AI Insights: Uncovering Customer Value

Happy 2026. Hey, how's this for a new Year's resolution? How about you Master AI marketing? The AI Business Society gives you live training with experts who are getting real results. No hype, no fluff, just proven workflows that work. And you've got access to an incredible library of training from many of the incredible guests that you've heard on this show. So secure your AI transformation by visiting socialmediaexaminer.com AI.

Welcome to the AI Explored podcast, helping you put AI to work. And now, here's your host, Michael Stelzner.

Hello, hello, hello. Thank you so much for joining me for the AI Explored podcast brought to you by Social Media Examiner. I'm your host, Michael Stelzner, and this is the podcast for marketers, creators and business owners who want to know how to use AI. Today, I'm going to be joined by Lisa Adams, and we're going to explore utilizing AI to determine your business's value based on a lot of public data that's out there and also looking at the defensibility of your business in. If you are wondering whether or not you are in a really great position with your business from a competitive fit and also from a customer perspective, I think you're gonna find today's interview extremely fascinating. Also, if you're new to this show, be sure to follow us on whatever app you're listening to so you don't miss any of our future content. Let's transition over to this week's interview with Lisa Adams.

Helping you simplify your AI journey. Here is this week's expert gu.

Today, I'm very excited to be joined by Liza Adams. If you don't know who Lisa is, she is an AI strategist and founder of Growth Path Partners, a consultancy that helps B2B marketers accelerate AI adoption. She also helps businesses with applied AI workshops and fractional CMO work. Liza, welcome to the show. How you doing today?

I'm doing great, Michael. So excited to be here. Thank you for having me.

Oh, it's awesome to have you. And today, Lisa and I are going to explore how to use AI to develop a rock solid marketing strategy utilizing in a really cool framework that she's developed. But before we go there, I want to hear your story. How in the world did you get into AI? Start wherever you want to start.

Oh, my gosh. Wow. So I've been doing AI, Michael, for about 10 years.

Wow, you're an early adopter then. That's cool.

But it's not gen AI. I know that in today's environment. When people say AI, it's synonymous with gen AI. So my work started in predictive analytics and machine learning when it wasn't so much in our face. Right. It was embedded in the things that we build, that we create. And then obviously more recently, over the last couple of years, generative AI and why I leaned in on Generative AI has an interesting backstory. You know, I'm based in Boulder, Colorado, been here for about 20 years, but half of my career was spent in Silicon Valley. So I, I was married to an airplane. I did the commute out on Mondays, back on Thursdays.

Wow.

Worked for some very large Silicon Valley companies. You know, Brocade, now part of Broadcom, Pure Storage, Juniper Networks, now part of hp, and then also worked in Seattle area for Smartsheet. And love the work. And, you know, I have less guilt as a mother because my husband, my better half, is a published author and he happens to do his work from home. So my last corporate role was with a company here in Colorado, ironically, right after Covid, when we didn't have to be meeting in person anymore and it was with a CRM, ERP and SAS company in the beverage alcohol supply chain. And honestly, Michael, I thought that it was going to be my last one. Love the business and really thought that, you know, five more years and I'd be done right. But it wasn't meant to be. We were acquired and I had a successful exit, but it was a little too soon for me. It was like a year and a half into my tenure, so I was a little bit heartbroken. And I said, well, you know what I'm thinking about? Maybe I should think about serving on boards because I am passionate about having more marketers and women and women of color on boards. But when I did my research, I found out that There are only 41 marketers and Fortune 1000 boards and, and less than 3% of board members, regardless of size of the company, have marketing experience. So I was really even more brokenhearted as a result of that. So I dug so deeply into why that is, and there are many reasons why marketers are not on boards, but one of the biggest reasons is that we are deemed as tacticians rather than strategists.

Ah, okay.

So people see the work that we do with ads, with social media, websites, events, campaigns, emails, but the work that we do in go to market strategy and ensuring product market fit in, figuring out segmentation, targeting and positioning and deeply understanding markets and creating categories and creating category leadership, those are relatively invisible to.

Many people at the High level of business, obviously.

Right. At the highest level of business. Right. But all of that work is so important for us to be able to do really creative and really effective campaigns in market. So I had taken it on almost as a personal mission with people who believe in the same things that I do to elevate the strategic value of marketing. And it happened. My exit from my last company happened to coincide with the launch of ChatGPT in November 2022.

What miraculous timing. That is so cool.

