
The Product Manager · 2025-10-21 · 30 min
Key moments - from our scoring
Substance score
62 / 100
Five dimensions, 20 points each
Product teams typically fail at conversion optimization by treating features as standalone selling points rather than understanding the emotional, functional, and social outcomes buyers actually seek. Chris Silvestri brings a background merging software engineering with marketing psychology to decode what's really happening in a buyer's mind during evaluation. He introduces Bob Moesta's Jobs to be Done framework - covering three sources of motivation (functional, emotional, social) and the four forces of progress (current situation pain, solution magnetism, anxiety about switching, habit of the present) - as a lens for understanding decision-making. Beyond theory, Silvestri shares how he repositioned Moz Pro away from "all-in-one SEO platform" messaging toward "simplicity," and their API product toward "trusted data," both grounded in actual customer research rather than company assumptions. He highlights the critical misalignment between marketing and product teams, the need for qualitative research (customer interviews, support transcripts, review mining) alongside quantitative data, and the emerging challenge of optimizing messaging for both human and AI agent audiences in an AEO-dominated landscape.
Most product teams ask transactional questions like 'what features did you value most?' but fail to dig into the actual decision-making process and psychology behind why buyers chose them. They need qualitative research (customer interviews, support transcripts, review mining) to understand not just what features matter, but why people make the decision and what language they use to describe their needs.
Strip away fluff and provide clear, fact-based messaging optimized for readability by both humans and AI agents. Buzzwords like 'optimize' have lost meaning; instead, focus on specific outcomes and benefits that are both emotionally resonant and factually differentiated, ensuring agents can accurately surface your message to users searching through AI.
Jobs to be Done identifies three sources of motivation (functional: what the product does; emotional: how it makes you feel; social: how it impacts your relationships) and four forces of progress (current pain pushing you, solution magnetism pulling you, anxiety about switching, and habit of the present holding you back). Understanding these helps product teams craft messaging that addresses all forces simultaneously.
Use thank-you page surveys, exit-intent surveys on pricing pages, and website traffic analysis to understand what brings someone to a page or why they sign up. Personalize and customize messaging for those specific moments of receptivity based on the context and needs they reveal.
Misalignment causes wrong expectations - marketing may promise ease while onboarding is complex, or product may assume messaging reflects actual buyer motivation when it doesn't. When both teams understand buyer psychology and decision-making, they can ensure consistent messaging and experience across the website, onboarding, and in-product, removing friction.
Our reviewer’s read on each dimension, with quotes from the episode.
The episode contains several useful frameworks (job-to-be-done energy sources, four forces of progress, MPG messaging framework) and practical research approaches (thank you page surveys, three-layer research system), but much of the content rehashes established marketing principles without significant novelty. The Moz example provides some concrete insight, but significant portions involve restating obvious concepts like 'benefits over features' and 'understand your customer.'
people don't really look at your features standalone as like packages, but they consider them as part of a conversation that they're having different trade-offs that they're making
the three sources of energy or motivation, which is functional, emotional, and the social one, how does the product impact the way that I relate to other people
While the guest introduces some structured frameworks (particularly the messaging percentage table based on market/solution maturity), most concepts are drawn from existing sources (Bob Moesta's jobs-to-be-done, standard conversion optimization practices). The agent/AI writing angle is timely but underdeveloped - no concrete examples of how messaging actually differs for agents versus humans. The MPG mnemonic is a minor original contribution but lacks depth.
I have a literally a table that based on where you fit, whether you are established solution in a new market...it gives you the percentages of benefits versus the features versus the differentiators
you basically have to write for another audience rather than your SAP, which is the agent audience
Chris Silvestri is a founder of a specialized messaging/UX consultancy and demonstrates genuine practitioner experience (worked with Moz, ran usability testing, former software engineer and UX lead). However, he is primarily a consultant/agency owner rather than a product leader at a major company at scale, and his examples are somewhat dated (Moz acquisition happened years prior to 2025). He has relevant hands-on experience but not the senior operator credibility of a VP/Chief Product Officer who has built products to scale.
