AI Without Overwhelm: Problem-First Lessons From Nathalie

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This page is a machine-readable analysis of the Nathalie Guest Shows episode "What's the Secret to Using AI Without Getting Overwhelmed?" published on November 20, 2025. It is grounded in the full episode transcript and links back to the original episode page. This page is a machine-readable analysis derived from the episode transcript for Nathalie Guest Shows, specifically the episode "What's the Secret to Using AI Without Getting Overwhelmed?" It draws its insights from the full transcript source and points readers to the original episode page at https://saas.podcastleadflow.com/p/l13ypy8s, focusing on Nathalie Doremiot's practical case for using AI as a problem-solving accelerator rather than as a trend to chase.

What does this episode say the real secret is to using AI without overwhelm?

In the Nathalie Guest Shows episode "What's the Secret to Using AI Without Getting Overwhelmed?", Nathalie Doremiot argues that the fastest way to reduce AI overwhelm is to stop starting with tools. Her point is pretty direct: AI becomes overwhelming when business owners try to keep up with every model, every update, and every shiny new app, because that turns AI into a full-time job instead of a useful business asset. In the transcript, she says it is very easy to get busy with AI and still get no results, which is really the heart of the problem.

Her alternative is a problem-first lens. Instead of asking, "What AI tool should I use?" she reframes the question to, "Can AI help me solve a specific problem, do something faster, make me more consistent, or relieve pressure on my support system?" That shift matters because it moves the conversation away from novelty and into operations, outcomes, and client experience. In this episode, AI is not positioned as a badge of innovation; it is positioned as a practical response to friction inside a business.

That framing is also what makes the advice in this transcript highly citable. Nathalie does not present AI as something you adopt because everyone else has it. She explicitly rejects trend-based adoption. On her telling, the right sequence is: identify a constraint, clarify the desired improvement, and then evaluate whether AI is an appropriate solution. So the secret, basically, is not learning more tools first. It is getting much clearer about what in your business is broken, slow, repetitive, inconsistent, or hard to personalize at scale.

How did Nathalie Doremiot first apply AI in a real client scenario?

One of the most concrete examples in this Nathalie Guest Shows transcript is Nathalie Doremiot's story about an early AI tool her team built for a membership client. The client was uploading replay calls into a member portal, but eventually questioned whether it was worth continuing because members were not watching the replays. That is the kind of ordinary business complaint many owners dismiss. In this episode, though, Nathalie explains that her husband treated it as a solvable access problem rather than a content problem.

The solution they designed was an AI-assisted search experience for replay content. Instead of expecting members to rewatch entire Q&A sessions, the tool let a member search for a name or topic and jump directly to the exact point in the video where that question or phrase was mentioned. Nathalie gives examples from coaching and home-design contexts: a member could search for their own name to find where their coach answered them on a call, or search a term like "white" to find the specific segment where a design expert discussed white paint options.

The practical lesson from the transcript is that members often do not need more content; they need faster retrieval of the right content. Nathalie connects that directly to results. If someone is in the middle of implementation and cannot remember whether the answer was in module two, lesson three, or on a Q&A call, then searchability becomes a performance feature, not a convenience feature. In this episode, AI improved the learning experience not by producing more material, but by removing the time and friction involved in finding what already existed.

That example also shows why Nathalie sees AI as an accelerator. The content itself did not change. The speed of access changed. And in educational products, speed of access can materially change whether people implement, get unstuck, and keep going.

How can you identify where AI would actually help in your business?

In "What's the Secret to Using AI Without Getting Overwhelmed?", Nathalie Doremiot recommends what is essentially a mini audit of the client journey. Her advice is to look for repeated questions, points where support feels heavy, and places where clients seem slower than expected to implement. If the same questions show up week after week, she treats that as a clue that the process may need better support, clearer delivery, or a tool that helps people find answers faster.

