcripts in your Salesforce, in your email, in Slack and Teams channels.

[00:27:51] All of that data is what actually provides the context to eliminate the possibility of AI slop. The organizations, though, that I have seen make an investment in really figuring out what that knowledge layer should look like and where the data should be coming from. It doesn't take two years to build a relational database. Now it's a matter of just getting it to the same watering hole and romantic search, right?

[00:28:19] But figuring out what that looks like and bringing that together, that's the secret unlock to really unlocking the potential of AI. That's my take, regardless of what functional group you're in. I know, I agree. The insights piece, I was curious about how that comes together. It's been a while since I did my social listening and social media analytics work at IBM.

[00:28:48] It probably goes back 15, 20 years. So I was curious what that might look like these days as you gather that market insights and the social insights from all the channels that might be relevant to 2X as well as obviously to your clients and how that sort of feeds into, I guess, your data infrastructure and how people sort of access that.

[00:29:13] Like you said, once it's all brought together into one place where you can sort of, I don't know, you've just got this cross section of insights from whether it's competition, potential new markets, new target buyers, you know, all kinds of things like that. I think first it's a matter of figuring out obviously what are the valuable sources. We're surrounded by signals, right? All over the place.

[00:29:41] There are intent signals that we are getting from platforms. There are third-party signals like what clay could serve for us. Those are our own, you know, first party, our own direct interaction signals. And then within the org, we have all of this unstructured data.

[00:29:59] We have data scientists that actually help us actually build these vector databases that could be integrated or, you know, our agents and agentic workflows can reach in and out to use this knowledge layer. What we don't do is we don't have one unified platform with multi-client data tenants. We're not, you know, we're not Accenture Song or we're not, I think Publicis also has all of their client data in one platform.

[00:30:29] We don't have that. We operate within our client's environment. So the way that it surfaces probably more manually than you might imagine, like where we connect dots across multiple clients and see what's surfacing. I think that's probably the one constraint I'm dealing with. I don't have a unified platform with everyone's data brought together. I have mine, if that makes sense. Right. Yeah. Right.

[00:30:54] And at the intersection of AI and that market insight, I was curious if you ever use like synthetic data, like synthetic personas for target buyers. We have used synthetic data for personas. We also have mock focus groups and this is for faster tests and learning of messaging and offer strategy for sure.

[00:31:21] And it, it hit or miss in terms of whether or not it's been very valuable. I have found the mock focus groups have been really valuable in developing overarching campaign messaging architectures. Okay. I, I know this is the buying influencer group and they all are wildly different. And so how do I actually develop a campaign with messaging arcs for each one?

[00:31:48] That has been much better than trying to get all of that with actual focus groups. The period of time and the cost associated with really understanding that buying group, it's nearly impossible. Certainly within most marketers' budgets. Right. So the, I thought the mock focus groups had been good. Others have been using synthetic data, you know, for their ad creatives. Anyways, but it's better.

[00:32:17] It's better waiting 90 days, 120 days, 180 days and spending, you know, a hundred thousand hours to get for sure. Yeah. I mean, I was thinking about focus groups cause I was behind the one way mirror for some of those in my heavy market intelligence days. And then I was also just thinking recently, Josh Burson was given a keynote at this Unleashed conference I was at for HR tech a couple of weeks ago.

[00:32:44] And he was just saying like, what's, what's the value of sending out a survey now? Right. Like, do we need, still need to do that? Does it still have a place in your portfolio of, of insights? I would argue for a period of time it does, but as you know, well, surveys are a point in time, you know, potentially emotional responses or whatever you're feeling that day.

[00:33:09] And maybe there's a, some kind of incentive at the end of the survey and someone's not really filling it out, you know, honestly or what have you. And so there are shortcomings to services or always have been, but, but there are ways to at least compliment, if not, you know, supplant what you can do with that. Yeah. I think the concept that we're all going to have to get used to in the age of AI is this notion of good enough. What does good enough look like? And what are the trade-offs for good enough?

[00:33:37] And, you know, when you kind of look across all the use cases that you would need that data for, what's informing and, you know, what risk gets introduced if you're not actually asking your target audience themselves in that. And, you know, when you think about ag creative, there is such a thing as good enough that likely leads to a business case of getting there faster, right? Speed to market matters.

[00:34:04] And being able to free up dollars that would have spent on the market research or the buyer research to put it into the actual testing, a greater set of versions of ads. Maybe in that case, synthetic data is good enough. The use case podcast is where technology vendors get to talk about themselves.

[00:34:25] And it's a wonderful place for vendors, investors, and practitioners to listen to the story of the solution, the features, the benefits, the attributes, et cetera. And we get to know the CEO or founder during the call. And we also get to know the tech. So subscribe to the use case podcast.

[00:34:46] Because it does by design, that decision enables you to get there faster and free up dollars that you would have otherwise spent on that activity. But maybe as an organization, if you need to reposition your brand and you need to make a long-term decision and how to do that, maybe it's you in an acquisition strategy and you have to make smart decisions about the equity that exists and how you migrate that over and then reposition yourself in market.