I was a software engineer, industrial automation. I did that for 10 years...I decided to found conversion Alchemy 2021
I worked at an agency as UX lead
The Moz case study provides useful specificity (positioning shift from 'all-in-one' to 'simplicity,' ICP shift from agencies to in-house teams, API positioning around 'trusted data'). However, most other claims lack concrete data: no metrics on conversion lift, no specific numbers, vague references to 'hundreds of usability tests,' and abstract advice on AI agents without actual examples. Research recommendations are tactical but lack evidence of impact.
for Moz Pro, they were messaging it as the all-in-one SEO platform...we realized, okay, the best buyers actually use Moz Pro because they want to simplify their SEO
we didn't really care about specific use cases of the API, what they wanted the most from Moz API...was the trusted data that the API was using
Hannah asks reasonable setup questions and shows engagement (e.g., connecting to prior episodes, asking for concrete examples), but rarely pushes back or challenges claims. She accepts frameworks without requesting evidence of their efficacy. Follow-ups are surface-level ('tell me more about...') rather than probing. The host misses opportunities to ask: what's the actual conversion lift from repositioning? How do you measure success with agents? What percentage of traffic now comes from AI vs. human search? Conversational energy is friendly but intellectually unchallenging.
That's really useful. And it actually, that to me feels like it kind of connects to something we talked about in our previous episode
Can you walk us through what does foundational research look like for product teams
Computed from the transcript - who did the talking, and the words that came up most.
Every product team faces the same monster: conversion optimization. But in 2025, the game has changed. With AI agents influencing discovery and AEO (Answer Engine Optimization) reshaping how people (and machines) interpret messaging, teams are now marketing to both human and agentic audiences. In this episode, Hannah Clark sits down with Chris Silvestri, founder of Conversion Alchemy , to unpack how product teams can use psychology and UX insights to craft messaging that drives both adoption and retention. A former software engineer turned conversion strategist, Chris explains how understanding human decision-making - and now machine reasoning - can help product leaders turn features into irresistible outcomes. Resources from this episode:
Transcribed and scored by The B2B Podcast Index.
Every product-led organization, no matter how exceptional their portfolio, shares the same ongoing battle, optimizing conversions. And when it comes to messaging for growth, adoption and retention, changes in user needs and behaviors have always kept us on our toes. But now, with AEO dominating search and AI agents joining the workforce in mass, it feels like we're doing battle with a mythical Hydra, optimizing for both human and agentic brains at the same time. And while it may indeed seem like a Herculean task, you have more tools than ever to win the war.
You just need to know how to use them. My guest today is Chris Silvestri, founder of Conversion Alchemy, a firm that helps companies craft messaging with a UX and psychology informed approach. Chris is a former software engineer, so he's got a knack for merging right brain marketing thinking with left brain analysis and development methods. You'll hear him debunk the wrong assumptions that stifle acquisition channels, decode the frameworks that can help your value proposition land with all of your audiences, and discern the elements of messaging that are costing you dearly to overlook.
Let's jump in. Oh, by the way, we hold conversations like this every week, so if this sounds interesting to you, why not subscribe? Okay, now let's jump in. Chris, thank you for joining me today.
Hey Hannah! Thank you so much for having me. Excited to be here. Yeah, excited to talk about this topic.
So before we get started, can you tell us a little bit about your background and how you got to where you are today? Yeah, so it's a bit of a weird background. I was a software engineer, industrial automation. I did that for 10 years, and then I wanted something more flexible, so I started learning marketing, did a couple of different things.
I worked at an agency as UX lead, and then in 2021. Still passionate about copywriting, which I started back then I decided to found conversion Alchemy 2021. It's basically my combination of copywriting, user experience, and psychology. All different skills that I've learned throughout the years, you know, different backgrounds.
So today we're gonna be talking about buyer psychology, which is a super interesting topic for me. I think that this is like something that connects to just about every role. Marketing for sure. But we're talking to product leaders here.
