Outthink Your Competition: AI in Marketing Strategy

Have you ever found yourself overwhelmed with data and wondered how you could turn it into meaningful insights to outsmart your competition? Well, today’s episode of ‘AI in Marketing: Unpacked’ is just for you. We’re diving deep into the revolutionary world of AI-enhanced strategic thinking.

Imagine having a thought partner that never tires, always has the latest insights, and helps you see gaps you never knew existed. This is what AI can bring to your marketing strategy, and here to guide us through this fascinating journey is Sunny Hunt.

Sunny is a seasoned marketing consultant who has helped B2B and B2C companies with strategic marketing solutions. Recently, she harnessed the power of AI to streamline data parsing and enhance strategic decision-making for the University of Arizona, saving 230 times the amount of time it would have taken manually.

In today’s episode, Sunny will share how she uses AI as both an eager intern to handle heavy-lifting tasks and as a thought partner to sharpen her strategic thinking. She’ll walk us through real-world applications and provide actionable insights on harnessing AI to elevate your marketing strategy. So, buckle up, you’re about to discover the future of strategic marketing!

AI in Marketing: Unpacked host Mike Allton asked Sunny Hunt about:

✨ AI-Driven Insights: AI can streamline and enhance strategic decision-making by handling data-heavy tasks and identifying gaps in thinking.

✨Efficiency Boost: Leveraging AI can save significant time and resources, allowing marketers to focus on creativity and strategy.

✨Future of Marketing: The role of AI in marketing is evolving rapidly, offering new opportunities for smarter, more effective campaigns.

Learn more about Sunny Hunt

Sunny Hunt is a Customer Growth & Retention architect. She’s best known for helping companies scale sustainably by reverse-engineering their most profitable customers and crafting go-to-market strategies to help them fill positioning and success gaps in the customer journey.

Over the past 20 years, she’s worked with a wide array of B2B and B2C companies, like DHL, DirecTV, and Blue Cross Blue Shield of Arizona, guiding and advising them on how to get the right message, in the right channel, at the right time, to the right customer.

Resources & Brands mentioned in this episode

Full Transcript

(lightly edited)

Outthink Your Competition_ AI in Marketing Strategy

[00:00:00] Sunny Hunt: Using generative AI tools to do things like creating strategies comes at a cost. And that cost is that your competition has the access to the exact same tools that you do. You really do need to lean on people who have the experience, who have been arms deep in the trenches, figuring stuff out the hard way and making those really terrible mistakes and really incorporating a lot of input, especially from your customers.

Because if you don’t know the desired outcomes of your customers, why they chose you in the first place, and what they value they get out of using your product or service, and how you’re making their lives better, you can’t grab that information and incorporate it into your strategy. Your strategy is going to be really hollow, and it’s more likely than not that you’re going to miss the mark and not be able to achieve the goals that you set out to achieve.

[00:00:51] Mike Allton: Welcome to AI in Marketing: Unpacked, where we simplify AI for impactful marketing. I’m your host, Mike Allton here to guide you through the world of artificial intelligence and its transformative impact on marketing strategies. Each episode will break down AI concepts into manageable insights and explore practical applications that can supercharge your marketing efforts.

Whether you’re an experienced marketer just starting to explore the potential of AI, this podcast will equip you with the knowledge and tools you need to succeed. So tune in and let’s unlock the power of AI together.

Greetings program. Welcome back to AI in Marketing: Unpacked where I selfishly use this time to pick the brains of experts, keeping up with and integrating or layering artificial intelligence into social media, content, advertising, search, and other areas, additional marketing. And you get to learn to subscribe to be shown how to prepare yourself and your brand for this AI revolution and come out ahead.

Now listen, you ever found yourself overwhelmed with data and wondered how you could turn it into meaningful insights to outsmart your competition? Well, today’s episode of AI in Marketing: Unpacked is for you. We’re diving deep in the revolutionary world of AI enhanced strategic thinking.

And imagine having a thought partner that never tires, always has the latest insights, never complains and helps you see gaps you never knew existed. This is what AI can bring to your marketing strategy. And here to guide us through this fascinating journey is Sunny Hunt. Sunny is a seasoned marketing consultant who’s helped B2B and B2C companies with strategic marketing solutions.

