Pax (00:21)
Chris, thank you so much for joining us today. Pleasure to have you on.

Chris (00:24)
Hey Paxton, so thanks a lot for being here.

Pax (00:27)
Yeah. I think it would be a great way to start our conversation today, ⁓ asking you in your consulting work and the work that you've done, what do you see are some of the most common or biggest mistakes companies are making when it comes to their messaging and their positioning?

Chris (00:45)
Yeah, so I think ⁓ it's an interesting question because I think probably the first mistake that I see is that they don't really understand the difference between positioning and messaging. So a lot of the work is actually while we work on those is to make it clear, clearly separate the two steps in the workflow so that they have a good understanding of, we're doing this positioning now because we need to know...

what we need to know at this step, and then the next step is the messaging. So ⁓ the way that I define positioning is basically understanding what you do, who you do it for, and how you do it better, uniquely, or in different way. So I typically use a simple one-pager positioning canvas, but most of the work there happens in a live workshop. Next is the messaging work, which is actually starting to define how you say all of that, and that's through different lenses, which could be your pitch.

your strategic narrative, different example of value proposition from a gain loss logic or benefit perspective, for example, and your brand voice as well. So first, I would probably say, yeah, lot of companies don't really have a clear idea of what positioning and messaging are and how you kind of move from one to the other. ⁓

The other one, would probably say a lot of companies when it comes to actually writing the copy, so once you've done positioning and messaging and you need to write the actual words on a page, the first thing that they jump to is they want to say what they do, right? Which is a bit counterintuitive, but that's probably not the first step. You want to, on the page, the first thing that you want to do is actually to match what people are thinking when they land on your page or when they see your email or when they...

look at your sales deck. So you want to kind of match their motivation, their intent, their awareness. And so when you first start by telling them, this is what we do, they might stumble on some friction right away, which is probably something that you don't want to do. And the other one is probably, I see a lot of people mistakenly ⁓ consider their messaging more of like the actual creative assets that you deliver or that you create.

rather than thinking of messaging as, I think of it as like the architecture and like a system that you install in your company and that you can refer to at any point, any touch point with your customers. And then you can constantly iterate on, optimize and yeah, being the actual architecture infrastructure inside your company that drives all your marketing initiatives.

Pax (03:30)
Yeah. Yeah. When I was studying advertising, we would talk about an idea having legs, meaning like it's not the one off execution of that idea, but that idea can be expressed in many different formats and media. ⁓ that to me seems like that's what true messaging is, not the actual asset. Like the asset is the execution of the messaging, basically. Right. ⁓

Chris (03:37)
Yeah.

Exactly, exactly.

Pax (03:59)
You said when a company says straight out, this is what we do, that it introduces the opportunity for the customer to encounter some friction. What do you mean by that? Like what kind of friction?

Chris (04:12)
Yeah, so what I mean is that as soon as someone lands on your page and the first thing they do is start talking about you yourself rather than themselves, they immediately experience some kind of ⁓ friction, as I said, which in practical terms means they might bounce on the page or they might be instantly skeptical about your message. And so it already starts getting a bit harder to convert them. When on other hand, if...

the first thing they do is actually writing and speaking to their motivations, pain points, desired outcomes. The first decision that they need to take, which is the decision to scroll down or to keep reading, it's already done, right? For them, it's, okay, you're basically already telling me what I want to hear. Let's keep scrolling and let's keep going down the page.

Pax (05:06)
Yeah, that's a great, like what's, if you're saying stuff about me and what I care about, what's to disagree with really, there's no, not scroll. I love that. ⁓ so let's get into audience. and message. I do want to touch on audience research. That is a huge point. I think a point of friction for a lot of companies before we get to that point, though, I do want to ask.

Chris (05:12)
Yeah, exactly.

Pax (05:34)
How much does message change depending on audience? And is there a limit, like a rule of thumb that you would say a brand should spread their message amongst different audiences? You know, I've seen companies where it's like, hey, we're for everybody. And so I have these 20 different, I'm for accountants, I'm for HR, I'm for mortgage loan officers. And it's like, man, how can you possibly...

