← Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
The Evolution from SEO to GEO for Modern Marketers
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- [00:00]
A
The Voices of Search Podcast is a proud member of the I Hear Everything Podcast network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice then visit iheareverything.com welcome to the Voices of Search Podcast. A member of the I Hear Everything Podcast network, ready to expedite your company's organic growth efforts. Sit back, relax, and get ready for your daily dose of search engine optimization wisdom. Here's today's host of the Voices of Search podcast, Jordan Cooney.
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B
I'm Jordan Cooney and joining me today is Lisa Adams, AI advisor and go to market strategist at Growth Path Partners. Liza, welcome to the Voice of Search Podcast.
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C
Jordan. Thank you for having me. Excited to be here.
- [00:56]
B
Likewise. I am thrilled to have you for a variety of reasons. One of them is you have got a plethora of experience working across a variety of different industries. And I think that it's, it's great to have folks with, with a totally different perspective. Right. So so many of the individuals right now in, in the tech space are just really barreled into a very, you know, myopic view of how AI is, is impacting their world. And your experience is, is much broader than that. So tell our, tell our listeners a little bit about where, where you're coming from, what you've been doing and then what, what you're, what you're planning to do here as you've been building up Growth Path Partners.
- [01:42]
C
Yeah. So again, thank you for having me. So I'm Lisa Adams. I'm based here in Boulder, Colorado. Been here for over 25 years. But half of my career was spent in Silicon Valley. Never really moved, but I did the commute, Jordan, you know, out on Mondays, back on Thursdays until Covid. So I've spent a big chunk of my career in big tech. You know, Juniper Network's now part of hp, broken up, part of Broadcom, Pure Storage. I was in SAS for a while and Smartsheet, and then I was also in telecom for, for a long time, WorldCom, now part of Verizon. And so I've been through every single inflection point in the last few decades, we won't say how many decades. Right. And I've always been in senior marketing executive roles. My last corporate role, I was CMO of the company. And you know, now I am, you know, quote unquote, retired from corporate life and truly pursuing my passion. Jordan. My passion actually isn't AI. When I Exited my last company. I wanted to serve on boards and so I thought about that as my post operator role. But I found out that There are only 41 marketers and Fortune 1000 boards and less than 3% of all board members have marketing experience. Experience. And I dug in and found out that there are many reasons why we're not on boards, but one of the biggest reasons is that we're perceived as tacticians rather than strategists. So my passion now, Jordan, is to elevate the strategic value of marketing, use business as a force for good and ensure diverse voices at every table. AI is not my passion. AI just happens to be a means to an end and it's an amplifier of those passions. So I am, you know, what I do now is I'm literally helping marketing teams and go to market teams transform and go through their AI transformation journey. When we no longer will have just human teammates, we will now have a combination of human and AI teammates. And I'm inspiring them with what's possible not just in their function, but also across functions.
- [03:58]
B
And I love this because you've transcended throughout a variety of different eras of how brands would communicate through these channels. Right. And AI is just one of these new channels. And I think level setting on that perspective is, is really critical for us as we're going through this AI transformation. Tell us a little bit about how brands should be thinking about this channel. What are some of the tactics that have we've always used as brands and marketers to ensure that AI is conveying what is needed about our brand.
- [04:38]
C
Yeah. You know what's interesting, I get this question quite a bit, right. Like how should we use AI? And I tend to back off a little bit and say let's peg this on what is happening to our customers. For us marketers, you know, that has always been our North Star. If we start with AI, then it feels like AI for the sake of AI. But when we start with customers and how their buying behaviors and their buyers journeys are changing and we deeply understand what's happening to them, then we can better figure out how we can use AI to better serve them. Right. And if we look at the, the buyer's journey, there's this stat from martech.org that says that the go to market efficiency has declined from 78% down to 47%, meaning that less than 50 cents out of every dollar that we spend in go to market is yielding good results. And I believe there's many reasons, but one of the biggest reasons is that our Customers have changed, our buyers journeys have changed. Like literally. It's no longer a linear buyer's journey. Right. When you do search using AI, AI looks everywhere to find information, to find patterns, and whatever patterns it finds is what it serves up. So it no longer is just looking at our websites. It's at customer reviews, social publications, analyst reports, even Glassdoor. And what employees or candidates are saying and what it's looking for is patterns. And once it finds a pattern, that becomes signal. Right. So if you think about the buyer as buyers, we no longer have to do Google searches. On each one of these, we ask a question based on our problems and we ask what the top three. Give me a short list based on my situation and rank them on the following criteria and overall, give me the pros and cons of each one. And what would you recommend? It will actually do that for us. Right? So that's a huge shift. The other shift also is it's no longer just relying on individual teams in our organizations to serve the customer. Customers actually don't care about our silos. They only care about a singular experience. They want to experience one company rather than multiple, what feels like multiple companies. When we get passed from marketing to sales to ces, right. That is also a big shift. So I think, you know, as we think about the expectations of customers and how their buying behaviors have changed, then we can now figure out how we can better serve them using AI.