Recently, she harnessed the power of AI to streamline data parsing, enhance strategic decision making for the university of Arizona, saving 230 times the amount of time it would have taken. Manually in today’s episode, Sonny is going to share how she uses AI as both an eager intern to handle heavy lifting tasks and as a thought partner to sharpen her strategic thinking.

She’ll walk us through real world applications and provide actual insights on harnessing AI to elevate your marketing strategy. So buckle up, you’re about to discover the future of strategic marketing. Hey, Sonny, welcome to the show.

[00:02:59] Sunny Hunt: Thanks for having me, Mike. Gosh, that’s such a great intro. Thanks for such a warm welcome.

And I hope to live up to the expectations today.

[00:03:08] Mike Allton: It’s my pleasure. I’m super excited to talk to you. If you could start by just sharing a bit more about your background and what led you to focus on this idea of AI and marketing.

[00:03:18] Sunny Hunt: Sure. So right now I am a senior strategist at Convince and Convert, but I’m also a growth and retention architect and CEO at Hunt Interaction.

So I’m wearing a lot of hats right now. I’m very busy. I’m always looking for a way to work smarter and not necessarily harder while still maintaining a really high level of quality for all of our clients. So my background, I am, I survived the dot com boom, like way back when I don’t even want to mention years, cause that ages me horrifically.

But safe to say that I am Gen X. I’m very secure in the Gen X generation as it were. But really what I do and what I focus on right now. For as far as client services goes is I help my clients basically build better customers, build more profitable customers. So I help them reverse engineer their existing customer bases so that they can improve things like their lead quality, convert better paying customers, reduce the overall churn.

And I do a lot of primary qualitative customer research, which is incredibly valuable, but it’s really painful and time consuming. To process and parse all of those insights and then operationalize them into the customer journey. So I’m always looking for ways to again, work smarter and not necessarily harder.

And when I stumbled across generative AI tools, I think it was about six months after chat GPT dropped. It was our first six months. I was like, Oh great. Another shiny object that we have to pay attention to. Like I’ve seen so many of these things come and go that I didn’t really pay much attention to it.

Until I did pay attention to it, and then I went, Oh, this, this is a big thing. This has a huge trajectory in front of it, and it’s not going away. And I need to be part of this conversation so that I can figure out how to use it, how not to use it. And to be on board with all the different changes and evolutions as they come up, because I recognized how fast it was going to move.

So, and again, like I said, I’m GenX, I’m used to embracing new technological waves, like we went through the cell phone and social media and the internet. This is the next technological wave that we need to ride. So, that’s a little bit about me and Generally, what I’m focused on as far as using generative AI tools.

[00:05:44] Mike Allton: That makes a lot of sense cause I pretty much had the exact same journey. I was not on board with AI when it first started off, you know, we knew mutual friends like Chris Penn and so on, who’ve been in the AI and the machine language world for almost a decade. That wasn’t me. That clearly wasn’t you either, but yeah, to your point, I started Paying more attention to AI late last year, 2023, and realized, Oh, dang, word this is going to get real and I need to know what I’m doing.

My friends and colleagues need to know what they’re doing. If we’re still going to have the kinds of roles that we want to have in the future. So I appreciate you coming on and sharing your perspectives that are going to be, like I said, very similar to mine. So I’m wondering how are you currently leveraging AI as a thought partner in your marketing strategies?

[00:06:33] Sunny Hunt: Yeah, so I, I typically use the tools that I’m Using today and those, these tools change all the time. I bring on a new tool, I deprecate another tool, but I usually have two running side by side because I always like to compare and contrast the results that I get. And those results vary from day to day.

It feels like, so I always like to have that sanity check between running two tools and I do pay for them. So I have two paid tools running side by side. Right now, and this week, I’m running ChatGPT and Claude side by side. But really how I use these tools to help kind of assist me as a thought partner is I literally treat it like a thought partner.

Someone who is inside my trusted circle of colleagues, I would reach out to and say, Hey, I’m a little bit stuck with something. Can I pick your brain for a second or do you have five minutes to help me out or think through something? But I’m a little bit more free because I know that the calendar for these tools is wide open and they’re always available to me.

So one of the ways that I do this is I start off by providing situational context. Hey, I’m this, I’m doing this for this person in this situation. I never use names or anything like that because I always tend to try to keep things a lot, very anonymous, probably even more so than I can, but that’s just my preference.