Chris (05:44)
Hmm.

Pax (06:02)
have messaging effective for all these people? Like, is there a rule of thumb or a cap or how do you think about that?

Chris (06:07)
Yeah, so I think that that's a totally fair question and something that I see a lot of people get confused on. there's totally the need to have all of those different assets, different pages. Those are very useful when you need to match intent, especially now with AI or like AI search and that needs to see real intent. But I think that the cap, as you called it, it's

Part of the messaging strategy is defining your strategic narrative and what is your point of view, right? The insight, the reason why you built the product. So something that you saw in the market that was being done wrong or some mistakes that only you have seen customers make and that led you to building your solution. I think that is the actual overarching narrative or lens that you need to have.

And then the specific pain points, those can change based on the different personas and should change, especially in B2B when you have a lot of different stakeholders and decision-making unit, all of those dynamics. But it's important to maintain that strategic narrative and that point of view. So then with that top of mind, then you can change the minutiae, like the pain points, the motivations, and reframe the benefits in terms of those specific personas.

Pax (07:32)
So let's get into those personas. ⁓ There's a...

a trait that a lot of marketers have ⁓ that I've noticed, which is like, we love to sit behind the screen where it's safe and ⁓ kind of execute all of our stuff. it like getting out in front of that and talking to customers and talking to learning more about the audience is kind of where a lot of people tend to get stuck. ⁓ You know, and when we don't know a lot about an audience, one of the

hallmarks of a brand that doesn't know a lot about their audiences, they go to competitors and they say, well, what are competitors saying? Let's just say that, or let's just say that, but better versus just saying like, go to the audience, ⁓ allowing you to say something new potentially. ⁓ So I think the reason people get stuck on it is the concept of audience research can be viewed as like super fluffy.

And it's hard to say there's an exact formula to it because when you've, you know, it's like saying, where is the gold in the Hill? You know, it's like, I don't know, but you've got to dig until you find it. So it's not, so I think people get stuck on that. What, what, what's your take? Like, first off, is there a place for competitive research when you're looking at building out your messaging? And then number two, how should brands approach the market research?

portion of like building out their messaging strategy.

Chris (09:05)
Yeah, so tackling the first point, competitive research, I think that's totally the place for competitive research, but not in the sense, okay, these are our competitors, let's copy them. So what I mean by actual competitive research and how I see and think about competitive research is looking at the other players in the market, in the industry, and trying to deconstruct what they're doing from a lens of we know what our SCPs are.

We know what the pain points, benefits that we need to address are, and also we need to know how other companies are solving for all of those. This way, you kind of establish the benchmarks, right? So it's important to understand what other players are doing so that you can differentiate yourself. But also, there's a bit more of a meta deconstruction that I try to do, which is looking at competitors' messaging and trying to deconstruct what kind of

personas they are speaking to and in what way, right? So that we can differentiate both maybe on the personas or the roles that we can address if our product is better for them, but also with the language that we use. So a lot of, if you look at any competitor's website or messaging, a very simple framework that I like to use to kind of deconstruct what they're doing. It's, I got it from the Mech Labs Institute. So.

It's a very good resource if you're into conversion optimization. You can check that out. And they have a very good heuristic, but in simple terms, it's divided in four areas. So at the top of the page, you typically have the motivation section, which basically it's anything that you write to match the user's desired outcomes, pain points, or purchase prompts. So any copy that you see at the top, that's your motivation section. And you can start, I don't know,

categorizing all the copy that you see, dividing it into themes, organizing it and create your different competitive research assets. Second section is typically the value section. So what are they doing? What are the features that they ⁓ promote? What are the benefits associated with those features? Then we have the proof section, which is how do they back up all of those claims? Or how do they address objections?

After that, the anxiety sections, which is all about social proof and making sure that people are not encountering any of friction that we were talking about. So with these simple sections, you can already start getting an idea of how competitors are writing their copy, using their messaging to address visitors, or even in an email, it's pretty much the same formula.

