Startups with no customers face different challenges than startups with customers. So founders need different ways of seeing the world, depending on the state of their startup. For founders of startups with paying customers, it makes sense to call their audience “customers”. By definition, the term, “customers” is inherently wrong for startups with no customers. So how should those founders talk about their audience?

Anyone who has ever been a customer of anything ever, started as a Person in Pain™.

Customers are downstream. Startups only have customers after they have a product and someone has paid for it. Founders with just an idea need to focus upstream, earlier in the process. They need a signal about who could become their startup’s first customers, and that signal comes from People in Pain.

I’ve gotten pushback that terms like “potential customers” and “prospects” are sufficient to describe this upstream audience, but I disagree.

In my experience, founders who start by saying “potential customers” often drop the word “potential,” which leads to the exact problem we’re trying to avoid.

As for “prospects” — these are people who, by definition, have already shown some indication that they might become customers. For instance, imagine a pod of food carts. Somebody who walks into the pod is a prospect. Just the fact that they walked in stands in contrast to everyone else out on the street who walks by.

Prospects are great, but they’re still too downstream for a founder with just an idea. With Nascent, I’m trying to take a step back and look at the people on the street walking by a business. How can we identify which of them might walk in and become a prospect, as opposed to everyone else who never would?

When all we have is an idea about a problem to solve, it’s crucial to identify who might care about that problem. That’s who we’re talking about when we say People in Pain.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is the first of three deep dives 📬 from Episode 033 🎧: Yes, talking about “customers” harms most founders. Instead, identify “bank accounts” of Pain. The next deep dive covers how to find People in Pain among everyone else who’s in your way. The last post covers how much Pain is in their bank account.

I hate it when a founder says: “I talked to customers about my startup idea.” That sentence is so commonplace and so contradictory.

If your startup is just an idea, then how can it also have customers? When I push back that they’re talking about customers their startup doesn’t actually have, the founder often responds with something like “Oh, come on, you know what I mean.”

For decades, founders have been encouraged to “fake it till you make it” and talk about customers, whether they have them or not. Entrepreneurs need to stop talking about customers they don’t have. A startup is a project that’s fundamentally about creating new knowledge, whereas untruth is the antithesis of knowledge. By saying that your startup has something that it doesn’t, you’re corrupting your knowledge-creation project.

Sloppy language leads to sloppy thinking, and this has consequences. The most common outcome for a startup is that the founder wastes a year pursuing an idea before deciding that it won’t get customers. One factor driving this unfortunate result is the loose definition of the word “customer”.

For founders with just an idea, there is better language, that leads to better thinking, that ultimately drives better outcomes. Here’s Nascent’s strategy to address this challenge.

First, founders with just an idea need an accurate name for their audience. Who is a customer before they’re a customer, or even a prospect? They are a Person in Pain™. Anyone who has ever been a customer of anything ever began as a Person in Pain. Even prospects are too downstream. Instead, founders need to look further upstream for the first sign of a person that could become a customer. That sign comes from a person with emotional pain.

Second, People in Pain sit inside a funnel. As a founder, you want to solve a problem with your startup and you need to identify who that problem applies to. To that end, Nascent’s People-to-Prospect Funnel™ (detailed in Episode 025) maps the journey of everyone in the world down to your startup’s first customers, i.e., the few people who have that problem and pay you for a solution.

The funnel starts with all of the eight billion people in the world. Inherently, almost none of these people care about the problem that the startup wants to solve, so these people are Blockers. They’re in the way. Below them are Distractions who don’t have the problem, but tell the founder to build the solution anyway. Then there are People in Pain — the first people that resonate with the problem. And then Prospects and finally Customers. The bottom of the funnel is visible: you can identify customers and prospects by their actions. The top three layers are hidden — founders can’t easily distinguish between Blockers, Distractions and People in Pain.

Third, imagine people with bank accounts of Pain. In Episode 032, we discussed how to go from a person’s emotions to dollars ($) of Pain. To extend that framework, you can say that a Person in Pain holds an account in the currency of your startup’s problem. The status of that bank account can be positive (they have meaningful pain) or empty (they’ve experienced the problem, but they’re indifferent) or even negative (what you believe is a problem, they actually consider a pleasure). These People in Pain with “bank accounts” sit in contrast to Blockers and Distractions who have no bank accounts at all.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep033 🎧 and three deep dives 📬 follow it: why every customer begins as a Person in Pain, how to find People in Pain among the eight billion people in your way, and how much Pain is in their bank account. For the full version, check out the podcast on Spotify / Apple Podcasts / YouTube.