And I looked into this and I almost automatically saw what other people didn't initially saw and what it was capable of. Like people were using it to create blogs or summarize long reports or helping them with email. When I saw it for much more than that, you know, I saw it for thought leadership, using it as a thought partner, using it for analytics and research to inform, you know, new insights and decision making, using it for automation, personalization, really strategic content creation, those types of things. And I thought to myself, this is the gift. This is the gift that we've been waiting for for marketers to flip the thinking, right, to actually infuse our work with AI to become more strategic. Because before, companies didn't have the tolerance nor the patience for us to do deep market inspection and research and surveys and strategy. But now all that is compressed as a result of AI having all this ability to do that in a very timely manner and be able to look at a lot of data and get some really unique insights. So I'm like, this is it. We're going to flip the script and allow ourselves to really have a seat at the table. Because now there's patience. We don't need all the patients. We can do this fairly quickly and we can have really informed, data driven decisions in marketing.

I love it. So somewhere along the way, in this discovery that you made probably very quickly in the months after ChatGPT was rolled out in late 2022, you decided to do what? Start your own business. Right. So kind of tell us what you're doing for businesses now.

Yeah. So it was almost just luck. Luck and passion, you know, the combination of those things. I am not an AI expert. I tell people I'm not that, but I have a passion for elevating the strategic value of marketing. I have a passion for diversity and inclusion, especially when we think about AI. If AI is supposed to benefit all of humanity, we need to have diverse opinions and diverse perspectives at the table. Then the last thing that I'm passionate about is using business as a force for good. These Three things. If you put them all together and then you infuse it with AI, AI just happens to elevate them, right? So that's one of the key reasons why I dug into it so deeply. So what I did was, you know, I said, well, do I have it in me to go back to be a CMO again? But I was like, I think I'm going to try to find companies, I'm going to be a fractional CMO and I'm going to try to find companies that believe in need, the strategic work of marketing, a CEO and a board that really believes in that. You know, if a company, you know, let's just say just want some lead generation, but they don't have good product market fit, I'm not the right person for that. Right? But if a company is, is so focused on ensuring that they meet the needs of the market and it is so defensible, once we nail that down, we demand gen like no other, that I'm a good fit for that kind of a company. So I found those companies and very lucky to have found them. And then I started sharing in communities and slack communities, on social media, on LinkedIn, on podcasts, just like this one. Some of these key use cases that many marketers weren't using AI for, for strategic use cases to align people, figuring out what market segments to go after, creating defensible positioning, doing competitive analysis, all these things, and as a result, almost unintentionally built the brand and now starting to help people, inspiring them with what's possible with AI beyond creating blogs.

I love it. And I know that the listeners and watchers of this are going to eat this like candy because there are so many marketers out there that are dabbling with, frankly, a flashing cursor on the screen and they don't even know really what it's capable of. So what do you want to say to marketers right now, now that are not using AI for strategy? Kind of. What are they missing out on? What's the upside if they pay attention to what we're going to talk about today?

Well, and before we even get to the upside, I just want to say that we have to be graceful and respectful of where everybody is in their AI journey because I happen to be passionate about something and I happen to do it for a living. So I live and breathe AI almost every day. Right. But not everybody has the same passion, not everybody has the same time, not everybody has the same access to AI. So I think we need to give ourselves a lot of Grace in this AI journey and my guidance to people is just give yourself the time, give yourself just a little bit of understanding of what it is. Because I do believe that AI literacy and AI understanding is so important. Because at the very, very least, when we understand AI, we can make better decisions for ourselves, for our families, for our careers, our business and society, rather than being influenced by others who may or may not hold the same values that we do. So I want to first just ground it in that love that I don't want to judge anyone for their use or non use of AI or wherever they are in this AI journey. Right. Because we all have different things happening in our lives to marketers to the extent that we can lean in. I actually tell people that AI is forcing us to be more strategic and more authentically human. And on the strategy front, we'll talk about that in a little bit because I do feel that. Let me give you an example. If you don't have good product market fit and we infuse AI in our campaigns, in all of our tactics, right. One of the key examples that I give is it's like doing an all out campaign for snowblowers in Florida.

Right. Or selling ice to Eskimos.

Right? Ice to Eskimos, you know, umbrellas to people in the Sahara, whatever you want to call it, Right?

Right.

Because they don't have a need. You've got a product that doesn't meet a need, you know, and now you infuse it with a high. So you do so much personalization, so many emails, so much content creation. Well, it's just a faster path to failure, right?