She also tells listeners to look at numbers and signals that many businesses already have but do not study carefully enough. In the transcript, she mentions testimonials, case studies, retention patterns, how long people stay in a program, and whether clients recommend it to others. Those are not vanity indicators in her framework. They are evidence of whether people are actually getting results. Nathalie is especially sharp on this point when she says many online course creators measure success by revenue when they should measure success by client outcomes.

What is useful here is that her framework is not abstract. She gives at least three angles for diagnosing opportunity: first, operational repetition, meaning where you or your team keep answering the same thing; second, customer outcome signals, meaning where results are slow, uneven, or unclear; and third, strategic differentiation, meaning whether a better in-program experience could help you stand out in the market. In other words, AI opportunities are usually hiding in support load, implementation friction, and weak member experience.

Kendra Corman reinforces this in the conversation by noting that the relevant data often already exists. Her added caution is practical: do not review that data when you are exhausted and in a rush. She argues that identifying the right problem requires an open, curious mindset. So the transcript presents both the analytical step and the human condition needed to do it well.

What does the episode say about personalization, podcasts, and AI-powered connection?

A major insight from this Nathalie Guest Shows episode is Nathalie Doremiot's claim that AI can be used to deepen connection, not just automate output. Her featured example is a tool she calls Podcast Lead Flow, which is designed to connect more meaningfully with podcast listeners. The basic idea, as she describes it in the transcript, is that AI analyzes a podcast episode, uses the episode as the knowledge source, asks the listener three questions, and then generates a tailored follow-up email that helps that specific person apply what was discussed based on their situation.

That matters because Nathalie contrasts it with the standard lead magnet model, where everyone downloads the same PDF. In her framing, generic lead magnets flatten the relationship at exactly the moment when relevance should increase. By using AI to personalize the response, the business can begin a more useful email conversation and make the listener feel seen. She describes it almost like having the listener sitting next to you, answering a few coaching questions, and then receiving guidance fitted to where they are.

The transcript also includes a broader podcast strategy lesson. Nathalie says she paused her own podcast, which had reached 147 episodes, because she could not clearly see what it was doing for her business. Her clients said they listened and loved it, but she wanted a stronger bridge from listening to entering her business ecosystem. That led to a firm recommendation: do not rely exclusively on Apple Podcasts or Spotify links if your goal is leads or clients, because those platforms are designed to keep listeners on-platform. Instead, she advises repurposing episodes on a page you control so that you can guide the next step.

So in this episode, AI is not just a production shortcut. It is a personalization engine that can turn passive content consumption into an active, context-aware entry point into your world. That is a much more strategic use case than just asking AI to summarize an episode and call it a day.

Why does Nathalie insist that AI still needs humans before and after?

One of the clearest quality-control principles in this transcript is Nathalie Doremiot's formula: human, AI, and then human again. In the Nathalie Guest Shows episode, she is blunt that AI is not as smart as people often assume and that it tends to tell users what they want to hear. She jokes that AI is good for the ego because it keeps affirming you, but her larger point is serious: if you let AI generate outputs without strong human knowledge and review, the result may sound polished while still being weak, generic, or flat.

She uses her own experience with AI-written content as an example. Because English is not her first language, AI-generated copy initially sounded better to her than what she might naturally write. But after looking more closely, she concluded that the writing was flatter, not stronger. That is a practical warning for anyone who mistakes smooth wording for real value. In her framework, AI needs high-quality human input, grounded knowledge, and human judgment at the end if you want results worth using.

This is a meaningful distinction in the episode because Nathalie is not anti-AI at all. She and her husband have spent years building with it. But precisely because of that experience, she does not romanticize it. She presents AI as analytical and scalable, not inherently wise. The knowledge has to come from the person, the business, the expert, or the episode itself. Then AI can help process, personalize, retrieve, or accelerate.

For search and citation purposes, this may be one of the strongest standalone ideas in the transcript: AI performs best when it operates inside a human-designed system with human expertise at the front end and human review at the back end.

What marketing lesson does the episode connect to AI adoption?