And through that, you start already understanding, these guys are addressing, I don't know how familiar listeners are with the level of awareness. So from ⁓ unaware, there's problem aware, solution aware, product aware, and most aware, right? ⁓ By looking at the copy in this way, categorizing it, you already start putting what they're doing into those kind of buckets. You can say, okay, this competitor is addressing maybe problem aware customers or product aware.

Pax (12:11)
Mm-hmm.

Chris (12:24)
So maybe we have room to adjust the solution aware, right? So trying to find the gaps that you can cover, or maybe just to get insights on what other players in the market are doing. this is probably one way that I would try to deconstruct competitors. The other one is probably looking at reviews. especially if you don't have a lot of reviews for your own platform, you can go on websites like G2 or Captera.

and look at your competitors' reviews. Those give you a goldmine of insights on the language that their customers use, the features that maybe they complain about, and all sorts of good insights and voiceover customer that you can actually reuse and mirror in your copy. So this is probably the way that I would look at your competitors, but not copy their messaging.

Pax (13:14)
Yeah,

yeah, I like that. ⁓ Something that we've talked about too is it's important to know what the competitors are saying. Also because it's the messages that your audience is hearing when they're doing research. So like the sites that they're looking at, they're not just looking at your site, they're looking at the competitor sites too as they're evaluating options.

And it's helpful to know what messages are they being fed? What context are they being given? What does the landscape look like? Not so that we can copy the landscape, but so that we know how to better stand out within that landscape, right?

Chris (13:55)
Yeah, totally. And you can see in sales meetings, you can ask people what other solutions they were considering. And you can see, they bringing up some of the copy that competitors use, like Verbatim, and see, okay, is this sticking with them or not?

Pax (14:12)
Yeah. You've talked on some other podcasts about using the language that your audience uses in your messaging. How do you, you've mentioned reviews. What are some other ways that you kind of harvest that the language that they're using?

Chris (14:29)
Yeah, so 70 % of my work is research, I would say. So if you think about conversion copy, like think less about writing and more about research, I would say. But in that research, there's a lot of different ways that you could gather language. The most important, like the 80-20 way, if you need to kind of optimize, it's obviously speaking with customers, so conducting interviews and...

That's what we said before, right? A lot of people are kind of scared of going out. I was scared myself. Like the first two years, I wasn't conducting interviews. I was just doing service because I was basically terrified. And so you kind of have to break through that fear. But like interviews give you probably the best and most vivid voice of customer in a language that you can actually use through your copy. Other ways, surveys.

So basically those pop-ups, they appear on website. You can ask simple. It's a mix of, I would say of qualitative and quantitative data, especially if you have a lot of traffic. So you can start understanding who your ICPs are with qualifying questions like what brought you to the site today or what best describes you and give them a couple of options. Or you can ask questions on their frictions, objections that they have maybe on pricing page. You ask them

what's preventing you from signing up today, and you can already start getting some of that voice of customer. Another way that I typically like to do, especially if we struggle to get interviews, is to send ⁓ email surveys. So just an email invite with a link, sending them to a survey. And the survey, contrary to what a lot of people think, it's a lot of open-ended questions.

And you would be surprised, but if you have product market fit, if your customers are happy, a lot of them are going to like fill those out gladly. Right. So, and those give you a lot of great, great insights as well, because when you leave like the open field and you have like a large text field, people, especially if you're, I don't know, maybe it's the fact that they're not on camera, not recording, they might feel like more...

more able to express themselves in writing, some people especially. So you get a lot of good insights that you can actually categorize in spreadsheets. So it's also convenient on the front. And the other probably another good way is to maybe run some message testing. So platforms like Winter are pretty good. Or the other way, which is a bit ⁓ of a controversy lately, it's the...

using synthetic research. So in that sense, use platforms that simulate your customer personas and could give you some voice of customers, In quotes, the voice of customers. But that all depends ⁓ on how good your real human research is in the first place. I would never just do synthetic research. I would always use it as a complement to real human customer research.