So when we're talking about building features that users want, there's usually a gap between what people say that they want and what actually drives them to convert. So what would you say are the biggest misconceptions that you see product teams having about buyer psychology specifically? Yeah, so as you said, lots of features. Features is a big focus, and I think that the problem is that they also think that people buy on features when in reality it's all about the outcomes that they get from those features.
I'm not talking strictly about messaging or marketing around benefits over features, but it's actually understanding that people don't really look at your features standalone as like packages, but they consider them as part of a conversation that they're having different trade-offs that they're making. So it's important to look at what those features get them, and not only what those features do for them. Another one is probably that a lot of product people, from what I've seen when I jump into working with companies is that when it comes to research, they do a lot of great product development research.
They ask, okay, what features did you value the most? What would you want to see next? And they don't dig enough into the decision making process, which, yes, it's super helpful for marketing. But I think it can also be of massive value to product people, understanding how people make decisions, why they come to conclude that Dr.
Product is the right choice for them. And so I think digging into the decision making process and the psychology behind it, it's probably super valuable for product people as well. Yeah. That makes sense.
It sounds to me kinda like you're saying that they're looking more at what was gonna appeal to existing customers versus like what kind of things do you need to know about people who are potential prospects, yeah. Okay. I think that we'd agree that figuring out how to drive conversion is kind of like the biggest make or break challenge that product that organizations will face. So what are some of the most common conversion optimization mistakes that you see product teams making and what tends to be missing?
So one I think stems from kind of misalignment or the disconnect between marketing and product. Which is the fact that messaging, but also the experience is probably that there's like gap between the marketing side of things and the product also between the user experiencing, for example, the website and then the onboarding or the in-product experience. A lot of times what I'm seeing, because I run a lot of usability testing on the marketing side of things as well. What I'm seeing is that there's a lot of like.
Wrong expectations created by the marketing for people going into the product, or vice versa. So people who are into the product who are expecting something that were probably misaligned with what we're seeing now. And so that's kind of that we are disconnect between marketing and product. Another one is probably relying on AB testing without actual questions to answer or like testing random things bit randomly, right without plan.
The other one, which is huge from normal branding agencies, but I also see it for, when it comes to product, people who actually have to maybe build some pages or work on product, which is the copy usually comes after the design when a lot of times it should actually guide and inform the design and the experience. Yeah. As someone with the background in marketing seen a lot of that, then that presents a very specific challenge. So I'm really curious about this psychology that you've mentioned before.
'cause you'd mentioned that's a big part of what the work that you're doing. So when it comes to biop psychology, when someone is evaluating, say like a B2B SaaS product or solution, what's really happening in their mind when they're making these critical decisions? Like in the lead up to signing up or making a purchase? Yeah, so I like to think as, and them having a conversation inside their heads.
So they're already asking themselves question like, is this for me? Do I trust these people? Do I believe. Myself as well.
Like, do I have the skills or do I have enough knowledge to be able to use this product successfully? And so it's all about them having this conversation. And then when they land on your website or the pricing page or start the onboarding, it's this conversation that keeps on going and either moves them forward, pushes them, or kind of prevents them and miss them with friction, right? So it's all about, I think, understanding that conversation and you do it with all the research that we typically do.
Which again brings us back to that decision making process and understanding all of that. Another great framework that I like always using in my research is I learned from Bob Mata, the one of the ideators of the job to be done framework theory. And so he talks all about the three sources of energy or motivation, which is functional. So what does the product do Emotional.
How does the product make me feel and the social one, how does the product impact the way that I relate to other people? So it's important to understand those people are kind of considering those energy sources, those are the energy sources that push them into actually making that decision. And so it's super important to understand those. Then you have the four forces of progress.
So whenever you make a decision, you have these conflicting forces that are pulling and pushing you, and this a content battle going on. You have the push of the current situation, which can be a pain or problem you're experiencing. Then the magnetism of the new solution. So you are starting to consider new solution and you see, okay, this product can do this for me.
So maybe it's time for me to evaluate and start considering it. So it's pulling me, and then you have the anxiety of this new solution because at the same time, this new solution could be hard to switch to, or maybe you are not ready for it for this technology. So it, it's solve considerations that you're taking into account. And then there's also the habit of the present, what you are already doing, right?