[00:35:17] Maybe there's so much risk in getting that right, you should probably talk to the humans. But I think that all comes back to, are you okay with figuring out what good enough is across these things? What's good enough for an email that gets sent out to invite somebody to a webinar? It might be wildly different than the data that you might use to reposition your company into a new category. So that's how I would think about it. Yeah, it does get down to the specific use case for sure.

[00:35:45] Yeah, I mean, I think about that a lot. I was just exchanging messages with a former guest who just wrote another book about storytelling as this super skill for the next generation. And he just launched a whole book of Substack, some courses and stuff like that. And I told him, I signed up as a paid Substack subscriber.

[00:36:10] I said, just so you know, you are my very first paid Substack subscription because this is important to me, right? It's important to me as a content creator and someone who cares about what they put out. I mean, I get stuck all the time. Like, how much do I really want AI helping me? I don't want to be a hypocrite. Here I am with this show and using my voice to talk about responsible AI and human centricity and human potential and all these things.

[00:36:40] And so, you know, I'm very selective about where I choose to use AI in my own communication. So I absolutely understand the sensitivity to it, especially as someone's trying to build and enhance their personal brand. And that brand shows up in all those places that you suggested, right? You've got to stay, you know, top of mind. You've got to be in all the places that people might go to do their research or, you know, wherever it is.

[00:37:09] And that way, you know, human psychology sort of takes over and gives, you know, you've got a little bit of a bias towards, you know, the people who are sort of not necessarily just like omnipresent, but seem to be to know where that their value aligns with what you're looking to achieve. Yeah. I like that you use the word omnipresent.

[00:37:33] One of the things that's fascinated me over the last two years is how AI native startups have been stealing share of attention, mind share, market share from these really trusted industry-leading brands that have been industry-leading brands and trusted for decades at this point. And one of the things, they have two things that seem to be their secret sauce. One is that they're building in public.

[00:38:03] So they're putting everything out there. They're not filtering it like a corporate brand might do. And by design, you consume a lot of that and you realize I trust them so much that when I finally get on the phone with them, I'm just going to buy from them. Because I believe them when they say they can help me solve this challenge. So that founder-led, creator-led brand is stealing from these trusted corporate brands.

[00:38:30] The other thing, which comes back to the omnipresent, they have figured out a way to leverage their AI first, their AI native in nature. They have figured out a way to scale their presence across all of these channels. But the original underlying thoughts and point of views, they're all theirs. So they've just figured out a way to become omnipresent without outsourcing the whole job to AI.

[00:38:59] They're using AI for an advantage, a scale. For example, I used AI when I was writing my book not to write the book, but to interview me. I love going on long car drives. And my favorite thing to do with ChatGPT was I would give it, I want to talk about this topic in this chapter. This is the thesis for this chapter. Here are three questions that I want you to ask me one at a time.

[00:39:29] And then as I answer these questions, transcribe it, ask me follow-up questions. Dig in deeper where I can clarify the concepts. So I would go on these 45, 50-minute drives, and I would get all my thoughts out related to that chapter in this interview with somebody that sounded like a human to me. And then I would take that, and it was basically a vomit draft, so to speak.

[00:39:56] And I would go back through and say, okay, totally long-winded here, not relevant here. Wow, that's the framework that I've been using repeatedly through the years that feels valuable for this chapter. That's using AI, but it wasn't outsourcing the thinking to AI. It was helping me do it at scale. This book has 28 chapters. It took me a year and a half to bring it together. It's 49 frameworks. And so I use it in that way.

[00:40:22] Other people use it in a way to take a core asset that is all they're thinking and then find a way to repurpose it in 100 derivative assets so that it is findable in different places. You're just going to make that decision in terms of what people would expect from you and your brand. But you also have to recognize that these AI-native companies are operating with an advantage. No, I love the use case. I've been trying to do more voice interaction.

[00:40:51] I know some companies have, I forget what company, I think it was a company Every, they had their people do like a two-week experiment. They were not allowed to touch the keyboard unless absolutely necessary. Everything had to be done through voice. I've got to start smaller than that. I mean, that sounds pretty aggressive to me. I don't know if I could do it. I've not done it. But I do. But I have tested whisper. I'll use whisper all day.

[00:41:19] But I don't think I've gone a period of time where no typing. I don't know. I realize, especially being neurodivergent, I definitely, my brain is moving faster than my fingers could possibly type. So I don't know why I haven't, you know, gone into using voice sooner. But I know that I need to do that.

[00:41:42] And if I have aspirations to write a book myself on top of everything else on my plate, I've got to make that a habit. Right.

[00:41:54] And I think more people will get more value from that type of interaction, not just because that's just a better, more efficient way to do it, but because you actually get a lot more out of, you know, just expressing yourself verbally. You can always clean it up.

[00:42:14] But being able to do that, and this comes up all the time when I talk to people in the talent space because AI interviewers and interview intelligence tools and things are becoming almost ubiquitous at this point. And so that's one of the advantages, not just the three-dimensional aspect of understanding how someone works and how their brain works and things like that, but just because you can express a lot more, you know, through voice.

