Lesson 17: Customer Discovery Process & AI Findings Detail

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Another chilly one out here today. Let's get up here and chill out. All right.

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Welcome back. It's a Saturday morning here and another spectacular morning. A little chilly, but going to be a little warmer this afternoon.

So yeah, let's get into it. Today we're talking about customer development, going to define what that means and how to use that to obtain and extract information from the market that actually matters. The nuance that will help you iterate faster on your product or service, connect with the market and drive revenue, profits, et cetera.

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It's a classic, classic methodology, talking to people who to thunk instead of just blindly posting things on the internet and just hoping for the best. All right. So customer development, what is it? Well, you talk to people, so there's places where you can go and you can pay money to talk to experts in a field and you can spend 30 minutes, an hour, a couple hours, and you can just have a normal conversation with them and you can record it and you can go back and look at it later.

And, um, that's one way to do it. The other way to do it is to survey, like your friends, but, um, or strangers on the street or set up a survey. But there are some methodologies that, uh, are important to ensure you're getting the right information out.

So what this not is, this is not a sales process. If you bring up the thing that you're doing at all, you've already failed. There's no sales here.

This is understanding. It's listening. It's asking deep questions.

It's asking expansive questions. It's asking for facts, for opinions, for principles. So examples of this would be like, you know, tell me about this thing that you know, like, what are your thoughts on this? How do you feel about the way that this thing works versus that one? And like, why would you choose this one, uh, over the other one? Right.

Or, um, you know, like, does this feel expensive to you? Does this feel inexpensive to you? How do you then perceive that? Or like when this brand or this creator said this thing, like, how did that make you feel? And then did it make you go buy this thing more or less? And so do you think that this is actually a viable or interesting path? Does this solve any actual problems in your day-to-day life? You can ask these and then you just shut up and you just listen to what they have to say. And then you follow the thread and you just ask them follow up questions. It's not just a list of questions.

It's being generally interested in them and what they have to say. And if you do enough of these, like we've talked about in prior videos, 30 at least, um, along one dimension, you will very quickly understand exactly what's happening in the minds of your customer base or the general market. And obviously those things can shift and change over time.

But what you're really looking for is core, deep foundational, fundamental principles, values, uh, thought patterns, decision-making capabilities. And from that, you can figure out things like key purchase criteria, willingness to pay features, benefits, etc. And even so much as like, what's your favorite brand? Like what thing will you buy the most of from this person, company, organization, whatever, and you just can't get enough.

And the real question is like, why? Like what drove you to that? That's where the really interesting insights come. So let's talk about a couple examples here. I'll give you a few real world things.

So we do a lot of work in the space of technology, artificial intelligence, product, brand experiences, we design for large consumer companies to activate their customer base and get some technical term, brand affinity, awareness, retention, purchase conversions, yada, yada. And one of the things in the AI space that everyone sort of agrees on is like, which also presents a problem and a fear is, um, workflow automation. Basically, like, can I have a machine or some software take this manual task and do it for me, like more often, better, faster, so I don't have to do those steps over and over again.

And that's where a lot of the fear of this, um, is AI going to take my job. And I think you do need to get a backup plan if your job is simply taking this thing and putting it there or doing that thing and then doing this. And you do that a hundred times a day, a thousand times a month, that same thing over and over again.

That is the lowest hanging fruit that a lot of companies are focused on, especially if it's core to the process of them generating revenue or profit. And so if you're not using any sort of like variability, your mind decision, if there's not a lot of like weird nuance and like, think of it like a, like a lot of winding pathways and forks in the road that you have to navigate that takes a lot of time to develop that capability set, then you are more ripe to be disrupted by automation from a machine. It's just, it just makes sense.

So your goal, if you're in one of those places should be to add more value on the outside of that core process or above, or like work on the way to automate that and then work on ways to automate other things and like develop more sense of value, create more value for the companies that you work with or the organizations or yourself. Um, but back to the original requirements. So where we see a lot of this happening is in organizations where it's very close to collecting revenue, like getting that payment to getting that payment inside your company to the, to the seller, whatever, if you're a marketplace, uh, collecting that, if it's a lot of transactions that lead up to that, where it's like you have a thousand activities, right? A thousand things you do every single day.