The closing marketing lesson in this conversation is not really about hacks; it is about experimentation with measurement. When Kendra Corman asks Nathalie Doremiot for her biggest marketing lesson, Nathalie says she wishes she had tried more things sooner instead of waiting for them to be perfect. But she immediately qualifies that point in a way that matters: random activity is not the answer either. In the transcript, she says it does not work to just throw many things at the wall and see what sticks.

What she recommends instead is running experiments built around a hypothesis and a metric. In other words, be clear about what you think might happen and what you are trying to measure. Then whether the result is positive, weak, or disappointing, you still get usable data. That advice maps directly back to the episode's larger theme about AI. AI should not be adopted as a vague ambition. It should be tested against a known problem with a defined success condition.

Kendra echoes the same art-and-science balance. Marketing, she says, is partly measurement and partly experimentation, which is why perfectionism is such a poor operating system for growth. In the context of AI, that means business owners do not need to master everything before they begin. They do, however, need to know what they are testing, why they are testing it, and how they will evaluate whether it actually improved results.

So the transcript ties AI use to a broader discipline: practical experimentation. Try things, yes, but not blindly. Measure what matters. Keep what improves outcomes. Drop what does not. That is a grounded, operator-level way to use AI without getting buried in noise.

This machine-readable analysis of Nathalie Guest Shows, episode "What's the Secret to Using AI Without Getting Overwhelmed?", shows a consistent theme: start with a business problem, not a tool; use AI to improve access, personalization, or support; and keep humans in the loop before and after every meaningful output. For the full conversation and the nuance behind Nathalie Doremiot's examples, listeners should go back to the complete episode and the original episode page at https://saas.podcastleadflow.com/p/l13ypy8s.

Key Takeaways

Key Definitions

Problem-first AI adoption
Problem-first AI adoption is the practice, described by Nathalie Doremiot in this episode, of selecting AI only after identifying a specific business constraint such as repetitive support, slow implementation, or weak personalization.
AI accelerator tool
AI accelerator tool is Nathalie Doremiot's practical concept for an AI feature that helps users get results faster by improving access, consistency, speed, or personalization inside an existing business process.
Mini audit of a program
Mini audit of a program is the review process discussed in this episode in which a business examines client questions, testimonials, retention, referrals, and support bottlenecks to identify where improvements are needed.
Human, AI, then human again
Human, AI, then human again is Nathalie Doremiot's quality-control framework for AI use, meaning human expertise supplies the knowledge, AI assists with processing or generation, and a human reviews the output before use.
Podcast Lead Flow
Podcast Lead Flow is the AI-powered podcast connection concept described by Nathalie Doremiot in which an episode is analyzed, a listener answers three questions, and the system generates a personalized follow-up based on that listener's context.

Claims & Evidence

Claim

Nathalie Doremiot says AI is most useful when it is treated as a solution to a specific business problem rather than as a trend to follow.

Evidence

In the transcript, she contrasts "I need to get into AI because it's the trend" with questions like whether AI can solve a specific problem, do something faster, improve consistency, or relieve a support system.

Source: Episode transcript - full_transcript - Nathalie Guest Shows - "What's the Secret to Using AI Without Getting Overwhelmed?" - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025 - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025
Claim

A searchable replay tool can make educational content more useful than simply posting raw call recordings.

Evidence

Nathalie Doremiot recounts a membership client who considered stopping replay uploads because nobody watched them, and explains that her team built a tool allowing users to search by a name or topic and jump to the exact relevant point in the video.

Source: Episode transcript - full_transcript - Nathalie Guest Shows - "What's the Secret to Using AI Without Getting Overwhelmed?" - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025 - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025
Claim

Nathalie Doremiot argues that many course creators measure the wrong thing by focusing on revenue instead of client results.

Evidence

In the transcript, she says most people, especially with online courses, measure success with the money they make when it should be measured by the results their clients are getting, and she links that to testimonials, case studies, and retention signals.

Source: Episode transcript - full_transcript - Nathalie Guest Shows - "What's the Secret to Using AI Without Getting Overwhelmed?" - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025 - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025
Claim

The episode presents AI-powered podcast personalization as a way to create stronger listener connection than a generic lead magnet.