But I really dig into providing a lot of that situational context. I set expectations about goals and the outputs. Like what am I trying to get out of this conversation that I’m having with you? And then I ask it to walk step by step through the specific task or the specific output. And I ask for ideas based off of those goals and outputs and literally talk out what I’m trying to accomplish.

And more specifically. I am asking it more often than not for a gap analysis. What is it that I’m missing? Did I miss any particular steps or is there something that I could be challenged on knowing these particular things or this particular outlook? What is it that I’m missing? Or, what are the objections?

If I were to present this to a client or present these recommendations to a client and I always trust the output, but I verify and then I always ask clarifying questions. Are you sure you did this right? Or can you double check your work? Can you do this? What about this? Or I go back and I challenge it.

With those gaps. So if it brings back like, Oh, you missed this and you missed this piece and you missed this piece. I’ll ask why, why did I miss those? Why are these more important than the other things that we’ve already talked about? So really, I use it as more of a conversational banter back and forth to understand.

Really what’s missing and to identify hidden opportunities that I may not have thought of before.

[00:09:20] Mike Allton: That’s amazing. I was listening to Paul Roetzer this morning, the artificial intelligence show. And he was talking about using AI the exact same way. I mean, this is a guy who’s been immersed in AI for years and years and years, and he’s still using multiple tools just like you are.

And he’s using them as a strategist. And he made this really amazing point, which is that one could argue whether AI can serve as a good or a great strategist, there’s an argument to be made there in terms of the quality of the output that you can get, but even if it’s just a good strategist, even if it’s just a good thought partner that you can turn to, you can turn to them to your point anytime a day.

I had no additional cost. Whereas, you know, if you were to try to turn to a marketing strategist or somebody else who’s a specialist in their area, they’re going to cost you hundreds of dollars per hour, and you’re going to book a time weeks, months in advance. And the other thing that I love talking about with AI is that if you aren’t happy with what you’re doing.

The output, you can tell it to do it again, you can say, give it, you know, try it again, do it again, do it again, and you can keep saying that over and over and again, and it will happily comply every time. Whereas if you ask me three times to repeat myself, Oh no, we’re done. I, I don’t like

[00:10:31] Sunny Hunt: what’s wrong with you.

Why are you like, like, did you not like the, like, this is the, this is the same answer. There, there is a caveat though. And using generative AI tools to do things like creating strategies, like net new strategies out of thin air comes at a cost and that cost is that your competition has the access to the exact same tools that you do.

So there’s. A very strong likelihood that any strategy that you get wholesale out of a generative AI tool is going to be a copy and paste that your competition already has access to or is already using. And it completely negates a couple of things. Number one, creative input based off of emotional inputs, because buying something or transactions or even consuming content is an emotional decision.

And generative AI is not really good at processing a lot of emotional factors in its responses. It’s also not good at using experience and human experiences And bringing those into the mix as well, because like I said, I’ve been, I’ve been around for a while. I remember like accidentally pushing a 404 page to a public website that was for a company that was publicly traded.

And the website, the 404 page had a, had a picture of Homer Simpson with Weezer lyrics on a ticker tape, like rolling across the top of it, right? Those are human experiences that generative AI can’t capture, harness. and incorporate into a lot of different strategies. So yes, it’s good as a thought partner, but that shouldn’t be your only resource.

You really do need to lean on people who have that experience, who have been arms deep in the trenches, figuring stuff out the hard way and making those really terrible mistakes and really incorporating a lot of input, especially from your customers. Because if you don’t know the desired outcomes of your customers, why they chose you in the first place and what they value they get out of using your product or service and how you’re making their lives better, you can’t grab that information and incorporate it into your strategy.

Your strategy is going to be really hollow, and it’s more likely than not that you’re going to miss the mark and not be able to achieve the goals that you set out to achieve.

[00:13:06] Mike Allton: That is terrific advice. Could you share an example of how you’ve worked on a recent project where you think AI has significantly enhanced your strategic practice?

[00:13:17] Sunny Hunt: Yeah. So through convince and convert recently worked on a project with the university of Arizona. They had a messaging campaign that they really needed to get out for their students. They wanted an evergreen campaign. They wanted to be able to reuse it over and over again with just only slight modifications.