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B
I love this because this is a first, very central to a theme that I don't think a lot of marketers have grasped onto, which is focusing on your customer and the full journey, both once they become a customer, customer as well as before they become a customer, is, is absolutely critical to winning in AI. As you think about this, this, this buyer journey changing and how that buyer journey has changed, what are some of the signals that marketers should be looking at that your customers are going or not going to your brand to seek out their, their services or products? What, what kind of data should we be looking at? What kind of inputs should we be considering?
- [08:04]
C
Yeah, so what's super interesting, Jordan, is that many tend to over pivot on visibility. They always ask, many ask, how do we show up at AI search? How do we ensure that our answers are actually sighted? I think that is the floor of what our expectation needs to be. Showing up in AI search is just step one. We actually need to be believable and credible, meaning the sentiment of what is being served up by AI. So fine, we're being served up, but what if the Sentiment is wrong, or it's not believable, or it's not the right thing. Right. So we need to solve for that. And then the last thing, which I think is even more important is are we being recommended for the right things? So, yes, we show up. Okay, yes, it's good sentiment. But are we being recommended for our ideal situation, the ideal problems, and for the ideal customers? And some actually challenged me on that last one because they're like, well, we just want to be recommended. And my thinking is, well, what if we're recommended for the wrong customer that we can't serve really well, and ultimately they're dissatisfied and they churn and then they say bad things about us online. And now AI sees all those bad things being said about us, then we now have a very different problem. Right. It, it actually feeds the system because AI essentially doesn't solve problems. It amplifies what's. So whether what's there is good or bad, it will, it will serve it up. Yeah.
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B
You just mentioned this amplification piece, and I think this is what I like to coin. Visibility. Right. Everyone's talking about AI visibility. And really, visibility is just a way of painting the picture of how amplified a particular brand or a particular message. In some cases, because a message could have a positive, negative sentiment is being shown inside of AI. As, as you've worked with different brand teams, different marketing teams. What are, what are some of the common strategic failures that teams have overlooked when it comes to ensuring that the message is clear, that the, the, the, the customer's voice is heard? And I'm not necessarily talking about, like, what ends up showing up in AI, but like, what ends up showing up in our customer support documentation, what ends up showing up in our pricing pages, what ends up showing up in our, our web content and our marketing strategy. What ends up showing up in our TV ads that we produce as marketers and ensuring that the customer's voice is being seen and heard in those, in those marketing channels?
- [10:49]
C
Yeah. So you hit the nail on the head. This is all about deeply understanding the customers. We get that. Right. The rest kind of, you know, falls into place. Right. And when I talk about deeply understanding the customers, start with anticipating what their questions might be throughout that journey. Whether it's, you know, somebody who doesn't know you, whether it's someone that you're trying to upsell or cross sell, somebody who might be evaluating what are some of these questions that they might be asking and what's interesting about that? It's never been easier to figure those out. Right. Because now we have AI to help us figure that out. So we have customer reviews where it could be very apparent what some of these questions might be. We have all those customer surveys. We have the gong calls, the sales are, you know, they're conducting calls with customers. Like, as human beings, it's very hard for us to take information from all of these sources and distill it and, you know, identify insights from that. But use responsibly. If we make sure that we don't have any of the proprietary information or personal information in there, feed it into AI and figure out what these top questions might be in the language that the customers are asking. When we understand that, then we can create the content that uses their language and it addresses those questions. The other key thing there is not just about the content or the message, but it's also about the watering holes. Where are you going to put these things? Right? And it goes beyond just our website. You know, it's. It's engaging in communities, it's Reddit, it's LinkedIn, it's publications. And, you know, in the past, some people used to say that PR is a cost center. I actually believe that PR has never been a cost center. It's always been a growth engine for the business because PR is ultimately trying to find places where we can add value and build trust. And I think the more places that we're in talking about how we help solve customer problems and then ultimately others amplifying that on our behalf in other communities and in other channels, that gives AI lots of different sources to find this information and then ultimately figure out the patterns that are consistent and then that becomes signal for the response.