And it's typically a standard process. There's some variability. You're doing it over and over and over and over and over and over again.

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That is a place where AI is being applied right now. Uh, and then that's creating a lot of competition. So it's very quickly become table stakes.

Emerging tech has become table stakes for competing in the market, because if you don't do this, that means a company that has automated this and a company that hasn't the one who has means you're now doing twice, three times as many, the volume at a higher accuracy rate at a lower price that you can pass on to customers, which means the one who doesn't do it makes it obsolete. That mechanic by itself is why AI is not a bubble because it's forcing existential risk and change to every business process that's starting very close to revenue or profit creation. And from there, once you get that going, you'll learn and it will expand across the organization.

Um, and so those are the areas that right now, as we sit at the beginning of 2026 are having heavy activity and a lot of investment by a lot of companies. We see this in high growth startups. We see it in lower mid market, mid market and sort of upper market, private equity companies and portfolio companies and funds.

We see this in public companies. We're actively advising, strategizing, building these things. So, um, this talk is to do two, three things.

One, present the real truth of what's happening in the market. Okay, so you can determine what to do with that early before it impacts you in a negative way. That's part of our core values.

We want to help things, help people, right? So that's companies, that's consumers, etc. Right? The planet, this, we've got to protect. Um, that's the first.

Two, you don't have to be afraid if you can figure out a way to provide more value in and around that or you shift. So that's protection mechanism. Three, as a company, or as an investor, or as a user, or as a consumer, or as a media personality, AI is not a bubble.

Companies, individuals are paying money for this hard money. And they're finding real value in this every day. That's not a bubble.

Okay, so that's, believe that, trust that. We see that. We understand that.

Please, if you hear nothing else, hear this. This is actually creating value every day for many folks. Okay.

And then the third piece is, where is all the activity? Where you can feel confident that you're not going to go into a space, waste a bunch of time, money, effort, resource, and get nothing out the other end. So that key place, which is a lot of the similar activity happening over and over and over again, that's as close as possible to the money. That's where it started.

And so if you have one of those, now all of a sudden you can use your noggin and you can go, all right, my thing is doing this. That's probably a good place to think about AI, either as an employee, as a manager, as an executive, as an investor, as just somebody who's writing about the space. Okay.

So that's some detail in and around these things. And so then if you're creating a product or service, you can step outside of that, these learnings, these lessons you have from customer development, from operating in these spaces, and you can say, how do I create a platform to make that easier for other people? So a lot of this you see for the AI space, like AI agent platforms to automate this stuff. So these companies are doing that.

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On the other side, though, it's the question of what are we going to do about our consumers? Where they may have had part of their compensation automated away or part of their job automated away. What are we doing for them? So there's another side that has the opportunity to create a platform to help upskill, enable, get them thinking differently, and basically help them evolve while the technology, the companies, the corporations, the investments are evolving as well. So everything needs to evolve simultaneously.

And that's the work. That's what we have to do every day. So don't be afraid.

It's going to be okay. It's not going to kill us. It's going to help us.

But we're going to go through this period, this transition period. And so the folks that get on the bus and start transitioning earlier, you develop expertise, that expertise is valuable. There's millions of companies around the world, 100 million.

There's 30,000 enterprise SaaS companies. That's just in software, selling software to companies. That's a teeny tiny little fraction.

So get in there early, get some knowledge, get some experience, get some skills, and then take that out to other folks and help them along the way as well. And you'll be fine. And you'll develop a community around it.

So that's it. Have a good weekend. Have a great day.

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And go wide, but also go deep. We don't want to be just singular shaped, like T-shaped, or like have broad expertise and deep expertise in one area. We want to be tic-tac-toe shaped.

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We're broad at layer one, layer three, layer seven. We go deep in column three, 17, 29. And the more of those tic-tac-toe squares you can fill up, the better off you'll be.

So go out there, get that skill set, and let's make a positive five. Catch the wave. All right, guys.

Have a good one.