They really needed to be able to get a lot of mileage out of this system. This, this campaign, just kind of a set and forget with slight tweaks and modifications as they roll through different, different semesters. And the campaign was really primarily focused on retaining students and making the registration process easy for them and proactively engaging them in the channels where they spent time, but they wanted to validate the messages that we’re going to be incorporated as part of this campaign to make sure that they were really on target and that they resonated with our students. So we ran a virtual focus group with a whole, that gathered just a ton of qualitative and quantitative information and data from different student and campus audiences and brought it all together.

But the problem with running a focus group is that it’s really time intensive to parse through all of that data and all of that information. And we were on a deadline in order to create this messaging campaign. So how do we just stay up and work late in order to do this? Or is there an opportunity to anonymize the data the student information and the response is enough that we were able to feed it into a generative AI tool and have it consolidate, parse, and stack rank the themes that came out of these specific questions from the focus group. So that’s what we did. And. Normally taking the time to go through and parse this information like you throw it into air table and you pull out the different themes for every type of responses.

And sometimes you have multiple themes per response. It’s really time intensive and it’s really good work because you become very ingrained with a lot of the responses and you get closer to the respondents and you can really develop a big sense of empathy when parse that information manually. Okay.

But we didn’t have the time, so we leaned on generative AI tools in order to help us do that. And it was able to do it 230 times faster than if we were to go through and manually parse out all that focus group information. It saved us four weeks in developing a messaging campaign. Four weeks. That’s a huge amount of time.

So, but we were also really, really careful because I operate on a trust, but verify basis with any of these tools, because I’ve kind of been burned by a couple of them in a couple of different times, but really making sure that we ran the prompts through the data analysis portion of generative AI tool multiple times in order to make sure that we got the same answer over and over again.

And we challenged it. Are you sure about this? Are you sure about that? Are you sure about this other thing? And just to make sure that we felt confident in the analysis that actually came out of these generative AI tools. And to be fair, we, we went through it and we did this question by question. We didn’t load the entire data set into, into a generative AI tool and ask it to like parse everything else.

That’s way too much information for these tools. If you go smaller and more discreet, you’re able to pull out a lot of this information. So, and a lot of, and again, just to be clear, like the information and the responses were like open ended responses that people actually typed in to this. This virtual focus group.

So we had to interpret what they were saying and overcome spelling mistakes and grammar mistakes in order to understand exactly what they were trying to say. So it was really, really helpful.

[00:17:08] Mike Allton: That’s amazing. I love those kinds of use cases. We talked about all the time on this show. Cause I think that’s extremely instructive to marketers who are trying to wrap their brains around what AI can and cannot do.

Cause it’s not like the tools that we’ve been given in the past. It’s not Canva where you look at it. You’re like, okay, this is to create an image. AI is different. Robert Rose has now famously said it’s, it’s, you can’t have an AI strategy anymore than you can have an electricity strategy. It’s, it’s baked into everything that we’re doing.

And. I love this example so much because I was having a similar conversation just earlier today, we’re recording this in late August and I was doing a live show, our MarTech show at Agorapulse. And I was talking to the founder of a company called allison. ai, which allows companies to look at their creative assets for ad campaigns.

Like think videos, graphics, headlines. Descriptive copy and analyze all of their advertisements across all time and try to decide which and how those have performed, which headlines, which images and so on, and use that information to inform new as strategy. And you can even incorporate competitors and that sort of thing.

So you can get it much wider. Look, those are the kinds of things that AI is just absolutely amazing. At that gap analysis that you mentioned earlier, right? Andy Crestodina talked about how as humans, we really struggled to identify what’s missing. You know, you can see that you’ve got an article on this topic, but you wouldn’t be able to look at my thousand blog posts and easily identify what topics I haven’t yet talked about.

But I can do that. And to your point, it can do it. So. Fast. So that’s one of the really obvious benefits I think for using AI in these kinds of scenarios. What do you think some of the other key benefits are for using AI in strategic decision making that marketers might overlook?

[00:19:05] Sunny Hunt: I think that, again, using it as a thought partner, a strategic PO thought partner to identify those gaps, I think is a really great way to do that analysis, but I also use it as a helpful intern or a really eager intern Who is capable of doing a lot of really great work But also again needs that context and that situational context the business context And kind of the slow guiding hand in order to get a lot of that stuff done it’s Really, those two ways are like the biggest opportunities that I think generative AI can really help a lot of marketers, especially with strategic issues.