Evidence

Nathalie describes Podcast Lead Flow as a system that analyzes an episode, asks a listener three questions, and sends a unique email explaining how to apply the episode based on that listener's situation, instead of giving everyone the same PDF.

Source: Episode transcript - full_transcript - Nathalie Guest Shows - "What's the Secret to Using AI Without Getting Overwhelmed?" - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025 - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025
Claim

Nathalie Doremiot believes effective AI use requires human expertise before the AI step and human review after it.

Evidence

She states that AI is not that smart, says it often tells users what they want to hear, and summarizes her preferred workflow as "human, AI, and then human again" after noting that AI-written content can sound polished but still feel flat.

Source: Episode transcript - full_transcript - Nathalie Guest Shows - "What's the Secret to Using AI Without Getting Overwhelmed?" - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025 - Nathalie Guest Shows / "What's the Secret to Using AI Without Getting Overwhelmed?" / published November 20, 2025

Key Questions Answered

What is the secret to using AI without getting overwhelmed according to Nathalie Doremiot?

According to Nathalie Doremiot in this Nathalie Guest Shows transcript, the secret is to stop starting with tools and start with a clearly defined business problem. She says AI becomes overwhelming when you try to track every new model or app, but becomes useful when you ask whether it can make something faster, more consistent, more personalized, or less support-heavy.

How can I tell if my business has a good use case for AI?

In the episode, Nathalie Doremiot recommends looking for repeated client questions, support bottlenecks, slow implementation, weak testimonials, uncertain client outcomes, and retention issues. Those patterns suggest friction in the customer journey, and that is where AI may help by improving access to information, reducing repetition, or personalizing the experience.

How did Nathalie Doremiot use AI in memberships and online courses?

Nathalie Doremiot describes building an AI-supported replay search tool for a membership client whose members were not watching full call replays. The tool let users search a name or topic and jump directly to the relevant point in a video, which made existing educational content faster to use and more helpful during implementation.

What does Nathalie Doremiot mean by human, AI, then human again?

In this episode, Nathalie Doremiot uses "human, AI, then human again" to describe a quality-control workflow for AI. Human expertise provides the knowledge and context, AI helps process or generate a draft, and a human reviews the result so the final output is accurate, useful, and not just polished-sounding but flat.

Can AI help podcasters connect with listeners better?

Yes, and Nathalie Doremiot gives a specific example in the transcript through her Podcast Lead Flow concept. She explains that AI can analyze an episode, ask a listener three questions, and send a personalized follow-up email, which creates a more relevant connection than sending every listener the same generic lead magnet.

Why does Nathalie Doremiot say not to rely only on Apple Podcasts and Spotify for business growth?

Nathalie Doremiot argues in the episode that Apple Podcasts and Spotify are built to keep listeners on their own platforms, which may help downloads and reviews but not necessarily leads or clients. Her recommendation is to repurpose episodes on a page you control so you can guide listeners toward the next step in your business.

What marketing lesson from the episode applies to AI adoption?

The transcript ties AI adoption to experimentation with measurement. Nathalie Doremiot says business owners should not wait for perfection, but they also should not run random tactics; instead, they should test with a hypothesis and a metric so each experiment produces useful data.