So it's all about considering the switching costs and the trade offs that you need to make. And so. When you start thinking of about it this way, so this conversation, these forces all conflicting. Then you start asking yourself, okay, how can I truly understand what's going on here?
What questions do I need to ask myself so that their experience is seamless between starting that decision, taking that decision, and also after the decision moving to onboarding, to using the product. So, yeah, this is the way that I think about it. There's actually a super simple simplified framework that I come up with. It's mostly because I'm a muscle car fanatic, and so I call it the MPG, so like miles per gallon, like you have a fuel efficiencies like fuel economy.
You should also have fuel economy for your messaging. Your messaging should take you as far as possible, and with M, I mean you should match the motivation of your people. With a P is you should prove your value and also prove that other people like your SAP use the product. Then the G is, you should guide them through making the decision and also after confirming to them that they made the right decision.
So this is just a quick memory useful mnemonic device that I came up with. That's really useful. And it actually, that to me feels like it kind of connects to something we talked about in our previous episode, which was all about how people learn, like the psychology of learning and acquiring new information. And I'm kind of seeing kind of a connect because.
In that episode with Maxine Anderson, who's the CPO of Aris, we were talking about how when someone is open to learning information is usually because they've reached a point where they're in the moment of critical need, where they actually feel like that information is contextually relevant to what they're doing. And I kind of feel like there's something there about optimizing your approach so that not only your messaging kind of matches that specific need or that information that they contextually seek, but also the moment to purchase or the right kind of context.
Like, kind of to supplement what you just said, is there a sort of optimization guidance that you would give? In terms of like, where should you be delivering your messages? Like how do you kind of find the right contextual moment to reach your user when they're receptive to that messaging? Yeah, so one thing that I like to do to understand that, so knowing where and how to do it, it's like can vary a lot.
But to understand, at least to get some insight, I like to do these like thank you page surveys, for example. So right after someone signs up. You could ask them, okay, now that you can use this product, what's the first thing that you are going to do? Or what was happening that led you to sign up?
And you can do the same with simple website falls on pricing pages, for example. And ask people, what brings you to the page today? Or do you have any questions that haven't been answered on the page? Or you can do it on exit intent.
So all these different little moments you can start collecting that information that once put together can actually give you a lot of insight into. How to personalize and customize the master for that specific moment. Cool. Alright, well thank you for answering that.
'cause I was a little curious about how you timed that. I wanna talk a little bit more about what you said about the role of research in driving conversions. Kind of like the research portion of being really effective at marketing a product. Can you walk us through what does foundational research look like for product teams in like more of a selling and buyer decision making context?
Yeah. The first kind of underlying principle, I would say we should start with the problem rather than the feature list. Again, as I mentioned earlier, first understanding, okay, these are the problem, this is the situation, the decision making process, but why? Why is this happening?
Asking deeper, more probing questions and also a lot of times from what I'm seeing, product people are focused a lot on quantitative research, which I know final analytics, heat maps, session recordings, which is great and I use it a lot for messaging, but I will also focus a lot on qualitative research, as I mentioned. So interviewing customers, looking at sales and support chat transcripts. Or I don't know, interviews with people who churned review mining, so all things that I do for messaging, but I think they can be super valuable for product people as well, because they give you insight on why people do something and also what kind language they use.
And you can actually use that inside the product as well for your UX microcopy. That's probably a good piece to start from, but also I like to look at research in three layers, which is kind of a system that I think once established, implemented, can kinda run continuously, and it can be super valuable to keep in touch with your audience and kind of understand how you think in sequence. So the first layer is kind of the more surface layer, so understanding what people say. To me, that's all voice of customer data.
So again, reviews or if you already have sales call recordings, support chats, all of that. Second layer is more of the structural layer, so understanding what people do on the website, which user heat maps, user recordings, product analytics. Then the final is the qualitative. So I would start with the voice of customer, which is the easiest to collect because you already have it inside the company.