I also like to do a little role playing with it, especially if I’m talking to a new client who I’ve never met before and making suggestions just like right off the cuff, that type of thing. I usually go in with a general outline. for your time. And if I do some role playing beforehand using like chat GPT or Claude, again, giving it situational context and just saying, Hey, you’re going to like try to break holes in all of these arguments.

Like, what is it that I should be prepared for? How should I react to these particular things? What are you the biggest concerns that someone in this particular role might have? It helps get me about 80 percent of the way there. That other 20 percent is going to be kind of a make or break time, but it’s going to help get you 80 percent of the way there.

Especially if you’re walking into a situation where you may feel a little uncomfortable or you may be a little unsure of what the end goal actually looks like. So just kind of mapping out what some of those opportunities could look like as well as your path forward. I think it’s great. But again, it’s not a cure all.

It’s an assist and making sure that you are embedding your human side, your experiences, making sure that you’re accounting for emotions and the roles that that plays into a decision making process, as well as Past experiences and where things can go sideways. And really understanding specifically in, in my role as a consultant, understanding what your clients are capable of executing on.

Like if you’re giving a full throated strategy, that’s designed for an enterprise and you’re handing it off to a startup, like they’re going to look at you with like, Glazed eyes because they’re not going to know what to do with it. So making sure that you understand as a human, what the scope and the intended outcome looks like is also really important because you can’t make recommendations and you, especially with strategic recommendations that the people on the other side of those recommendations have no hope of executing against.

So. Just keeping things real, realistic, and identifying that these tools are an assist rather than a complete solution.

[00:22:04] Mike Allton: That is a terrific approach and a valuable reminder. Folks, we’re talking with Sunny Hunt about her innovative approach to bringing AI alongside her for strategic thinking. In a moment, we’re going to talk about potential challenges with this approach, as well as where she sees AI going.

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No fuss. No hassle, just results ready to simplify your AI journey. Visit Magai today to learn how their solutions can revolutionize the way you engage with your audience. Don’t just market market smarter with Magai tap the link in the show notes. So Sonny, you mentioned chat GPT, you mentioned Claude earlier for marketers who are looking to bring AI into their strategic decision making processes, are there any of the tools or is that where you would start?

[00:23:46] Sunny Hunt: I like to think of myself as tool agnostic primarily because they change and evolve so quickly over time. And as a consultant who works with a variety of different clients, it’s also my job to remain flexible whenever possible. So for instance, I work with a client who is just implementing Microsoft co pilot.

So I need to know more about Microsoft co pilot and how to interact with it and the little like tweaks and the little Nuances that comes along with that particular platform. I also have clients who are running chat GPT on their phones and not necessarily on their desktops, even because there’s, you know, some discussion internally about whether or not they should be using it in the first place.

So knowing that they are, I’m giving them guidance on like, maybe don’t include this information and be really generic when you do this. And cause. People are going to use these tools, whether the, whether their businesses and their companies allow it or not. So giving them the education and the guardrails that they need in order to be successful and not damage either their personal reputation or take their businesses accidentally is something that’s also really important to me.

So again, I just try to be tool agnostic. I’m always trying out new tools and new ways of working with these individual tools. I think it’s really important to maintain a sense of curiosity and to. Really try to find a way to overcome the blank page problem. A lot of times people will sit down in front of a tool like chat GPT.

They’ve heard all these really amazing things like, Oh, it does this. And it does that and it does this other thing. But then they sit down and like. I, I don’t even, I don’t even know where to start. Like, how do I get into this? So providing people with an entry point into using some of these tools, whether it’s on a personal level or a professional level is something that I’m always encouraging people to try and to play with.

[00:25:40] Mike Allton: That makes a lot of sense. It’s kind of the same reason why I’ve always had my notifications turned on and my DMS open on every social platform, because no matter where clients or prospects or potential partners are influencers, for instance, that they need to be able to get through to me. And so yes, they can message me on Snapchat if they want to, even though I’m not.

Often there, but I love that approach with tools. I think it’s also good to have a friend who likes to use everything and be the first one to try it. Who can message us about, Hey, have you seen this? Have you seen, we can let them take that kind of time.