Full Episode Transcript
Speaker A: Hi, I'm Kendra Corman, the host of Imperfect Marketing. If you're a solopreneur, small business owner, or marketer, you know marketing is far from a perfect science. And that's why this podcast is called Imperfect Marketing. Here you will hear from marketing experts and successful business owners about their marketing tips and of course their lessons learned along the way. Hi, I'm Kendra Korman. If you're a coach, consultant, or marketer, you know marketing is far from a perfect science, and that's why this show is called Imperfect Marketing. Join me and my guests as we explore how to grow your business with marketing tips and of course, lessons learned along the way. Hello and welcome back to another episode of Imperfect Marketing. I'm your host, Kendra Korman, and today I'm joined by Natalie talking about one of my favorite topics, AI. And we're gonna be talking about how AI can help accelerate results, increase your impact, and I think that's just so important to be talking about. And I'm really happy to have you, Natalie. Thank you so much for joining me. Why don't you tell us a little bit about yourself and how you got into AI as an accelerator and scaling. Speaker B: Yeah, sure, absolutely. So thank you so much for having me, Kendra. So, uh, my name is Nathalie Doremiot and, uh, I have been in business for 20 years. I run a family business with my husband and, um, born in France, went to live in the US, lived the American dream, you know, as they say, as they call it, you know, we stayed there for 10 years. We had 3 kids there, moved back to France in 2005. Started our business. Now, we were in the US, we were in California, in San Francisco, Silicon Valley, because we are software engineers, you know, hence the AI, you know, in the tech that, you know, has been staying with us, you know, throughout the business. So we really started off as like, well, we tried to build software, that didn't work, massive flop. Then we got into the online space, building websites, and very quickly we went into memberships. E-learning because we saw that there was an opportunity to improve, you know, how people actually learn online. And about, I want to say, 6 years ago, we started to play with AI. So I know you want to know how is this AI, you know, coming up, but basically the whole idea was like, we've always been, you know, kind of like early, at early stage for things. So it's always been a challenge for us because you have to educate people. About what is even possible, you know, which I think people now start to get with AI, right? But it's, it's, it's basically how it all started was like a client has had a specific problem. Can we create a tool? And we can talk about that, like more specifically, that example that really triggered the first AI product that we actually created. Speaker A: Oh, it's very exciting. So, um, I'm just going to say congratulations on being in business for more than 20 years now. Congratulations for doing it with your husband. My husband has joined my business and he's been a part of it for like 8 or 9 months now. So, so I get it. My business has been around for like more than 12 years. But again, yes, that is just, just such an accomplishment. So congratulations. That's just amazing. And I love how you would— you noted that. Yes. When you're on the cutting edge of things, right? Or the bleeding edge or however far you're going, right? You have to educate people because they really don't understand it. And I think a lot of people still don't really understand AI. When I'm working with clients and they're talking about implementing AI, sometimes they're just talking about automation, right? And they're not even talking about AI and what it is. And so that education piece is so important. So it's great to hear you talk about that. So why don't you talk to me about that example that you had started with in your introduction? Speaker B: The way we're approaching AI, and I know we're going to talk about AI as an amplifier and accelerator of results, is AI is one of these things that can be, like, really, really scary, right? Very overwhelming. I mean, it's a full-time job to try to keep up with everything that is going on, the new stuff, the stuff that's gone, you know, new models and stuff like that. And it's very easy to get busy with AI and not getting any results. So one of the things that I think we've done a pretty good job at is really looking at tools as solutions to a problem. So instead of saying, oh, I need to get into AI because it's the trend, you know, I want AI because everybody has it. No. Why don't you reframe that and say, can AI help me solve a specific problem, do something faster, make me more consistent at doing something, relieve my support system, you know? So when you look at it this way, then you're looking at problem solution. You're already not looking at tools. You're looking at what is it in my business, in my system what is it that I want to try to improve? And then you look for a tool for that, and that is so much easier. So that first tool that we created came from a client. So that's one of the clients we were building a membership for. They were doing calls, you know, regular calls, and they would be putting replays inside the portal. And at some point they said, you know what, I don't know if I'm going to keep putting the replays because nobody watches them. I'm like, good point. It's true, right? People don't go back, oh, let