- [13:20]
B
You brought up trust. And in our prep sessions prior to this podcast, you mentioned this development that you've been working on. And I think it's really critical for our listeners to really understand this concept of visibility, sentiment and recommendation. And in this new framework, how should we be thinking about GEO AI? Why is visibility, sentiment and recommendation critical for marketers? And what are these three layers when it comes to trust?
- [13:51]
C
Yeah, I think underpinning all those three layers is trust. Right. And it's one thing to chase the algorithm. And people always ask me, so, Lisa, what should we do technically and what tactics and all of those things, There are certain things that you can do to essentially game the system. Right? But if ultimately we are not landing the message, we don't have the right positioning, we are not targeting the right audience, we are not. We don't have the right offer like we we don't have good product market fit. Right. You could have the best, you know, geo algorithm, you know, playbook in all of the tactics are implemented. It would literally be like doing an all out campaign for snowblowers in Florida. Right. It's not going to land, it's not going to be trusted because people aren't resonating with it. It's not a product that aligns with their needs and their problems. So I think one of the biggest things that we need to do is, you know, ensure product market fit, develop the messaging, develop the positioning and then through the content, through the influencers, through the various channels, amplify those things. A huge part of me also believes that, you know, it's not just about what we say, but it's about what other people say. It's living our brand and that's really what trust is all about. Right. We can't be saying one thing and everybody else is saying another because ultimately what AI does, as I mentioned previously, it looks for patterns. If we're saying we're the best in the world in customer service and everybody else is saying, saying that it's crap, well then we're an outlier, we're noise. Everybody else becomes signal. And you know, that it doesn't align with what we want to be. So, you know, a big part of what I'm thinking here is it's less about the algorithm, it's actually living your brand, being authentically human, being authentically helpful. And when we do that, let the cards pop, fall as, as they may. Right? Because AI will amplify what's there.
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B
Exactly. And, and, but here, here's one of the interesting components because most of the naysayers who, who, who talk about AI, they, they talk about where it's getting it wrong. Right. And, and like what you see often, and I'm sure, Lisa, you've experienced this, right? Like every CEO is like finding examples in ChatGPT of where something is wrong. Right. And, and part of this is perception, part of this is lack of consumer education, part of this is maybe sometimes lack of the right marketing investments. Your whole point on pr, I think is a great one. Right? Where, where if a business thinks about PR purely as a cost center, you're not seeing the full picture of how the message can be conveyed in the market.
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C
Yeah.
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B
So tell us about what happens when these moments are wrong and when AI gets it wrong and how do we communicate to the leaders about this?
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C
So very interesting. Because AI is not infallible. Right. You know, as we Know, it does hallucinate and when it can't find a pattern, can't find a signal and it, it has gaps that it will make it up. Right. But here's the challenge for us way and it's much, much bigger than that. When, when, when somebody does an AI search, right. And AI makes a recommendation, it talks about the positioning of a company where it's ideal and where it's not ideal for that. It sources like 39 different channels or 39 different sources, right. There's this concept of perception as reality in marketing. I believe that moving forward that the AI response will be reality. Here's the reason why, regardless of what it says, let's say it gave you a good response and the user doesn't know whether it's right or wrong. And responsible AI use basically says you need to check its work. How many times have we ever gone to the second page of Google search results?
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B
Never. Yeah, yeah, exactly. Never, never.
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C
Now the question is, how many times do you think the user is going to go to those 39 different sources and check AI's work? Never.
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B
Never.
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C
Even worse.
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B
Exactly, exactly.