Okay.

Absent this really good product market fit. So AI will force us to solve for these more strategic problems. Otherwise, like I said, it's a waste of money, waste of resources. The other aspect of AI is I believe that it will force us to be more authentically human as marketers more than ever. If we think about it, people's radars are up. They're like, oh, that's a bot, that's a deep fake. Oh, that was created by AI. I don't trust that company. Trust levels are going to be one of the most important things that we need to earn. In the era of AI, people are meant to connect. During COVID we figured out how to have birthday parties by having car parades. Right. We like having human beings. So events will rise, authentic human connections will rise. Even though you and I are having this conversation digitally, we know that it's a human talking to a human. Our listeners are human. That will rise. But in the era of AI as marketers, the challenge for us is how do we get the full potential out of the technology, out of the innovation, but at the same time maintain authentic human values that are important to people. So it will force us to be authentically human. Because now our jobs just got harder. We have to balance innovation with ethics. We have to balance convenience with privacy, balance personalization with transparency, balance automation with the human touch. Like NotebookLM is a, an application where you could input, you know, a PDF or a newsletter and it outputs an AI podcast with two AI hosts.

Well, and by the way, listeners of this podcast heard me actually release a special episode of this podcast within the last few weeks specifically utilizing this. And it's mind blowing. And it sounds human.

It sounds human, right? And it's awesome for auditory learners like me. Right. I like to listen to things. I, I tend to multitask. Right. But if we use it for commercial purposes, I'm no lawyer, but let's be so transparent about, hey, this podcast is not a human podcast. These are two AI hosts. It is based on written content that I've created and I provided human oversight and reviewed the content of this podcast. I'm delivering you a podcast in this manner to ensure more efficient delivery of information and so that people with different learning styles can take advantage of it. So there we used AI, but we were so transparent about our use of it. So I think this whole thing around the balance of technology and human centered ethical use of AI is going to be one of the things that is going to be critical in the marketers remit moving forward.

I love it and I agree completely with everything you're talking about and we could definitely go down that rabbit hole, but we're not going to. I want you to kind of do address though. Hey, here's why you should use AI for strategy. Just talk about that for a minute.

Yeah, so I dabbled into it a little bit when I talked about the product market fit and the snowblowers in Florida. I love that analogy. And I also tell people, you know, just like you can't out exercise a bad diet, you can't out campaign a bad product market fit. Right? Like it just doesn't work.

But assuming you have that, this could help, right?

This could help. And AI can help you figure out if you have a good product market fit. AI could help you figure out if you have a defensible moat. Right. Let's say you've got good product market fit, but it's not defensible. Six months from now, somebody else can replace you. So when I think about how AI can help us from that perspective, there's this framework that I've used for several decades. I won't say how many.

No one will judge you. Trust me, don't worry about it.

And what I about this framework is that it has stood the test of time, right? It has stood the test of multiple inflection points in the market, from Internet, cloud, mobile, social, and then now AI. And the framework basically has two dimensions to it. One dimension is around value we provide our customers. And that dimension could go from one end of the scale where we are providing the same value as our competitors. The middle part of that scale is we provide incremental value over our competitors. And then the top of the scale is that we provide order of magnitude of improvement of value compared to our competitors. So ideally we want to be at the top of that, right? Or at least at the middle. We don't want to be at the bottom, right. The other dimension, and then we could dive into each dimension in detail. The other dimension is around defensibility. Defensibility basically just says, how easy or how hard will it be for your competitors to replace you or to overcome your competitive advantages? Is it easy to copy, meaning their next release of the product you're now at par or irrelevant? Is it moderate to copy or is it super hard to copy? Super hard to copy meaning they would have to hire your top engineers, your top talent, or they may even need to buy your company because it's so hard to copy what you're doing. And ideally you would want to be at the top on each one of those two dimensions.

I love it. So basically what I hear you say is on one dimension, one axis, we have the value that you provide to consumers, customers, and the other one is this defensible moat. How unique is whatever you offer and how hard is it for someone to replicate it? So let's talk about this value to customers and let's dig in on this a little bit and just go for it. I know you've got a lot to say there.