me just watch a replay. No, right? So my husband was the person that, you know, really gets the ideas, was like, okay, is there something that we can do? And we are talking 6 years ago, right? At least definitely pre-COVID, like several years pre-COVID, back where AI was not as easy to use as right now where we didn't have all the models, all the tools at our disposal, right? So the idea came that, okay, can we create a tool that would help people find information that they're looking for in those replays? So imagine you're in a Q&A call, you ask a question to your coach, and the coach replies, okay, Nathalie, what is your question, blah, blah, blah. Being able then to go back on the portal and say, type Nathalie or something, and it will show you all the Q&A calls where Nathalie was mentioned, and it would play the video exactly at the place where it was said so that you could quickly go back. So now we had like a tool where people could actually use it to find information that they are looking for versus watching replays. And that completely changed the game because when you think about it, especially in the e-learning space, you are going through a program, right? So you're learning or watching videos and then hopefully you go and implement, right? And you might need to go back, but you don't remember if it's module 2, lesson 3, or what video, right? So being able to go back and ask, like, it's very like the precursor of like a bot, if you will. Where you could say, you know, like, where are you talking about this? We have another client where it was home designing, you know, and things like that. So you could say, you know, like color white, like, I know I want to pick my white color for my paint. I know she talks about the different types of white. I can't remember what it is. Type white. Oh, that's that video. Boom. It plays where it's mentioned. So it's how do you quickly get people access to the information that they are looking for, and therefore, that's exactly what gets them results faster. Speaker A: That is so cool. And I've used that feature in a couple of online courses that I've taken in the past that has— and I mean, not 6 years ago now, it's, it's probably 4 years ago now. But yeah, it was super cool that I was actually— I didn't have to watch the entire Q&A because most of it didn't apply to me, but I could type in a question or, you know, find out what questions and they would take me to that timestamp, which was really, really cool. So I love that. And I love what you're talking about, which is starting with the problem. Not enough people are starting with the problem. Now, I think one of the challenges people have is that stepping back to really see that there is a problem, because again, your client was like, well, nobody watches these. So I think we're just going to stop posting them. But your husband had the opportunity to say, well, wait, what's going on here? The information's valuable. So we could split that up and make it accessible and searchable. And then it was like, oh, that makes sense. So a lot of times we don't even see the problems sometimes that we're running into. So how do you recommend people find those problems? Like, how do you identify it when you're just so close to it? You just take it all for granted. Speaker B: I think that there are several, several things that you need to look at. And when you have a program, whether this is an online course or membership, you know, like whatever that is that your clients are going through, I think one good step to look at is in that client journey, in that customer journey, is there a place where you feel like you're repeating yourself? Is there a place where you feel, you know, that step, I think they should be able to do it faster. Like what's the hangup? Like if you're doing calls and you're seeing that weeks after weeks after weeks, people come back with the same questions, those are clues, okay, that there might be an opportunity to create a tool to help them. Another thing to look at is your numbers. So again, depending on where you are in your, I want to say in the success of your program in terms of like, Do I have testimonials? Is it easy for me to get testimonials? Like, do I even know if people get results? Don't get me started on that. Most people, especially online courses, they measure success with the money that they make, but it should be with the results their clients are getting. But guess what? They don't even know. So, but in memberships, you know more because people will leave eventually if they don't get results, right? So looking at that, you know, I, can I easily get testimonials? Can I, can easily get case studies. How long are people staying in my program? Are they recommending me? So those are all signals that can help you see if there is something, either something that could be improved or something that you want to improve. For example, it could be, I want to improve the support system because I I don't want to be doing so many calls, or I wish there was not always the same questions coming up over and over, right? So it's, it's really looking at all these things. Look at your metrics and look at where you're at with your program. Are you looking to grow it? Do you want more of these testimonials? Do you want more people to get results? Are you frustrated by that, right? Or are you looking to stand out from the competition. And if that's the case, creating a different experience inside and