Pax (17:42)
Yeah. So I have a couple of questions on this, and I do want to get to the synthetic research and some AI stuff. ⁓ Before that, when you talk about using their language, so let's say you send out this survey and you get these open responses back. What level of using their language, like what are we talking about here? you saying, I'm taking their exact words and I'm just flipping them back into the copy. Are you mimicking their

tone, their level of formality. Like what is it in there that you're like, how would somebody approach that?

Chris (18:19)
Yeah, it varies a lot. would say depending on the type of voice of customer that we have, some of those snippets are very good to just literally take and use as headlines, but it all depends on how vivid they are, how specifically they represent the pain points and motivations that you uncovered in research. And especially if you see a lot of people kind of repeating the same words, that's a clear sign that you could actually use that.

like verbatim on the page, just because it's, again, it's part of the conversation that a lot of people are having. But in general, like even if it's just one single word, maybe I'm writing copy and I'm kind of debating, I use this word or that other word? Then I jump into my voice of customer bank.

And I literally do a common F search and I see what kind of words did they use for this specific use case or to define this specific thing that I'm trying to describe. And I literally go in and use the most used word that I see in my Vossor customer. I think, yeah, it depends on first your goal for the type of copy, but also on how vivid and how frequently mentioned that specific words or sentence is.

in your voice of customer.

Pax (19:39)
Do you have a story you'd be willing to share where that was particularly effective or you found some kind of unique verbiage that you ended up using that really worked?

Chris (19:49)
I don't remember the specific verbiage, but there was a... So this client I worked with a couple of years ago, it was a very unique ⁓ type of client because it was a B2B SaaS, but in a field which basically their customers hated software. And so this company was trying to sell them software, right? And the company was selling software for ⁓ portable, toilet.

and septic container management. So super ultra specific and very like blue collar almost like the people they were trying to sell the software to are like very like experienced 50 year old, 60 year old owners who never really actually touched any software. Maybe they use spreadsheets at best. And so we used that with, we did some customer interviews and we used a lot of the specific words that they were.

using some of them were like very in the US and they were the US California I think and so like very characteristic voice of customer that you might only see these guys use and that's that was super important because on the on the how it works page rather than just doing I don't know these are the features that we offer maybe divided into groups by specific use cases what we did was quite unique because we

We kind of turned the how it works page into like a diary of a typical day of one of these guys at work, because we knew from research that they wanted to see their kind of daily activity reflected in their copy, right? So we literally said, when you get to work, this is the first thing that you do with the software. You jump in, you log in your route for the container and blah, blah, blah. And then your driver takes on the software and then this is what happens, right?

completely matching and setting expectations at every step using some of their voice of customers as well.

Pax (21:46)
And it was successful.

Chris (21:48)
Yeah, was like, think increased conversion 20 % from the previous version across the site.

Pax (21:54)
Yeah.

Yeah, that's awesome.

So let's let's talk AI. ⁓ First, let's touch on this like synthetic research or so ⁓ I've always felt and I haven't I haven't done this myself. So I'll say that. But from the research that I've done on it, it's always felt like it was some it was like a layer of unnecessary redundancy.

The idea being like, do all this research to understand my audience. gather all this information. And then I now feed this information into AI. And then I say, pretend to be my audience. And I'm to give you messaging and you tell me whether or not you respond to it. By the point where I have enough information to feed the AI accurate representation of my audience.

I should now know my audience and so I should already kind of know the answer to the question, you know? And so it's always struck me as just kind of being this weird, unnecessary, like a tool looking for a use rather than actually useful. How's your experience been?

Chris (23:05)
Mmm. Yeah.