Yeah. On value to customers, this one, I like to break down big problems into bite sized chunks because otherwise it becomes more of an emotional gut feeling about really big things. Right? Oh, I think we provide a lot of value because XYZ and somebody might have very different opinions on that. And the way to do this is to define what we mean by value. So value might be, is it price, is it meeting a need that is unmet today is it allowing them to scale? Is it allowing them to transform their business? It could be a number of things and it varies by company.

You want to give an example like ChatGPT would probably be a great example, right. Of something that's way high at the value side of the things, right?

That's right. And it doesn't have to be like ChatGPT, way higher the value scale because it is across many industries, it has many use cases. You can actually have a lot of value in very specific use cases in very narrow markets. Right. It doesn't have to be like the end all be all for it to be highly valuable. You just need to think about your space. And the key here is figuring out what those three to five areas of value are and then having data that can support it and where we find data to support that. I love using customer reviews or customer conversations with sales. And we have GONG transcripts, customer reviews from G2 or Capterra or Gartner Peer insights because you get real insight into what those customers are saying. And those customers reviews could be like Google reviews or anything like that on the consumer side, Right. Once we have that data, then we can then have AI analyze it and AI can actually say, all right, on a scale of 1 to 10, it could build heat maps for us. Buy Persona by buyer. Based on these customer reviews, here's some insights that AI is going to be able to gather for us and illuminate for us.

Let's talk about filling the gap between AI potential and AI results. I'm sure you've tried ChatGPT. Are you seeing real ROI? Most marketers are barely scratching the surface of what's possible with AI. And it's because they're missing the training and the frameworks that will allow them to be very successful in their careers and in their future. AI Business World allows you to get that training. When you attend, you get two full days and 20 expert practitioners, many of the people that you've heard on this very show, that will teach you exactly what you need to know to build the workflows and to succeed as an AI enhanced marketer. It takes place April 29th and 30th in Anaheim, right alongside Social Media Marketing World. And here's the good news. You can save $300 when you register by January 16th. Head to AI BusinessWorld Live right now. This discount ends soon. Tell us how we might do this. So so far, just so we're clear, what I'm hearing you say is you need to identify like three or four areas that you believe are of great value to your customers, then you need to go out and you need to gather as much information as possible. Could be Google reviews, it could be Amazon reviews, it could be customer interview, whatever you've got. Right. So let's say we've got that and now we're sitting in front of Claude or Chat GPT, trying to figure out what to do with it. Give some guidance and advice on what we would do with something like that.

Yeah, you would prompt at something like this. Right. And it could be a qualitative response or a quantitative response from the AI. You might say something like in the area of customer service, look at these reviews and identify the customers that have made comments around customer service.

Ah, because that's one of the things you think is valuable.

What are the dimensions? Right.

Okay.

And you would say based on their comments, make some assumptions or infer on a scale of 1 to 5 where most customers are. And you would say 5, they're extremely happy. 1. The sentiment is they're highly dissatisfied.

Got it. So we're doing a sentiment analysis on the comments around a category. Like customer service. Right?

Like customer service. Right. Maybe we get a five there, who knows? Right. You know, maybe the next one is price, you know, maybe we get a three there, so on and so forth. So you could now almost see an evaluation of value along multiple dimensions based on what customers are saying. And then we get a really nice chart. Right. But that's just customer reviews. We might have partner insights, we might have customer conversations with sales. Lots of data that we can now take to an executive team and be honest with ourselves. Okay, based on this data, based on these insights, where would you put us on that scale of we are at par with our competitors, we are providing incremental improvement or an order of magnitude improvement compared to our competitors. And the way we do that, we have a benchmark for us. Heck, benchmark it for our competitors too, because those reviews for our competitors are out there.

Ah, I love this.

Do it the same way for them. So we get insights from our customers, we'll get insights from what others think about our competitors. Then we can then determine where we are on that scale based on that data.

I love this because this is like a relative scale based on, for example, let's say you have a competitor that you know is likely higher on the customer service frontier. Right. You could gather up that data, put your data in there and ask the AI to analyze kind of it's in its assessment, you know, where you fall on this relative scale. That's Right now, what goes through my mind, especially for businesses that maybe don't have a lot of access to data, how much data do we need for this to be effective? What's your thoughts on that?

Well, obviously, the more data, the better. Right, Right. For those who don't have the data, I think we need to go get it. And sometimes what that means is customer surveys.

There you go. Okay.

Interviews. I also mentioned those transcripts that we have between sales and customers. Transcripts between customer success and customers. Those are going to be critical. But what we need to keep in mind is privacy and protection of sensitive data. Right. We need to ensure that we redact all that information before feeding it into AI and otherwise we've got some issues on ethical use, if that makes sense.