[00:26:12] Sunny Hunt: We all need the guinea pig friends, like just go figure it out and report back.

[00:26:17] Mike Allton: Yes, that’s, that’s exactly what my friend Chris Carr is to me. He’s always on the lookout for the newest stuff. I’m like, okay, Chris, just, Text me. That’s fantastic. So other than that time, what other kinds of challenges or limitations do you think markers might be facing if they’re thinking about integrating a I into their strategic thinking?

[00:26:39] Sunny Hunt: Yeah. So your team needs education. Number one. Your team needs to know what’s I’m going to talk about what’s allowed, what’s not allowed, how to use these tools, how to recognize when one of these tools is going to use the data that you input into it in order to train itself, because we’ve had a couple of early examples of people just dropping code into some of these tools and personally identifiable information or financial information.

Like that’s not always the best, best use for these tools. So making sure that your teams are educated on what tools they can use, what the limitations are around those tools and what they can and can’t use the outputs for. So for instance, if you have content marketers who are writing blog posts and GPT, but the output needs to be copyrightable, like there’s an issue there because.

Copyrightable content needs to be predominantly created by humans. So you can’t copyright stuff that comes directly out of these tools. So again, education is something that’s really important. And it’s a challenge that I think a lot of marketing teams are experiencing right now because they don’t know what’s what and how to actually operate with them.

But then when you’re actually using these tools, making sure that you are, again, trusting what’s coming out of them, but verifying it. So I was playing around with it and I I was playing around with chat GPT, I think it was this weekend, and I said, here’s my date of birth, here’s the time that I was born, here’s the location I was born, can you give me like my sun sign, my rising sign, my moon sign, and it got one of the three right.

I was like, Oh, that’s, that’s not good, right? So I was like, can you try it again? And it took two or three tries for it to actually get those astrological signs. Right. But that’s a great example of trust the output, but like verify it and double check it, especially if you’re like, Hmm, that doesn’t quite look right.

So, especially if you’re doing quantitative work or database work. Trust but verify, and they are also a lot of these tools are they’re just not good at complex parsing of emotional data. So if someone is having really big feelings, or if they have a comment that’s really big and really long from a survey, or even a customer interview, like you pull out a piece from a transcript and you put it into one of some of these tools.

They’re not good at pulling out things like sarcasm. And humor and when someone goes on a big emotional journey in the same comment, like they start off really happy and they end up really mad, it doesn’t pick up on that nuance. So make sure that your prompts are very specific. Make sure that you’re not asking these tools to do.

Too much or be too in the touchy feely realm versus the quantitative data realm. They tend to do better with that and also recognize that there’s still a lot of bias built into these models. So, and it’s creating unexpected challenges. A good example of that was I have been building or playing around with building a custom GPT to help me kind of capture my own voice, my own writing voice, and.

I asked it, I asked ChatGPT to update the photo on this custom ChatGPT because it had generated a picture of a marketer, but it automatically defaulted to a man, and I was like, no, this is, this is for me, like, I need a woman, and it came back with an image of three women. And I said, does it take three women to replace one man?

Like, I just asked you to swap out the gender on one of these, these images. And it took four or five times for it to actually give me an image of one woman. It kept coming back with three, three, three, one, three women. And I’m like, What is this? So just make sure that you’re recognizing that the people who built a lot of these tools are also testing a lot of these tools.

And it may not, they may not do a really good job of representing a broad or diverse group of individuals. So again, that human lens always needs to be applied to the outputs because we have different ways of viewing the world and different ways of walking through the world. And it doesn’t do a good job yet of capturing those differences.

So just be sensitive to that.

[00:31:09] Mike Allton: That is fantastic advice. And my next question is a perfect example of that because Chad GPT wanted me to ask you, how do you foresee the role of AI evolving in the marketing landscape over the next five years as a human? I know that question is kind of ridiculous because nobody knows it’s going to happen with AI in five months, let alone five years, but still the question is not bad.

I am interested in where you see AI evolving in the short term for marketers.

[00:31:38] Sunny Hunt: I am really interested in seeing where synthetic data comes into play. It’s promising, but it’s not there yet. So if you are looking for a replacement for doing time intensive customer interviews and getting a lot of qualitative data, synthetic data may be an answer, but not today.