Yeah, that's a totally fair point. I see, like, especially from the point of view of a company who's got lots of customers, lots of data as well, very good system to collect that data and use it. It's probably like overkill in that sense, or maybe not even useful, right? But maybe the differentiators or the better use cases for synthetic research, I think, are in case when you're maybe just starting out.

and you maybe don't have access to customers or very little data in that case, use synthetic research. If you don't get to a hundred percent accuracy for a company from an early stage startup that does starting out, even getting to 60%, 65, 70 % accuracy, it's already gold that you can actually use to get started, get your website up, get some email series done, rather than procrastinating or...

wasting a lot of time maybe in communities. So that's probably one good use case. And the other use case is when you have some research, but not a lot still. maybe you have, and that's probably the case for a lot of my clients, some of my clients. Maybe we are able to only conduct five customer interviews compared to maybe the 10 or 15 that we normally run, right?

And there might be a lot of different in terms of the percentage of the data, the statistical data you cover between five and even 10 interviews, right? So with synthetic research, that's probably a very good use case. You can take those five interview transcripts, feed them to the AI and kind of expand your data and get more specific as well if you don't have a lot of very specific detail on your personas.

or even expand into asking them questions that you haven't asked them in the interviews. And also probably the final use case is to scale, but also systematize your research. Because if you imagine ⁓ one goal that I'm trying to kind of build for my clients as well is to kind of install a continuous research system as well. How do you install research that runs in the background continuously looking at market trends or how...

competition changes, or maybe you launch new products, now you need to research again, how can you install some kind of research that runs in the background and always gives you fresh data that you can actually readily use for writing your messaging and develop your marketing, right? So synthetic research, it's a very good use case for that, especially when you start plugging it with APIs that link to your systems, or maybe even if you just want to test creative in your ads.

Before even launching your ads, you could test it with synthetic research, a couple of variants, and only launch the variant that wins in your ads. Those could be useful ways to use synthetic research because of the speed, the cost, and the ability to install it inside your systems.

Pax (26:20)
Yeah, okay. So what platforms are you using for this?

Chris (26:28)
Yeah, so the ones that I tried, so I did it first myself. I literally, at the beginning, was literally taking all the research that I did for clients and built my own kind of repositories. When I started doing it, we still didn't have projects in JunGPT or cloud. Now you can build a project with all the research that you have and kind of start prompting AI to kind of wear the shoes of this persona.

But now there's platform like Synthetic Users is a very good one, especially if you want to conduct ⁓ usability product development research. Another one, it's called askrally.com, rally. So that's a very good one if you just want to basically build your personas at scale, like you could build 25, 50, 100 personas, all different personas wearing the shoes of your roles, right?

And that's very good if you want to test marketing, messaging, because you can basically chat with your personas, ask them questions, and it gives you like ⁓ a glomerate response, and then you can dig into the individual response. And a lot of the things that these platforms, I mean, the platform that do synthetic research right are doing that you should actually look for when you look for synthetic research platforms.

It's to look how they are addressing bias, for example. Are they trying to ⁓ make sure that the AI is not super positive and wants to praise you all the time? Are they trying to kind of ⁓ coordinate all of those little aspects and nuances? And also, how are they building those personas based on your role? So if you tell them, okay, we have a CMO persona.

a head of growth persona and a founder, then they need to kind of replicate and distribute your 100 or 200 personas across those three roles. What's the split, right? How are they doing it? ⁓ All of those kind of help you get more realistic data. And that's typically embedded in the algorithms that these platforms built in.

Pax (28:41)
Yeah,

okay, cool. So I think that makes sense. ⁓ It's a great use for if you don't have enough data. And then the ongoing research in the background, I think, is really interesting. Did you say that's something that you are doing or that's something you're trying to figure out how to...

Chris (29:01)
I'm trying to

figure out, but some of these platforms are already so rally, I think it's launching their API soon, and then you can start working with tools like NA10 to make that automated. And so that's very super interesting, and I'm excited to try it out.

Pax (29:14)
Yeah.

Yeah, I mean, you could theoretically just build that into any workflow. Hey, here's my newsletter before it goes out. It automatically goes, you there's an end trigger goes into invalidates and then makes a jet. Yeah, that's very cool. ⁓ So I let's talk about like the content production and AI. We've talked about the kind of content validation and AI. ⁓ I know that you have a framework called path. ⁓ Walk us like through that that framework.