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C
So the AI response becomes the reality. Now that's tough for brands to hear, right? Because that means we're going to have to look at all these responses because we can't just look at one response. We have to do this over and over again. Because even if I gave the same prompt to the exact same AI, I will not get the same response over and over again. Right? You need to do this. Lots of testing and lots of data to figure out where it's getting it right and where it's getting it wrong. What I truly believe needs to happen is we again back to deeply understanding that customer. There will be some lag until we fix what's broken. If we're being positioned for the wrong things, maybe it's because we didn't say on our website in which situations we're good for and which situations we're not. Perhaps in our websites we're, we're over indexing on features. When the customer's prompt is around their problems, they're not asking for features, they're asking for problems. Right. So again, understanding that customer language, perhaps it also is maybe a lot of our content is behind a gate or a paywall. Well, guess what? If you get awesome content behind a gate or a paywall, AI is not going to see that. So even if you're positioning correctly and you've got awesome things behind that paywall, somebody else who's giving data and Information for free might dominate the citation as a result. So there's lots of these different things that, you know, AI pushes us to be more authentically human, authentically helpful, rather than using some of the tactics that we've leaned on in the past, like paywalls and all sorts of things, right. To get leads. So not to say that we should never hate an asset anymore.
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B
Sure, yeah, yeah, yeah, exactly. And I want to dive into this further because, you know, Liz, a lot of your experience, you've been on like, you know, big tech, software side of the company, software side of the industry. And you know, in many of these organizations, one of the main levers for growth is to create a, you know, a moment in time, right. A webinar, a hosted event, a set of content that's going to help you do your job better. Maybe a, a checklist, a resource or whatever it might be. And, and I think this has historically been a phenomenal tactic to getting a user's set of information. Right. I want to get a user's email address, I want to get a user's phone number, zip code, company name, right. Like you're trying to attract that user in so that you can find the data point that unlocks them in your sales journey. Right. And to your point about gated content, these are all heavily gated experiences with the intention of getting some sort of data about the user in return. And with AI now, it just seems like so much of that can be bypassed. It seems like I don't need to go and do that checklist because guess what? AI will create the checklist for me. I don't need to join your webinar because guess what, I can ask AI those questions and it's going to give me a very good answer, right? So I don't really need to participate in this gated asset in order for me to get the knowledge and information I have. What do marketers do? How do we change our tactics and behavior in a world where that gated content isn't the secret sauce to accessing a future customer?
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A
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C
Yeah, let me address the gated content first. Then I'm going to elevate it just a little bit. So I'm still pro gated content in situations where you're truly personalizing and adding value to a specific customer. Right. So let's just say it's IBM, it's going to have very specific data just for IBM. Sure. Gated. You don't want everybody and their dog to be in there, right? So there's still a place for gated content. You know, analyst reports like Gartner, Forrester reports, those are all behind the gate. And guess what? Customers are going, hey, rate this based on their coverage in the analyst reports, including their placement of the Gartner Magic Quadrant. Unless the brand actually talks about it, the AI can't get to it because it's behind a paywall. Right. So in terms of what people need to do, I think we go back to what's working from a human perspective. So events and communities are top of the list, right? In communities. So many conversations are happening in there. I'm in five CMO communities. Guess what? If somebody says, I'm looking at these three conversational AI platforms or AI SDR platforms, here are the pros and cons. People listen, right? Like that automatically becomes a short list. Or somebody might recommend a product that they've never heard of and then now everybody in that community is aware and there's 7,800 CMOs and some marketing in there. So I think the participation in these very human events like communities is going to rise. Right. The other one is events. So whether it's an online event or an in person event, even more so in a, an in person event, those conversations are also highly valued because it's humans, right? Like we're getting tired of the constant AI, AI. But when we can actually hear from human beings and their experiences, those rise. Now people are asking, what about from a digital perspective? So this is where I go back to. The tactic now is to give this notion of one of my good friends, Andy Crestedina, who's just a brilliant, brilliant digital and content marketer. He basically said that we are now in an era of it's a race to generosity of who can be the most generous and when we are generous with our thinking, with our thought leadership, with our time, actually helping customers through the buyer's journey, they'll remember us even if we are not the right solution for our, for them today. But we help them through that journey. People remember. Yeah, I'm going to give myself as an example. I don't do any outbound. Right. But I do a lot of thought leadership. I share very openly. And one of my mentors said, Liza, if you chase butterflies, they will fly away. But if you build your garden to something as beautiful as you can and you share it with others, you will attract the right butterflies. Now, I don't attract every single butterfly, but I attract those that believe in the same things that I do. Same values, right? So same thing with brands. If we could actually be authentically helpful and people can see that you're helping them and you're not just selling to them, they're going to come naturally to us. We're going to build trust. Back to the trust component of this and it's going to be, you know what, my sales cycles are very short. Your sales cycles are going to be very short because they came to you rather than you chasing them.