Like I am, I’ve tried a couple of different options. Over the last like three months, and I’m not, I’m definitely not satisfied with the outputs that I’ve received, although my standards are, my standards are really high as far as quality is concerned, but if I’m going to trust my reputation and my work and my client’s businesses to these data sources, I need to be confident that they are producing the right result.

And with the right amount of detail in order to use them and incorporate them into my work. They are not there yet. I also see, and I think they’re probably going to start seeing this, this next year is a backlash against AI generated content. We’re kind of on the precipice and we’re already kind of like dipping our toes into a sea of really mediocre, crappy content that’s out there.

Like blog posts and social posts and all of this stuff. And nobody wants to consume that. There’s nothing insightful there. There’s no personality. There’s no unique insights, no unique point of view. I think we’re going to see a backlash against that. And I think in response, a lot of these models are going to get better at creating this content and more specific and incorporate a lot of that personality that’s currently missing.

But I have a feeling that we’ll still be able to pick it out pretty easily. So it’ll be interesting to see how that develops over like the next year, 18 months. And another thing that I’m really interested in watching is the evolution of assistant or task oriented models come into play. Like right now we’re just operating kind of like with a flat model that just kind of produces content for us. Some there’s some in investigation and there’s some, there’s some tools that are kind of investing in video development, which is kind of like the next step, but really allowing some of these tools to take actions on our behalf, I think is really going to be transformational.

We’re also going to have to be really, really careful when we start onboarding a lot of these tools, because if we misspeak, or if we are in the middle of a fight with somebody or we’re feeling some really big feelings about something and we have insomnia and wake up at 2 30 in the morning to like, Interact with some of these assistants.

We may find up that we’ve like booked a ticket to Bali on a vacation that we really didn’t mean to, because again, these tools will take us literally. So you’re like, Oh, I hate everything. I’m just going to go take off for a week in Bali. And it’s like, okay, wish granted. And actually take, That that course of action for you, like we’re gonna have to be careful with how these are implemented and how we interact with them in order to make sure that we are using them wisely using them responsibly and that they’re behaving in the intended manner.

But I really think that having these tools have the autonomy to take action on our behalf is going to be transformational. So I can say, Hey, I need you to go find an appointment on so and so’s calendar for, before Thursday, we need 30 minutes to talk about this, this, and this here’s the agenda. Go make that happen.

And they go out, I do it. And they come back and they’re like, great. Here’s your, here’s your meeting. It’s all booked. Like, awesome. Like we’re almost there now. So I’m going to be really interested to see how that, about how that evolves.

[00:35:12] Mike Allton: Yeah, you’re right. Those are some really cool use cases that I know are coming really soon.

Could we go back though, to your point about synthetic data? Cause I just want to make sure myself and anybody listening is clear. Are you talking about asking the AI to synthesize data? Like, like what would my target audience pain points be? Something along those lines. Is that what we’re talking about there?

[00:35:33] Sunny Hunt: Yes. So you could actually ask these tools for, I need to create a jobs to be done statement for this customer cohort, who is coming from this competitor, give me that statement. So it goes out and it simulates what that customer set would actually look like, and it brings back things like what they were struggling with.

What their alternative options were, how they evaluated their options, what their desired outcomes were, and what their motivations for looking were. Using commonly used words and phrases in order to synthesize or kind of create that customer insight on a qualitative basis so that you can get closer on an emotional level as a marketer to your customers.

And synthetic data offers the promise of being able to provide all of that insight without the heavy lifting of going out and doing customer interviews and customer surveys and ethnographic research, that type of thing.

[00:36:37] Mike Allton: That makes sense. I was talking to Ardath Albee on our B2B podcast just recently, and she was in a conversation with Andy Crestodina and he wanted to get her opinion on using AI to build personas and she’s like, I don’t think you want to talk to me.

He’s like, no, no, no. I want to talk to you. So she said, okay. And that’s her whole career is building personas for major, major corporations in the B2B space. And he’s showing her these algorithms and that sort of thing. And the question she kept coming back to was, well, how do you know that’s true? How do you know that’s accurate?

If you’re not actually talking to customers, right? If you’re just allowing the AI to generate that synthetic data, how do you know? How do you verify to your point that I don’t think you can. So that’s, that’s definitely a challenge.

[00:37:21] Sunny Hunt: Everybody is looking to build a competitive moat, right? What makes my business, what makes my product different than everybody else?