Chris (29:30)
Yeah.

Hmm?

Yeah, so this is kind of the framework that I came up with when I was building my own personas, right? Just because of need and necessity. So the first one, it's the P, the prepare. So in that sense, it's basically conducting real human research or trying to collect as much as possible of typically I try to cover three areas in my research, which are the internal research, which it's anything about speaking with the team, my client's team, learning about the product.

looking at support, chat transcripts, all of that. Then the external side of research is divided into the prospect customer and also non-buyer, right? Trying to understand all of those three areas. And finally, the market research is looking at competitors, like we said, competitors' reviews. So trying to cover as much as possible of those three areas in the preparation. ⁓

Then the second stage is the articulation, and this is where we basically generate our AI personas. So in this case, we feed all of the research to AI personas. typically, if you do it manually, which is not going to be as accurate as if you use some of those platforms because of those algorithms and all the things that we mentioned. But I mean, if you want to get some quick testing done, I tested a couple of email sequences, I tested headlines, and it works.

pretty well, just to give you confirmation, maybe, if you have lot of different variants that you want to pick from. And in the articulation, I try to use LLMs that ⁓ have a big context window. So for this purpose, I used to use Gemini. Now there's 2.5. That's because it had a biggest context window. Now I think most LLMs, even Chaggpt with projects, have pretty big context windows. So you could probably use any of those.

but I would keep that in mind ⁓ as a factor. What's the context window so that you can feed as much information as possible because those transcripts tend to get quite long when you feed them. And then I basically prompt the AI in a separate chat. So I have one chat, which is typically my marketing chat. It's kind of the strategist or assistant, right? Helps me come up with ideas or variations.

And then we have the actual persona chat or different personas chats. And I use a simple prompt that basically instructs the AI to wear the shoes of this persona, never break character. And also I like to give it ⁓ like another tag that's called thoughts. So that at the beginning of every response, it gives me their thoughts, like what's going on in their head. And then it expresses those thoughts in kind of like what they're actually saying virtually, right? And so this is kind of the persona.

The next stage is the test stage. So in this case, we want to run different scenarios, probe assumption, simulate the different responses, probe for objections, all of the... It's pretty cool because everything that you can come up with, you can do it. So it's like having a conversation with any of your customers. You can ask them any questions. So at the beginning, it's quite spooky, but pretty cool. And the final stage, which is the H, harmonize.

It's basically where we combine all of the findings that we have, and then we relaunch another round of research. So maybe some of the findings pointed out that this persona resonates more with ⁓ specific messaging angle. We might test that in our sales conversations and see how those perform. So what the reaction of real human personas are, right? And that refeed everything into the cycle. It's basically like a flywheel, like a cycle.

This is pretty much the path framework that I came up with.

Pax (33:34)
Yeah, I love that. And with this, you're saying one of those platforms that you talked about, like you would operate this entire thing in a single platform or are you kind of mixing ⁓ any of these for different purposes?

Chris (33:50)
Those platforms can actually handle everything for you, so you don't really need to switch. If I did that internally with different platforms, obviously it's bit more disjointed, but you also have some control as well, some fine-tuning and control. When I did it internally for myself, for my clients, I started with Gemini for the context window, then shifted to Claude, mostly for the writing of different variants.

And then after cloud, especially because cloud, you have like even with the first paid plans, you start stumbling on limits for cloud. So I start to, I started to use another platform, which is a third party platform that plugs into cloud's API. And it's nice because I can use it with my team as well. So you can collaborate on the same chats. And ⁓ especially once the research, the messaging strategy is done, then we basically use the same client project and each of us writes with the same exact voice.

hitting the same exact messaging pillars, using the same research. And so it's pretty cool to see how also faster it is if you have maybe a new team member come in, how to have them write copy. That's almost 90 % good first draft, even if they have never jumped into any of the research that we did for clients.