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B
Correct. I mean, I love this because I actually do think that this is the transformation of how great marketing is going to succeed in an AI world. And it really foundationally starts with human connection. So you brought up events, you brought up slack communities, you brought up about giving and doing, you know, services that, that normally would be maybe paid for but you're doing because you feel like you can build a connection and a bond. How do these things then become a reality in the current marketing ecosystem? How does this often word of mouth, human connection strategy become something that we think of as a marketing function? And how do we sell those kinds of ideas to our leadership teams and our partner teams?
- [28:29]
C
It's very hard and here's the reason why I believe it's very hard. While it's human, it's Also change, right? And change requires time. Building relationships require time. You know, any kind of relationship requires time. Right. But we are encumbered by quarterly earnings. You're a public company. There's not a lot of patience for building a relationship or engaging in a community. We are also encumbered by PE and VCs that want return on their dollars very quickly. So I'm very fearful and I worry that we're not going to be able to actually build the kind of relationship that we need to do with customers to ultimately build the trust and build a brand as a result of being in a pressure cooker. When we're in a pressure cooker, we can't be our best selves, we can't make the best decisions for the company and we ultimately go straight to what decisions will get us some results immediately. Right? But the challenge is we may get some immediate results, but they might be short term and it could actually be backfiring on us because like I said previously, we could get some customers. They may not be the ideal customers ultimately they churn, they attrit and then something bad happens down the road. So it could be a short term game, very long term pain for the business. So that is just some of the things that I think about and I think ultimately what AI is going to push us to do. Jordan, you know, there's this Harvard study that says it was a study with 776 P&G professionals and basically they gave AI to cross functional teams. And when these cross functional teams used AI, they began to care less about the boundaries of their job. Which is awesome, right? Because AI doesn't care about our departments and our silos. The good news about that, our customers don't care either. Right? And I'm going to connect this for you. Just hold on one second. Customers don't care because they want to experience a single company. They don't want to experience what feels like three companies because marketing says something different than sales and says something different than cs. Right? And what I believe will will push, push us to, to connect these things is AI because it doesn't care. And in the AI world because it only cares about outcomes. I believe at some point these silos will, will come down the they will converge like marketing, sales and ces. And we will no longer have ideally a set of KPIs for marketing like MQL's, a set of KPIs for sales like closed deals, or a set of KPIs for CS like renewals. Right? It will now converge to One that's outcomes based and customer centric like time to value or customer satisfaction or net retention rate. And everybody lines up to that, that right when it's, if, when it's at that level then we can have a conversation with the leadership team, the CEOs, the CFOs, those are the kinds of things that they care about anyway, you know, csat time to value and net retention rate. So lean into that rather than the, you know, the MQLs, closed deals and, and, and, and renewals because we know we can achieve all those and the company is still would not be doing well. But lean into those customer centric metrics and show how we can get to that using some of the techniques we talked about.
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B
So you know, you brought up something that I think is critical to this human connection to helping companies grow and scale today. And one of the big frictions that I see in the market as we talk to these executives about the right KPIs is this, I think ungrounded appetite to reduce your workforce. That less people can do more because of this AI. That my cross functional departments don't need more headcount because AI helps them move and operate faster. That my systems are now more efficient because I have AI at the center of it. And so I don't need an operator that's over overriding or doing an overview of these systems. And all these teams are getting smaller, all these companies are getting smaller and there's less people to connect with prospects and customers. What's your point of view on how AI is enabling teams versus dismantling teams? And is that point of view in the market one that's grounded in the future of how we're going to do marketing?
- [33:47]
C
Yeah, I have a fairly strong point of view on this one and people can certainly agree or disagree with me. We've heard so many say, especially CEOs. Right?
- [33:59]
B
Yep.