Then start tracking those, that behavioral data, and then do the qualitative data with this kind of sequence. Doing the best that you can at every stage kind of keeps you in touch with your customers and it's a good way to supplement your product research that you're already doing, I think. Yeah, that makes a lot of sense. So let's get into storytelling time because I feel like a lot of this stuff we're talking about stuff more in a theory context.
It's kind of helpful to sort of put this into perspective using like a specific example. So have you worked with a client for example, where helping them understand their buyer psychology really changed how they position their product or feature? Tell me a little bit about like, how this has kind of come to life. Yeah, so I actually have a couple example, but I want to make a product led growth example just because product people might be a bit useful, more useful than a sales led one.
And so when I work with the Moz SEO on their Moz Pro product positioning and messaging and most API products, so both products. So the company got acquired a while ago and so it got a bit lost. They were kind of considered one of the more established SEO players in the industry, but still they were getting a bit more, more of like, antiquated perception from the audience. And so when I jumped in.
My goal was to kind of understand, okay, in this current situation of the market, how should Moz position themselves for these two specific products and for the audience that were kind of using them, their buyers. And so when we jump in, we conducted positioning, workshop, messaging framework. We wrote the copy for the pages of the two products, and there were two things, one thing per product that we actually understood that wasn't being reflected. Which was the first one for Moz Pro.
They were messaging it as the all-in-one SEO platform, which is what a lot of these mega platforms do typically. And so everyone was biting the saying the same thing, right? What we found by speaking with customers, which would also a thing that changed a lot for them just because they haven't done some interviews in the recent past as well. So we wanna refresh that insight.
Speaking with people, we realized, okay, the best buyers actually use Moz Pro because they want to simplify their SEO. They want to make it simpler. They are not ICO experts or massive agencies. It's mostly in-house people who, when they open up their Moz Pro dashboard, they realize that, wow, this is super easy to use.
I can actually understand what my next step are in the workflow. Versus another platforms maybe, I don't know, like compared to Ahref. So we just got a hundred thousand features and you can do literally anything. It's super technical.
So that was a very good understanding in the sense that, okay, we don't need to sell everything here. We need to sell the simplicity of Moz and what it does for people. And so that was one with the API. Again, similar process.
We started speaking with their customer, which in this case were a lot about enterprise as well. But at the same time they didn't really care about specific use cases of the API, what they wanted the most from Moz API, just because of all the history the Moz had behind the shoulders. Was the trusted data that the API was using. So again, we position Moz API product around the trusted Moz data.
And so that's why on the page, if you look at it now, you'll see it's positioned around trusted data. You'll see a secondary link that leads to their. API specific data page. So all the journey is customized to kind of promote that specific positioning and messaging.
I think these are good examples of, okay, you, maybe you have an assumption because maybe the company has been moving forward in the past years, almost automatically on autopilot, but it doesn't mean that it's the right assumption. So go back to the drawing board, speak to people and kind of understand what are their deeper needs, what are the things that they resonate on. A lot of times some product people might already kind of intuitively know them because when I speak to product people, they kind of know them, but then they don't communicate it to marketing.
So there's this all misalignment that if everybody at the company was aligned, they, the message would reflect that on the website as well. I have to say I'm, I particularly appreciate the first example that you gave about like just modifying the feel of the language from like being almost overwhelming, like it does everything, you know, every feature under the sun to like it simplifies because that's, I think, a huge psychological shift. I feel like this is a huge sin that I see all the time on product homepage and that kind of thing where they just kind of.
Blast you with features that are kind of vaguely described and a lot of jargon about, you know. Especially now with AI. Yeah, of course. Like, you know, it's just like you see a lot of the same buzzwords that I feel like at this point have kind of lost meaning, which I think, okay.
This kind of segues well into the next thing I wanna ask about, which is actually like user behavior having shifted with AI tools. So, you know, ChatGPT, it's obviously changing how people search for things, how the people evaluate things. But I also feel like it's also creating a little bit of friction in terms of what words carry any weight anymore when a buyer sees it on a webpage. For example, like when I see the word optimize, I kind of shut down.