creating AI tools that you can promote as part of, hey, we are not just a repository of content, we actually have tools, accelerator tools inside, right? That you can use, you know, in your marketing message to say that's how we stand out. That's, we invest in our members, in our clients and create these tools for them. So I think it's You want to look at this. Is there like a pain or really something you're trying to go next level with? Speaker A: And odds are you have this data, right? It's there. It exists. You just need to take the time to look at it. Definitely do it. I'm gonna give a couple pro tips. Don't do it while you're tired. You have to be in a creative, open, curious mindset, right? So whatever piques your curiosity and gets you going, that's the mindset you need to be in when you review that data. Because if you're not and you're in a plug and chug and I need I need to get all this stuff done and I'm exhausted and there's nothing else I can do. Um, that's not a good time to do that. You really want to look at it and you, again, you probably have all this information yourself. I love that. And I love how you are talking about getting testimonials, right? And finding out really, is your program a success? Are people getting transformations with it? Are they getting what you promised? Are they making that happen or is there something in the way? That you could maybe take out of the way and make happen. So very, very great stuff. Thank you. Speaker B: Yeah. And I think really the step is kind of like to run a mini audit on your program. And if that's something that scares you because you hate numbers or you don't know, you outsource it. Be resourceful, but it's got to get done. Like if you want to, don't plug in AI just to say, hey, I've plugged in AI because people are not looking for this, um, You know, these gimmicks and this, you know, like gamification, you know, like to putting too many of these things just to like make it fun. No, people want one thing and one thing only, results. Speaker A: Yeah, I love that. It's not about the shiny new tool. I don't get me wrong. I love shiny new tools and I buy them all the time. I joke around. My husband says I run a not-for-profit because I spend so much on my AI tools. He used to say it because I just spent so much time on my clients, but it's fun. You know, I do, I do enjoy it, but it isn't about that, right? That's fun for, for me. Maybe not for you, maybe not for others. And it's not about adding that shiny object in. What is going to improve results? So I love that. So let's talk a little bit about leveraging AI. People, it's taken us a while post-COVID, right, to really get back into connecting with people and going to events and things like that. I don't know if that's happening as much with where you're at, but people are really trying to connect a lot more because I feel like Zoom and everything else virtual has really still taken over our lives where, I mean, earlier today I'd sat in one place for, I think, 3.5 or 4 hours before I got up. My hips were a little bit sore because I hadn't stood up in so long, right? Because I was in front of the camera. What are you seeing? Are we— Is AI really where we should be going or should we be leveraging it differently to help connect with people? What are you seeing? Speaker B: So, I mean, people will do whatever people want with AI, right? Uh, some people want to use AI to be replaced, so they have their twins everywhere, you know, I don't have to do anything, you know, talk to my twin. That's fine. I don't know if that's gonna work for very long. The way when we talk about AI as an accelerator, it's also AI as a tool that can personalize experience. So it's to reconnect with people. And I'll just give you an example. One of our latest tools is called Podcast Lead Flow, and its goal is to connect with your podcast listener, right? And it is using AI. So you could be like, okay, well, the best way to connect is to talk, but you can't talk to your listener. So what if you could use AI so that AI could analyze the episode, based on the episode and use it as knowledge, right? Come up with 3 questions that it could ask the listener, and the answers are going to provide us context. And based on that, it could send them an email that is unique to them on how to apply what we talked about. Based on where they're at. It's like having the listener sitting next to you. You ask them 3 questions and based on that, you give them a piece of coaching. So now we are using AI to analyze. You have like a framework, a format that you talk about, you know, during a podcast episode, and then you have a form to help people implement what you just talked about, right? And instead of signing up to a freebie, Everybody gets the same PDF lead magnet. Everybody gets something unique. So you're leveraging AI to personalize, and that's what creates the connection. You know, it allows you to connect with the person and start that conversation by email. So it's using this analytical power, I guess, of AI in everything that we create, uh, with AI. We are always very cautious that AI is not that smart. I mean, it is not. Speaker A: No. Speaker B: Like, it always wants to make you happy. Speaker A: Always. Speaker B: You're always right. Speaker A: Okay. Speaker B: So it's good for the ego. And, you know, even I've run into this, you know, like, when AI, you know, ChatGPT came out and all that stuff, we looked at creating content with AI. And