Yeah, totally. So do you have an example of something you've done, even if it's anonymous, and how the AI helped? You could do this without AI, obviously. Right. So what's the big upside to utilizing AI? What can it see that you cannot see?

Well, you know, I always talk about the Justice League of Humans and AI. You know, humans, we cannot remember things. Right. I don't remember what I did yesterday. I can't process a lot of data, but AI can. Right. However, the flip is AI cannot adapt easily. It doesn't have an emotional response. Right. So together, we kind of basically overcome each other's weaknesses. The main thing for me is when we have a lot of data, there is no way. I don't care how good you are in Excel or how great you are as a data scientist, you. Those people are not exactly cheap. Right. Like, AI can really help us sift through a lot of data and uncover things that we would not have seen. Like cross tabs. Right. Like you could see the dimensions that we might think are not related, but ultimately they are. That allows us to really get some new insights that we would never have thought of. But the main thing for me is the use of AI is not even the hard part. The hardest part is the data. Getting the data, cleaning the data, putting it in the right structure. I did this for one of my clients, and it took us two to three weeks just to get the data, just to put it in a format so that we can have a conversation with AI, with ChatGPT teams, that conversation with teams, oh, I don't know, a couple hours. The data cleansing collection curation.

Give us a couple of tips on how to do that.

Oh, my gosh. The tips would vary depending on the company, but I have not seen a company with clean Data. We were looking at data from Slack, data from Excel, data from HubSpot, probably from emails too. Right, Emails. And literally putting that thing into a spreadsheet.

Wow. Okay.

Cleaning it up. Make sure that we don't have customer information. Oh, and by the way, we had to do a translation. Just pick a company.

Different language. Translation, Is that what you mean?

No, I'm talking about if we're redacting the information. Right? Yeah, yeah, yeah. Okay. Walmart is now Acme.

Right, I see. Oh, yeah. So you need to set up some sort of identifiers that are generic is what you're saying. Got it.

Generic, exactly. So this whole thing around genericizing, redacting, adding some noise so that AI doesn't really think that this is your customer base. Right. I keep telling people that AI probably thinks that I own a zoo because I always give it a context of this is a zoo. The data that I'm giving you is based on the most popular attractions in the zoo versus this is my market size. And these are the penetration rates by segment. So you kind of have to trick it that way.

Oh, I see. So what I'm hearing you say is that if you want to make sure that it doesn't leak into the large model, you kind of have to make a metaphor, if you will. Right. And that's really intriguing. Okay, so we've talked about the value side of things. We haven't talked about the defensibility side of things. So connect the dots for us on that.

Oh, I love the defensibility side. And the reason why I love it is I work in B2B tech and people are generally very enamored by technology. Like it's the best technology ever. And you know what's ironic? Especially in the era of AI, a lot of people are building on top of the existing large language models and frontier models. They're building on top of OpenAI, on top of Gemini or Meta. Metaslama. And you begin to question how defensible just having AI is. My belief is that it isn't. We need to have other things beyond the innovation, beyond the technology to defend ourselves. It could be in the strength of our partner ecosystem. It could be our deep insight into a vertical. It could be unique customer knowledge, it could be brand, it could be our distribution channel, something like that that AI or a large AI company won't be able to replicate very easily. Because if I think about, there are a lot of what they call AI wrappers, and these AI wrappers are essentially companies that have built products around the Gaps that current AI, large AI models can't do today. But this whole notion of, you know, this is the dumbest form of AI we'll see moving forward, what happens six months from now when we've got GPT5 or whatever. Right. And then we built something that's based on the gap. So I think one of the key things in this dimension is just being so honest with ourselves, look ourselves in the mirror as companies to really see what is defensible in the market. And this one is probably a little bit more, less data driven because you kind of have to like have a vision for what is defensible in the market. And that might vary by industry. Right. Like if you're a donut shop, are your ingredients defensible is so hard to find. Is it the recipe, is it how you create?

But your location could be defensible. Right.

Is it your location? Right. Like all those things I think is something that we need to think about. And the use of AI is probably less on the data aspect of this because it's, it's a vision. But when I now think about the value piece of this and the defensibility piece of this, you put those two responses into AI and see where you are on that map. A top right hand corner, you've got fully defensible, hard to replicate, and you're adding order of magnitude of improvement. I will map you and put you in that top right hand corner. I would suggest that you have the potential to be a category maker.