- [34:00]
C
We're implementing, we're adopting AI to improve productivity. It's about efficiency, do more with less. And sometimes, you know, we don't have the patience to upskill and reskill and do change management. We just lay off the people. Right. But while I believe there's a lot of benefit in using AI to make things go faster, so make existing work go faster, I believe that that should be only the floor of what we make possible with AI, not the ceiling. And what I mean by that is if you take a look at automation, we make existing work faster. We train AI to do our work. You can almost see how it can automate the human out but if we actually think about AI way beyond that, we're using AI to improve the quality of the work and then ultimately using AI to reimagine the work, meaning that we are now doing things that wasn't possible before and it grows the business. That is ultimately what we need to do. Not just make old work go faster, but actually create new work that wasn't possible before and grow the business. Right. When we simply train AI to do our existing work, we automate the human out. If we reimagine what's possible, we innovate, and then we ultimately grow the business. And that's what I believe, you know, people need when we grow the business, that humans are essential. Right, Right. So it's this reimagining. It's kind of like, you know, a Henry. We're in the Henry Ford moment. Jordan. I can't reimagine the future by simply automating the past. Right. Just like, you know, in the early days of Uber and Lyft, if they did not reimagine, they would have just put more taxis on the road.
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B
Yeah.
- [35:59]
C
But instead they reimagined it and said, you know what, this is going to be around building trust. We'll be allowing people to use their own vehicles and we're going to use an app. So, like, it's a very different way. Same thing. In the world of AI, what does AI do that's really hard for human beings to do, but now it's possible with AI, we could do this very differently. So, for example, one of the good examples that I have is it's really hard for human beings to take data and information from various sources, market signals from various sources, GONG transcripts, analyst reports, social information, publications, community entries, take all that signal and then figure out what the pattern is, what this, what the anomalies might be and what's common. And then based on all that, help us figure out a good campaign that caters to each of the Personas in the buying committee.
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B
Right.
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C
Well, goodness, like, we would go nuts as human beings. We would have had to take all of that. Right. You know what's happening today. PR&AR looks at the analyst reports, product marketing looks at the gong, call calls, CI or customer intelligence looks at competitive information. Each team is actually doing their own thing just to address the signal that they're paying attention to. But rarely does any one group or person look at all those signals. You know, synthesizes them, gets them insights, and then figures out an integrated campaign that's not possible with the existing Environment it. Right. But with AI that is now possible. So now we can achieve better outcomes as a result.
- [37:48]
B
Yeah, I, I, I love this. And, and, and I fundamentally believe that, that AI is one of the biggest enablers that we have now, not just in marketing organizations, but, but in all organizations and ways of working. One of the, one of the things that, that really stood out to me in terms of how you're, you're is really reimagining how we do work. And that means that you have to have some level of creativity and innovation. My last question for you is like, how important is creativity and innovation at the center of the use of AI in today's marketing landscape?
- [38:27]
C
I think it's important. But here's what I've learned in, in many transformation journeys and Jordan, I don't have best practices. What I have is pattern recognition. Right. Because best practices are coming to be, it's moving really fast and I don't believe that there are any best practices yet. But my pattern recognition says that AI today rewards people who are intensely curious and happen to be process and systems thinkers and who are, or, and have a growth mindset. Right. They, they love to think differently. They love to reimagine. Now not everybody is like that and we need to be cognizant of that. Right. Like our brains are not all wired the same. Not everybody is a system thinker. Right. So we have to have a lot of empathy and a lot of, give people a lot of grace depending on the differences. And what's, what's interesting is if the, if the difference is physical, then we kind of understand like I'm 410, right. Like no one would ever ask me to put their bag on an overhead bin because they know I can't. Right. But if the difference is cognitive, like cognitive differences, like, you know, I'm a process thinker, he's not or she's not. Right. That people are so quick to judge. And I think nowadays instead of just saying, hey, you're not doing this so well, you're really a process thinker. You stay, you go. I think we need to give people the grace and the opportunity to be upskilled and reskilled and it's one of these where we hired these people to serve a market, but now the market has shifted. I think it's our responsibility as, as leaders to upskill and reskill people. Right. And it doesn't mean that we don't eventually, you know, shrink the organization. You never know what's going to happen. But right. And people first AI forward, Jordan. And what that means is that we always apply a people lens in every AI decision that we make as we use AI to reimagine what's possible, reimagine our work. And when we are people first AI forward, we're committed to upskilling and reskilling people so that people actually have a decent chance to compete, wherever that might be, whether it's for a new role in a different team or in a different company.
- [41:06]
B
Absolutely. I love this and it's a, it's great advice and it's super on point with, with a lot of the, the, the, the friction that's in the market today and how marketers should be reinventing their, their skill sets. But I want to transition to my favorite part of the podcast, which is what we call our lightning round. I'm going to ask five questions from our conversation today and you're just going to give me a quick 30 minute answer on each of these 30 seconds.