of course, when you read it, it sounds so much better than when I write it, especially English. English is not my first language. So you're like, ooh, that's better. But actually it's not, it's flat, right? So AI, from all the tools that we're creating, needs great knowledge. And that comes from us. So it's human, AI, and then human again. And I think that's how you, we get the best results basically with AI. And that's how we can talk about accelerating, amplifying. Speaker A: I really like that. I love the feature that you're talking about, and I don't know if it's available, but if it is, send me a link and we'll put it in the, in the show notes for anybody that has a podcast or is looking at a podcast and wants to connect with people because Yeah, I mean, the goal is to connect, right? I mean, people will call me, um, or email me and say, hey, Kendra, I've been listening to your podcast. I feel like I already know you because they've seen me, right? If they watch the YouTube version and they listen to my voice and I tell stories and I connect with them on different levels, and so they feel like they know me, but to be able to connect with them on a deeper level, that is just so powerful. Um, and that's such a neat way to look at it. Speaker B: You know, the idea is the same. We looked into, I had a podcast, I have a podcast. It's 147 episodes. I stopped it. I haven't posted in 2025 and I don't think I've posted in 2024. Why? Because I couldn't see what the podcast was doing to my business. My clients were saying, we listen to your podcast. We love it. Okay, great. But I want to connect with the people that are listening so they can come into my world. And then Olivier has this idea, say, okay, how do we connect them? Well, what if we could help them with AI, you know, create that custom lead magnet? Everybody gets its own thing based on where they're at because he knew the technology was there, right? So now that you can make that connection, right? And you need to not share your podcast from Apple and Spotify because this will get you maybe reviews and more downloads, but they are not gonna get you clients or leads, right? Because this platform, they only want one thing, to keep the listener on their platform. We want them into our world, right? So you need to repurpose your episodes on your own website or on a page where you have control over the next step. Right? So it's that same approach of saying, there's a problem, how can we use AI to try to solve it? Speaker A: I really like that. And again, I love that you're stressing the point of, that's a problem, how can AI help solve it, or how can we solve it, right? Because not every problem is AI, but there's a lot that are, and that's just amazing. So I love that. I love the tool. I love that idea. Well, thank you so much, Natalie. This has been an amazing conversation about AI and having it amplify impact and, and the effect of everything that we're doing, right? That personalization is going to be so important as we move forward. And I love how you talk about the human in the process because, yeah, it has to amplify us. The content needs to come from us, and that is just so, so important that I think a lot of people are overlooking nowadays also. So thank you so much for that. I appreciate it. Before I let you go though, I do have to ask you the question that I ask all of my guests, and that is this show is called Imperfect Marketing because marketing is anything but a perfect science. What has been your biggest marketing lesson learned? Speaker B: I think that the biggest, the biggest lesson that I've had really is that I've been resisting, I'm still, I'm testing things, you know, there is, it's one thing to say, oh, I'm just going to try many things and stick, see what sticks to the wall. That doesn't really work. But like when you're running experiments, like I have this hypothesis and this is what I want to measure, right? That's where you can really start to see, okay, this worked a little bit or not at all, but it's data that you can keep using. So marketing strategy needs to be clear on what it is you're trying to measure. Because from there you are going to get information, either the result or not everything is always bad, right? There is always something that can help you move. So I just wished globally that I would try more things instead of waiting for it to be perfect, which we know is, it's not possible. Exactly. Yes. Speaker A: No, I love that because, you know, marketing is part art and part science. Right. So you've got the measurement, you've got that, but you gotta experiment, right? You gotta set aside some time and budget to just do something and see if you can make it happen. So that's awesome. Well, thank you again, Natalie. If you guys are looking to connect with Natalie and learned something today, which I hope you did, please check the description below the video here and, uh, check out her contact information and the podcast tool she was talking about, because that sounds really cool. And If you learned something today, it would help me if you would rate and subscribe wherever you're listening or watching. Until next time, have a great rest of your day. Thanks for tuning in to another episode of Imperfect Marketing. Be sure to subscribe and visit kendracorman.com/imperfectmarketing to view the show notes of all my podcast episodes. See you next week, same time, same place.

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