What are our competitive differentiators and who’s our competitive set? And the only people who can give you that information, Reliably are your customers. So if you’re not getting that information from your customers, you’re not really able to build a true competitive moat. And right now, synthetic data and any data that you get out of a generative AI platform is just a guess.

And it’s not even a really good guess.

[00:37:55] Mike Allton: It’s the most probable guess, or as anyone say, the most average guess. So what advice would you give to marketers who are just beginning to explore AI? A lot of our listeners, they’re relatively new to AI. They’re coming around to it but they want to use it as a tool for strategic thinking, the way we’ve been talking about today.

[00:38:14] Sunny Hunt: I would Pick a tool and start playing around with it. I would look at some of the tutorials. I would start reading some blog posts. I would start talking to other people who are doing what you want to do with these particular tools. Like I know I want to use it for marketing, but I’m not quite sure how to use it.

Start talking to people in your network who have more experience and who have already started playing around with some of these tools so that you can kind of get familiar with what’s possible and what people are actually doing with it, but then also making sure that you understand exactly what you should not be doing with it and what information you should not be giving it.

So again, that you’re not getting yourself or anybody else into significant trouble. The last thing you want to do is load up an entire spreadsheet of really sensitive customer information into chat gPT and go, what can this do? It’s not really a helpful thing to do. It’s kind of like danger, Will Robinson, don’t go there.

But play around, stay curious. Listen to podcasts like this and figure out exactly what the possibilities could look like so that you can solve that blank page problem. Cause once you start getting into it and you start experimenting and playing around with it, you start unlocking a lot of different possibilities.

And you start asking yourself, I wonder if what if and then you start executing on those what if scenarios and kind of getting to the point where you can get smarter about how to use them and how to ask for the right things and how to challenge assumptions that it gives back to you.

And also I would, if you’re in a marketing team, that’s just starting to explore this, build a council inside your company and learn at scale from each other. So like, John, what did you use it for? Oh my gosh. And Amy used it for meal planning this week. I’m like, Oh my God. I didn’t even think about it. I could use it for meal planning and like running a grocery list.

Like something as mundane as that, but still saves me a ton of time. I can analyze all of this data from like GA4. And understand exactly what our visitors are doing. And then in the next prompt, I can actually plan out my grocery meal for or my grocery list for the week. Like, but really understand and learn from each other, especially in the same company, the way you’re operating in the same guardrails, you have access to the same tools and you can make each other smarter.

[00:40:36] Mike Allton: Fantastic advice, folks. Go back and listen to that again. It’s terrific, Sunny. I’m wondering if you could finally just share any upcoming projects or initiatives that you are excited about that maybe involve AI and marketing.

[00:40:50] Sunny Hunt: Yeah, I am actually giving a talk at the Marketing Analytics and Data Science Convention.

All right. conference in October in San Diego. It’s kind of the sister conference to content marketing world. So if you’re going to content marketing world, you can actually just kind of cross over to Matt’s and come see me talk, but I’m going to be going more in detail and providing specific examples around parsing that qualitative data from a focus group so that we could create a messaging campaign.

And I will be presenting with the marketing director from the university of Arizona. It’s going to be amazing. And I am really excited.

[00:41:25] Mike Allton: That is awesome folks go check out sunny at that event And if they can’t make it to the event, but they have more questions for you. Where can they go?

[00:41:33] Sunny Hunt: Find me on linkedin.

I I think they’re only like one maybe two sunny hunts in the entire platform But i’m the one with the the red hair and the glasses So feel free to connect with me on linkedin and let me know if That you heard me here on the podcast.

[00:41:49] Mike Allton: Terrific. We’ll have Sunny’s LinkedIn and all the other notes and links that we talked about today in the show notes.

Don’t forget to find the AI in Marketing: Unpacked podcast on Apple and drop me a review. I’d love to know what you think until next time. Welcome. Thanks for joining us on AI in Marketing: Unpacked. I hope today’s episode has inspired you and given you actionable insights to integrate AI into your marketing strategies.

You enjoyed the show, subscribe on your favorite podcast platform and consider leaving a review. We’d love to hear your thoughts and answer any questions you might have. Don’t forget to join us next time as we continue to simplify AI and help you make a real impact in your marketing efforts until then keep innovating and see just how far AI can take your marketing.

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