'cause I'm like, of course. You know? So how would you say that, you know, in broad stroke. What are some of the major trends that you've seen in terms of the changes to buyer psychology that product teams need to be adapting to right now?
Yeah, so it's an interesting one because the first one, I think it's kind of, I don't want say a bias, but a mental shortcut in a way, which is that if you think about when people go on ChatGPT and search for it, or even just use it for their own work. A lot of times people value the convenience of using ChatGPT for search or for work more than the actual quality of the response. And so in that case, you have to be good enough with your messaging, with your marketing. Putting your messaging and positioning out there strongly enough so that ChatGPT grabs your message and then spreads the word in a way to people using ChatGPT strongly enough and differentiated enough so that people can actually understand.
Just because people are basically shutting down their brains and they basically trust everything that ChatGPT promotes them, right? So that's one. And the other one is, as I was saying at the beginning, you should think of people having this conversation inside their heads about their product. Now people are having a conversation with ChatGPT even before they'll end on your website.
And so you basically need to understand that conversation as well. So it's kind of, it's more complex decision making process gets even more complex. There's a couple of ways, both on the SEO or AEO, AGO, I dunno what they're called now, the different terms, but also on the marketing messaging research side of things. Like for example, one simple thing.
Even just using testing, different AI reasoning models and looking at their reasoning process, you start seeing, okay, what is the LLM asking itself and where is it going to search? And you can also extract the questions that it's asking itself in this reasoning process. So that's super helpful for kind of stepping into that conversation that people might have with AI. Yeah.
The other one is. That you basically have to also write for another audience rather than your SAP, which is the agent audience. Yeah. Which is a lot of people, especially for testing product, might start using agents as well that go through your website.
You go through your app and test it, and so in a way you have to make sure that your messaging and your design, your experience also work for these kinds of agents. So definitely an interesting times to be alive and play things. Yeah, I use that exact phrase all the time. So it's an amazing time to be alive, isn't it?
Okay. So let's talk a little bit more about agent experience, because this is, like, this is a whole new discipline area of expertise that, I mean, like, no one can really claim themselves to be a thorough expert because this it's not really a firm science that's, and it's changing so constantly, but as far as you know, best practices. At this moment in time, in this week of September of 2025. What have you seen as far as, you know, shifts that kind of seem to make a positive impact around agent experience?
Yeah, so the first one, it's try to make your, at least for the messaging side or usability, to make everything as clear as possible and readable by machines in a way as well. So all the meta content, make sure that it's in order, but also. Balancing those features and benefits properly in a way that you provide the facts and that the fluff is completely removed. And so in a way that's always been good copywriting practice, right?
So at least now that now it's forcing us to do it better. Just because these machines are faster than us going through websites, they don't need to spend a lot of time to kind of extract the data they need. And the other one is, I'm starting to think of messaging more as kind of infrastructure as something that you kind of install in a company and needs to basically flow. Through different channels, through different assets.
And so it's important to be even more consistent with your message across all your channels. Product marketing, side, shades, collateral, anything. Just because once these agents start circulating and navigating around, as soon as they start seeing some disconnect in your messaging, then they're probably gonna go to a competitor who's doing it better and using that as the main source. Consistency.
Super important, I think. And also the other one, which has always been something that I talked about, it's the UX of copy or the hi the messaging hierarchy on your website. So making sure that you have the right pages for the right ICPs on your website that. The navigation flows well, and that's all.
Again, going back to that structural research, the looking at user recordings, eat maps, understanding how people use your website or navigate through website or use your product. That's all super valuable to kind of understand as well how these agents work. And the other one is probably something even more fundamental, I think, which is your positioning. So the stronger your positioning is and your specific point of view, the better I think.
The higher chances you have to stand out and to make sure that these agents actually get the gist of what you do in the right way for the right people. And so having a strong point of view what's that insight that only you have on the market, on your customers, on the competition that actually made you build your product? Right? So yeah, I would say these are the main things that I'm thinking about.