[00:42:44] And if AI can capture that effectively, then that's a huge bonus for the way you work. I have been on the job market for a couple of years, but I do a lot of hiring. Anyways, it sounds like a fast saying, me too, for sure. Yeah, I can give you some recommendations after this conversation.

[00:43:05] But, yeah, I mean, it's, you know, without getting too far into the talent acquisition, you know, issues, the fact is, you know, there's more applicants for every job than any talent acquisition team can possibly handle. So what are you supposed to do? How are you supposed to give people a fair shot and avoid, you know, ghosting great candidates without giving them an opportunity to express themselves and add a lot of color to their resume? So that's the premise.

[00:43:35] But there's a lot of rich insights that you can get from that. There's a lot of context and nuance from that. So hopefully they don't use AI in that interview and they're using their own brain. But it goes back to your original point around, you know, transparency and say, you know, what are the expectations? Here's how we use AI in our, you know, recruiting process. This is how this is how we use it and this is how we expect you to use it.

[00:43:59] We will tell you when it's OK to use AI for some phase of the interview process. But if you don't see us tell you it's OK to use AI, then we expect you to use your human brain and your judgment. Yeah. So. So one of the other things I wanted to ask you to ask, I mean, you support clients across the globe, right? You're not just us.

[00:44:24] Yeah, we so we work with B2B enterprises, mid-market enterprise organization that happen to have their headquarters in the U.S., but more often than not have a global footprint. That's the first piece on that land. So we are working in these larger, more complex marketing organizations that they themselves have in-house team of marketers in different regions. We also the nature of our model is an offshore execution model.

[00:44:52] It's part of where leverage gets created for the leaders that kind of embed our resources in their team. There's a bit of a cost savings and it also kind of frees up dollars to put money into programs. With that, we have our 1,400 marketers are in Malaysia, they're in Manila, and we have another 150 or so that are in the U.S. Where onshore collaboration throughout the workday is required.

[00:45:21] The near shore, Manila is where there's some collaboration on a daily basis, some overlap. And then the Malaysia, that's where you're looking for kind of 24-5 around the clock, so to speak, execution work. Where less collaborations needed, you know, deploying emails, creative production, copywriting for assets, stuff like that.

[00:45:46] But in all of that, you're dealing with two global organizations working together. Yeah, I guess I was thinking about just perceptions of AI use and going back to your three categories of, you know, your client's sort of comfort level with AI or where they are on the adoption acceptance scale. And whether or not culturally there are places that you need to accommodate.

[00:46:13] And just in terms of your 1,400, but also just because they're embedded, you know, the culture of those different organizations around the globe. Well, I think regardless of what, whether AI is involved or not, you do need to think about and be aware of cultural dynamics, right? I was a former customer. And when I was a customer, my team that I was working at, a third of my team was based in Israel.

[00:46:36] I had Germany, France, Italy, U.S., Singapore, large, about 19 or so countries that I had in-house marketers interacting with Malaysia and Manila. And there are cultural dynamics even between those countries. So my team in Israel, Israel and Malaysia, they have their own unique dynamics that you've got to navigate. On top of that, you layer AI in.

[00:47:02] And there is, you know, depending on the country, depending on the region, there are different levels of tolerance for technology in general. Now, 2X picked Malaysia and Manila because it was the highest of the rankings from an English proficiency.

[00:47:20] And where our locations are is it's actually in the university hotbeds within those countries that have marketing as a either marketing or technology as the core educational path. And so by design, I think Tuwax kind of stacked the deck in the favor long before AI kind of settled into marketing.

[00:47:44] Because B2B marketing, by and large, is very much more of a science with a lot of complicated technology. AI was just the thing that kind of adds on. But you could, you do need to be thinking about India and Poland and other offshore options and whether or not they're B2B tech, B2B technology and AI. That's a couple of things you've got to consider. Yeah. Yeah, for sure. Sure.

[00:48:13] Well, Lisa, this has been great. Thank you so much for spending some time with me. Really amazing work that you're doing. Really fascinating topic. And I love how you're leaning into human centricity and all these great attributes that I know you want all your marketers to have. And the fact that you're bringing on people that are sort of AI literate from the get-go and have the right mindset, I think, is probably half the battle right there. So it's amazing.

[00:48:42] And congrats on the new book. Congrats on Brand Gravity. And congrats on the new CMO book coming out. What's the date it releases? April 6th. Awesome. Yeah. Excellent. I will, if you could share a link to the book with me, I'll include that in the show notes of the episode so people can find it. I will. It'll be available on Amazon on April 6th. But what I'll do is I'll send you a link to my author website, my company site, and there are links to purchase from there. Awesome.

[00:49:38] And if I can, I'll just kind of close out. People have not stopped talking about it for two months. If you actually know your workflows and can taskify it in such a way that you can explain it to an intern, then it's very easy to apply AI to accelerate it. So just roll up your sleeves, figure out how the work gets done, and then add it on to that. That's perfect closing thoughts. Thank you again, Lisa. I really appreciate it. Thank you. And thanks everyone for listening. We'll see you next time.