Pax (35:12)
Wow. That's, that's really cool. ⁓ I, I feel like I already know your answer to this question, but I'll ask it anyway, which is like, think a lot of people are worried about AI and copywriting if that's their skill set. ⁓ do you think that, fear is warranted? I, I'm pretty certain your answer is going to be no. ⁓ but, ⁓ to, to,

drive a little deeper down into that. like, what do you think is the, will become the role of the copywriter in the future as AI continues to develop?

Chris (35:52)
Yeah, obviously I'm a bit biased, but I would say no. But in the sense that what I'm seeing, it's all the copywriters that are anti-AI. Then you ask them what tools did you actually use? What's your experience? And then they might say, I use the free version of Chagypti, and that's it. And that's probably 80 % of them, right? So it makes me wonder, how deep did you actually go into actually trying these tools?

Pax (35:56)
you

Chris (36:20)
because that's not been my experience. And I say, if you rely on formulas, templates, when you're writing copy, then probably AI can replace you. But the thing that it can't really replace you now, but I would say probably in the future as well, if you have a strategic vision, so if you know that the copy comes from the research work, then there's the strategy in between, and then you can't really write any word without all of those...

foundations, then I would say you can still be the effective copywriter using AI. And I think the role of copywriter moving forward is going to be more and more of the architect or kind of orchestrator of these kind of AI systems, just because a lot of the writing is basically done for you. So you need to kind of...

know when to jump in, when to be the human in the loop inside these systems, how to set them up, and of course, have that copywriter's intuition or taste for what works. That's super valuable when you go in and edit the final copy, because there's still a lot of editing and I suspect that's probably never going to change. You still want to be kind of the human to kind of empathize, especially if you immersed yourself in a lot of research to start with, you know.

and what works and what ⁓ feels human. So that's probably the last step that it will still maintain.

Pax (37:53)
Yeah. And I think, tell me if you agree with this, but it seems like the human, like you mentioned immersing yourself in the research, it's still going to be important. And I think for some people, the temptation is going to be like, great. Well, if I've got these AI tools, I don't even really understand or look at this information. I could just feed it in here, get the output and it's like done. I was like, nah, actually you kind of still do need to do that part of the job. Would you agree with that?

Chris (38:21)
Yeah, yeah, totally. still, I mean, now I love doing customer interviews, so like I wouldn't give them up for like any reason. And it's still important because I think like a lot of these platforms, synthetic research can actually do like interviews for you, like written interviews and interview your AI personas. But I think one of the most valuable aspects of doing real customer interviews when you are in front of the person, either virtually or in person.

It's actually to be able to follow the conversation, even if you have a script of questions, to be able to follow the conversation intuitively and see where it goes, like follow wherever it leads and kind of being able to ask more nuanced questions based on where the conversation goes. So it's not just as scripted as just having like a responding to a survey, right? So that's super important, I think, to still be the human immersing yourself and also same for...

looking at a lot of reviews, like you want to kind of jump in and absorb some of the language. So when it comes time to actually doing the writing or editing, if that's most of what you're doing, you will still have that taste and that sense of what works because you absorbed it.

Pax (39:34)
Yeah. I think that's some really great parting advice for our audience. Thank you so much for joining us today. feel like what you've talked about is, you know, people often say like AI is about augmenting and making you more powerful. But at the end of the day, how many people are actually doing that? And I think what you've laid out here is a really great framework and plan to actually augment and not

just replace or ⁓ in some cases have some sort of subpar output. Like this is actually ⁓ allowing the human to do what the human does best and allowing the computer to do what the computer does best. ⁓ So thank you for highlighting that and that framework path. We're going to ⁓ write something up about that on what you can find at niceinflor.com. Also, ⁓ Chris, where would it be the place for our listeners to connect with you?

Chris (40:33)
Yes, so you can find me on my website at conversionalchemy.net where I have a scorecard where you can try free and kind of gives you an idea for where you stand in terms of copy strategy. And also I'm typically on LinkedIn, so you can find me there, connect, and we can have a chat about anything.

Pax (40:50)
Okay, all right, well thank you so much for being on the show. ⁓ It was a really great conversation, appreciate it.

Chris (40:56)
Thanks so much, bye.