- [41:33]
C
No pressure.
- [41:33]
B
30, 30 second. 30 minute. 30 second answer, answer. 30 minute. We'll be here all day. Sorry. But 30, 30 second answer on each of these. But. And I think it'll be a ton of fun because you've given us so much great insight. So are you ready?
- [41:49]
C
Yeah.
- [41:50]
B
All right, Lisa. Okay.
- [41:52]
C
I feel like I need a button.
- [41:54]
B
I know, right? We gotta, we gotta, we gotta add that to the podcast. Okay. What's the most important human connection we can make with customers and prospects?
- [42:07]
C
Trust.
- [42:09]
B
Tell me more. Why trust? What is. What's at the center of that?
- [42:13]
C
Well, you know, I. 30 seconds. I have this framework that says it's a two by two product market. Fit on the x axis, trust on the Y axis. You want to be at the top right hand corner where you have good product market fit because you're addressing their problems and you're highly relevant, but they also need to trust you. Right. Elsewhere on that chart, you've got a problem. Either you need to find a market that fits your product or a product to fit the market, or you have to build trust. Right. So the combination of those two things is really important. But you asked me about the human elements. I'm going to pick on trust.
- [42:48]
B
Love it. One thing marketers still misunderstand about AI.
- [42:55]
C
Yes. Misunderstand that the hardest part of AI transformation is humans, not AI, that this is human change management. More than anything, AI is actually the easiest part. You can't just give people tools and a couple of workshops and expect transformation. This requires giving people the space to learn, a safe space to learn. Not just highlight successes, but also highlight the failures. Because even with failures, we learned get them to build and share and then ultimately help them with a governance process where people are getting enabled as we move forward.
- [43:41]
B
Love it. What important leadership skill should we master in AI marketing?
- [43:52]
C
Yeah, so won't be one, but there's two. I think it's being graceful and compassionate about meeting people where they are and taking them along on this journey. And then the second thing is being able to align across functions. So those are the biggest things for me.
- [44:15]
B
Absolutely. One, pattern recognition that we should use to redesign our workflows in AI.
- [44:26]
C
Yes. To begin to redesign workflows, we need to think about capabilities of AI. That's very difficult for human beings to do. The reason I say that is, as I mentioned before, we're like the avengers. Humans and AIs have complementary superpowers and we overcome each other's weaknesses. There are things that are really hard for us to do, but it's easy for AI. So for example, really hard for people to distill information, lots of information from various sources, as I mentioned previously. So look at our work. If that's one of the key roadblocks of why we didn't do certain things because it was hard for us, maybe now AI can do it. Right. The other thing that AI is really good in doing is constant pulsing of the market or whatever it is that we're trying to get information on, like whether it's scheduled or real time. And then the other thing is consistent context, regardless of how many documents or how many pieces of data we've got, it's got consistency in applying certain standards across all those. And then last but not least is memory. We have super bad memory. AI has a lot better memory than we do. So, you know, with all these things, if we can find our limitations, see if we can get AI to use it to do it. And then on the other hand, AI has limitations. So for example, it doesn't have a moral compass. Right. It doesn't know our context. We still need to check its work. But when we combine those two, we can have complementary superpowers and overcome each each other's weaknesses to achieve better outcomes.
- [46:14]
B
Okay, last question. If you could give enterprise leaders one piece of advice for the next 12 months, what would it be?
- [46:24]
C
Give your teams the gift of upskilling and reskilling. Because regardless of what happens, you know, I rarely remember the campaigns or the product launches that I did in my career, but I always remember where the people are today that I was able to help. And I think upskilling and reskilling isn't just something that we do for our companies. It is something that we do for our teams and for the individual, allowing them to thrive and better compete in the era of AI.
- [46:59]
B
Okay, and that wraps up this episode of the Voices of Search podcast. A huge thank you to Lisa Adams, AI Advisor, and go to Market Strategist at Growth Path Partners for joining us. If you'd like to contact Lisa, you can find a link to her LinkedIn profile in our show notes or on the voicesofsearch.com or you can visit her company website, growthpath.net if you haven't subscribed yet and want a daily stream of SEO and content marketing knowledge in your podcast feed, hit the subscribe button in your podcast app or on YouTube and we'll be back in your feed every week. Okay, that's all for today, but until next time, remember, the answers are always in the data.