So how do we even know? I mean, because defensibility, to be honest with you, because you said yourself a lot of times the marketers are not near the top of the company. And sometimes businesses don't think about defensibility until they get much bigger. So how do we even know? Can AI help us figure out what our defensible unique thing is?

Yeah. So I've actually built this custom GPT, Michael.

Okay.

And this custom GPT basically asks you questions around the value dimension.

Okay.

And it asks you whether you're providing the same incremental or order of magnitude of improvement along number of value parameters. And then on the defensibility parameter, it basically says, what are your three defensible moats? Your top three. Right. And I do put on the GPT that technology might not be truly defensible. And I give them some examples of things that are probably more defensible in their areas. Right. So if it's a donut shop, it applies to any industry.

So the AI helps them identify potentially.

Yes, potentially. What Those are right. So the GPT suggests like things like ingredients and recipes and things like that. So I begin to like feed it with some ideas for other things beyond technology that will allow you to be defensible. So you pick your top three, and then I say, the GPD says, weigh these top three. Which of these three do you believe is the one that you have the strongest defensibility in? So you might say, all right, ingredients 50%, you know, recipe 40%, location 10.

I see. So it's a weighted average. Okay.

And then it does a calculation and then the combination of the value plus the defensibility, it maps you on a chart.

Is this GPT freely available?

Yes, it's on the GPT store.

So what's it called?

Strategic Defensibility Analyzer.

Okay. And just for those that don't understand what the GPT store is on ChatGPT with the, the paid account. I think it's only on the paid account, but you could correct me if I'm wrong.

That's right.

You can add these things called custom GPTs that are pre designed. And you said it's called Custom defensibility, what was it?

Yeah, it's Competitive Defensibility Analyzer.

Okay, cool. So it guides you because you've developed a line of questions behind the scenes to help guide anyone to determine their defensibility. Competitive Defensibility Analyzer. Love it. So let's talk about this just for a second. It sounds like what I'm hearing you say is that, hey, you can use AI to kind of query you to help you figure out what your defensibility is. And you've built the, the prompts behind the scenes to make that easy. How long of an exercise does this typically take? If you were to do this, like for example, with a client or if an AI was to do it with you. Is this something that takes a long time? I'm just curious what's involved here.

The research, the data cleansing is what takes the most amount of time. Right. Once you do that, using the GPT could be, you know, 30 minutes.

Got it.

But the key is whatever answer it spits out is just a place to start. Because what that now does is you have a framework by which you can take this to your leadership team, your executive team. You know, if you're a small business, maybe you and your partner, you now have a conversation, right? You now have a debate around what AI spit out, and you determine whether that makes sense to you. But now you have something data driven that gives you a lot more insight and I think from that discussion that I believe is the most value. It's not the answer that AI gave, it's the discussion with anyone else in the company that you need to align with. And based on that discussion, now you can have, you know, something that you can validate in market and then ultimately make a final decision. All right, we need to increase, you know, our defensibility. We need better ingredients or we're not meeting the needs of the market. Do we need to go after a different market, a different segment of the market? Do we need to improve the product for this particular segment that we're going after? I think it illuminates where the problem is. And then we need to figure out how we need to solve for that problem, if that makes sense.

It does. So on one side we have value, on the other side we have defensibility and we're a dot somewhere on this rectangular matrix kind of thing, for lack of better words. So an AI can assist us on determining relatively easily our defensibility by asking a few questions by going to your competitive defensibility analyzed custom GPT. The data side of it is a little more complicated, as we've talked about before. But if you have all that information and it plots you on a spot and ideally you want to be upper right. Right. You want to be like highly defensible and you want to be highly valued. I mean, that's the ideal scenario. Right? Because as you mentioned, if you're there, then you've got a great opportunity once you see where you are. How do you use this now? Strategically, to make decisions moving forward?

Yeah. Like I said, it will vary depending on the business and where they want to be. Right. Some people are okay being a me too, and that's their business. Not everybody can be a category maker. That's a hard place to be in as well. Right. Because when you're a category maker, you don't want to be in a category of one.

Right.

You got to attract other people to be. Want to be part of that category and things of that nature. Right. So people will have. Businesses will have different places where they want to be. And then that is more a decision of like the example I gave, hey, we've got this product, it doesn't quite fit the market. Do we go after a different market?