I'm very curious about this because I foresee at this point all these predictions. Who can say, but I kind of see this trend of, especially in B2B agents being the primary decision maker, or at least the primary kind of filter for, you know, what are the decisions that a business needs to make in terms of tooling, in terms of solutions, in terms of services. Because they can just evaluate the information with a lot more objectivity and a lot faster. But I still think that there is a place for.
Making a, let's say, a more emotional connection with a buyer, with a consumer, and especially with B2C. You know, like when you're talking to a B2B client, you're trying to get them the solution that they want at the price that they want, with the features that they need. And a lot of that is negotiable. When you're talking about B2C, you're talking about a product that you want people to kind of integrate into their life, and there has to be a certain way to build affinity with the buyer.
So how do you kind of balance. Kinda what you're describing this agent experience, which is really focused on delivering things in a way that's easily processed by machines and easily understood versus kind of like this liminal space where there's like that fluff that you described is also kind of the place where we sort of establish a personality in a POV. How do you kind of balance those things out and kind of determine what's like the percentage of experience versus human connection that you wanna integrate.
To me, I think it's always been about understanding where you fit in like how new or establish your solution is your category and your market. Once you understand, okay, my solution is a new solution in established market, or I'm an established solution in an established market, established solution, new market, whatever the combination is. Then you can basically and it's the exact thing that I do in my messaging framework. I have a literally a table that based on where you fit, whether you are established solution in a new market.
Or vice versa. It gives you the percentages of benefits versus the features versus the differentiators that you should use in your copy, and that's basically how I balance it. I have literally three sections and in one sections, for example, if you are kind of a new solution or established market, then you have to explain the benefits. What's the benefit?
'cause the feature maybe already established differentiator of maybe you don't have allowed. If you are established solution and established market, then you have to be heavier on the differentiators, secondary benefits, and then features. So I think it's finding out where you're at in terms of solution, category and market maturity. Then figuring out how to split those three main copy elements.
I love a scientific approach to copywriting. This is. I'm a former engineer. I had to turn it into system.
You are probably one of the few people in your craft who is like really coming at this as such a data-driven way. Like a lot of copywriters I know are just like, what speaks to my heart? Yes. Creative.
Such a cool POV. So anyway, since I already broke the seal as far as looking at predictions and that kind of thing. Without putting too much stock in it because we, who knows what's gonna happen in two months. What would you say is like a piece of advice that you'd give to folks about staying ahead of psychological and behavioral changes as far as what you're kind of seeing trends wise and predictably when it comes to shifts in AI and agent use?
I would say rather than chasing trends, I would say go back to your market territory your ICP, like it's the most fundamental tip, but especially now with AI and the speed at which we can collect information and also analyze information. It's what I was saying before. If you install a kind of a research system and I call it research optimization system, those three layers that I talked about. If you make it a consistent practice inside the organization, run it consistently and co consistently collect fresh data, like being in touch with your audience is actually what dictates everything else, I think.
And so, okay. It's important to, to look at the trends, but again, I would still anchor everything into the knowledge of the ICP. Yeah, I guess so. And I really like this takeaway of we are writing for a different ICP now, like we have to start thinking about agents as an audience and not just as a tool.
Which is like a huge paradigm shift in terms of how we think about reaching people, but I feel like that's such a huge golden nugget for this conversation. And speaking of this conversation, thank you so much for sharing these insights. This is like such a cool thing to dissect in this way. We've talked a little bit about a lot of marketing strategy related topics before, but this is, I feel like the first time we've really looked at things from a really data first perspective.
So, where can people hear more about this? Where can people find you online, Chris? Yeah. Thank you so much, Hannah.
It's been super awesome and I feel like I hated a bit on too much on product people, but hopefully not because I love product people and I also like from my UX experience and watching hundreds of usability tests, I feel their pain. So I always try to help them. But yeah, people can find me at conversionalchemy.net to my website where I have a newsletter.
Or mostly on LinkedIn. I'm there chatting, posting about everything that I learned, and so yeah, feel free to connect. Sounds great. Well, thank you so much for making the time.
Thank you.
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