Okay.

And then now that's yet another use case for AI because I was working with a company that had that same problem and they're like, oh, here are eight potential market segments that we could go after for our product. Well, I'M like, okay, which one do we go after? Right? Because you can't go after 8. What are the two or three markets that we need to go after? Then? That's yet another use case because we have to now evaluate each one of those segments across a number of criteria. Is it market size, market growth, competitive intensity, reference, customers, strength of the ecosystem of partners, all sorts of things. Again, we can use AI, feed it with data, it can do some forced ranking for us, it can build a heat map for us, and then we can apply weights. It can have a final answer for us what the top two or three segments are that would be best for us based on the criteria that we gave it, if that makes sense.

Yeah. And where I think this is kind of exciting is you could tell the AI, hey, given this data, what opportunities do you see for us to potentially get from here to here? Right. And I would imagine it would come up with ideas and then you could discuss those with the AI and maybe go back with more of a plan to your executive team. Is that kind of what I'm hearing you say? Or at least to start the discussion?

It is, it is a starting point. Right. AI is awesome as a thought process partner. Right. Because you can ask IT questions. You could say, all right, I'm thinking about these three segments. Here's what my business is like, here's my positioning, and here's my areas of defensibility. Tell me the pros and cons of going after each one of these. Or you can say something like, use the Thorn Bud Rose framework. Rose Thorn Bud basically says, you know, here are the positives, here are the neutrals, and here are the negatives. Okay. One of these, right? And it will give you a starting point. And then you done need to do your research and kind of be introspective with the leadership team to see how that maps well or not well with your thinking. So I love how it gets us started with some hypotheses, but then human oversight all the time. Our own experience, our own data trumps whatever I might recommend.

I love this. This has been so fascinating and I really like the idea that we're utilizing AI to help us think strategically. Right. And it's not necessarily doing the thinking for us. Instead, it's doing a little bit of analysis for us, given the large sets of data, which is speeding our time. And it's also allowing us to, like you said, have a thought partner. Right. Like, I love using the voice mode on the chat GPT paid version when I've got really Sticky things that I'm processing. Right. Because I'm a verbal processor. And, and that's what I love is I got the transcript of what I said and what it said when it's all done. So I think what I'm really hearing you say is AI is kind of like a really fast employee, right. That can help you move things along relatively quickly. Where this would have taken months now, this can be done very fast. Is that right?

Yeah. And the analogy that I use, Michael, is imagine lifting something from the ground. That's really heavy, right? If you're lifting it from the ground up, that's painful, right? AI lifts it just a little bit above the ground, maybe 6 inches, 12 inches higher. It's a lot easier to get it up. That's how I think about it. I think about it as a tool to help us get started, helps us with data driven insights that we would normally have to use a lot of time and manpower to do. And then ultimately, once we apply human oversight, we now have a framework by which to align different people. And unlike the past, in the past where this could take an enormous amount of time and resources and we didn't have the appetite for that and we sometimes skip the steps as a result, now we don't have that excuse. It shouldn't take that much time to do things right. Get this thing right, then our campaigns will be so much better. Get this thing wrong. Faster path to failure.

Liza Adams, this has been a fascinating dialogue. If people want to connect with you, I'm guessing LinkedIn is your preferred platform. So how do they reach you there? And then if they want to connect with your business, where do you want to send them?

Yeah. So LinkedIn. Follow me. So, Liza Adams, it's L I Z A growthpath.net is my website, so you can reach me there as well.

Thank you so much for sharing your insights with us today.

All right, thank you so much, Michael. Happy to be here.

Hey, if you missed anything, we took all the notes for you over@social mediaexaminer.com a28. If you're new to the show, be sure to follow us on whatever app you're listening to. And if you've been a long time listener, can I ask you a favor? Would you give us a review on whatever platform you're listening on? And if you're willing, also let your friends know about this show. I'm Elsner on Facebook, I'm Telzner on LinkedIn, and I'm IKestelsner on X. And do check out our other shows, the Social Media Marketing Podcast and the Social Media Marketing Talk show. This brings us to the end of the AI Explored Podcast. I'm your host, Michael Stelzner. I'll be back with you next week. I hope you make the best out of your day and may AI help you to become more, more successful.

The AI Explored podcast is a production of Social Media Examiner.

AI Business World, early bird pricing ends on January the 16th. You can save $300 on your tickets. Register at AIbusinessworld live today.