Nascent enables founders to generate a value for a startup idea by analyzing customer discovery interviews using a 3-step process that delivers a dollar-based metric. Specifically, Nascent has founders run each recorded conversation through these steps:

1. Characterize interviewee’s emotions as hurting, fine or joyous using the Yardstick of Pain™, as detailed in Episode 027 and Episode 028.

2. Convert emotions to a dollar-based signal. We use behavioral economics and psychology to get an initial signal. (The focus of Episode 032.)

3. Measure effort in dollars — Go from the rough signal to a specific dollar-based measurement, as detailed in future posts.

In Episode 31, we discussed how every product is a Pain-relief device that helps People in Pain get closer to feeling fine. From that perspective the value of a product is determined by how a Person in Pain feels initially. Nascent uses an interviewee’s “origin” on the Yardstick to assign a dollar-value for their Pain:

• Hurting means the Person has $1 of Pain.

• Fine means the Person has $0 of Pain.

• Joyous means the Person has −$1 of Pain.

This assignment of dollars to feelings reflects the emotional journey of a Person in Pain going from origin (their current Pain) to destination (feeling fine).

A person with an origin at fine has $0 of Pain because they have nowhere to go. They’re already at the end of their journey. They have no need for Pain relief, no need for a product. In other words, how much might they pay your startup? Zero dollars.

Even worse is a person who feels joyous. This person needs to go backwards to get to fine. A product would provide them with negative Pain relief. It would take away their joy. So if you want them as customers for your startup, you’re going to have to pay them. How much might you have to pay them? Let’s simplify and call it −$1.

And then there are people who are hurting. Special people with meaningful Pain, who have the potential to go on the journey from hurting to fine. They might pay some amount of money to feel better. They present an opportunity for your startup to deliver Pain relief. Maybe that’s 10¢; maybe it’s $10M. At this point, let’s not worry about exactly how much they would pay and instead capture the positive signal. So we’re just going to simplify and call it $1 of Pain.

The benefit of this mapping is that it enables founders to make better decisions faster. By monetizing emotions, we can more clearly identify who’ll pay our startup and why. People with $1 of Pain might become customers, but People with $0 of Pain or −$1 of Pain are valuable counter examples of who will not become customers.

Founders today disregard and overlook interviewees who won’t become customers. I think that’s a huge waste — there’s tremendous utility in assigning null values and understanding why those values are null. As founders, we naturally focus on finding customers to pay our startup. Nascent takes a more holistic perspective: identifying people who will not become customers also allows us to create valuable knowledge and make progress in vetting our startup idea.

The most common outcome in entrepreneurship is that founders waste a year before recognizing that a startup idea will not meaningfully get customers. This dollar-based signal enables founders to be decisive in days about whether to invest more time. If a founder runs batches of discovery interviews and only finds People with $0 of Pain, then the Estimated Revenue Next Year (ERNY) for the startup is $0. The value of the startup idea is $0. By contrast, the more dollars of Pain a founder can identify, the higher the ERNY value and the more reason for the founder to keep investing time in the startup idea.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 032.3 📬, a deep dive into converting interviews into dollars discussed in Ep032 🎧 (18 mins). The deep dives are 032.1: why people who feel fine won’t buy and 032.2: what drives a purchase.

Only one thing matters for founders of startups with no customers: determining how their startup could get its first customers. Previously, we talked about how behavioral economics predicts who might become a customer. Now let’s leverage the field of psychology, specifically how drive reduction theory indicates who might take action and pay for a product.

The key is that feelings drive actions. Specifically, drive reduction theory explains that people with negative feelings, like hunger or thirst, experience a drive to take action and reduce their discomfort. This is why we eat food and drink water. Humans seek Pain relief.

The example of a thirsty person drinking is called a primary drive because it’s innate and reactive. It’s an immediate response to a really uncomfortable, visceral feeling.

But human beings aren’t purely reactive — we also think ahead. We tell ourselves stories about scenarios in the future, which generate emotions and also drive us to act. These secondary drives are acquired and predictive.

For example, yesterday you might’ve felt thirsty so you looked for water. That was a primary drive. Now today you have a secondary drive: anxiety. You’re projecting out a story that you might be thirsty again, and that fear of discomfort is what makes you carry a water bottle around with you all day.

What’s interesting about secondary drives is that they’re not only based on personal, direct experiences. We don’t just worry about repeating our own painful ordeals. Secondary drives can also come from indirect experiences — other people’s stories. If somebody tells us about an awful incident, that can also cause us negative feelings that drive our actions.

You are a founder searching for People in Pain™ who might become your startup’s first customers, so you want to look for specific primary and secondary drives. When you run discovery interviews and ask people about their previous experiences, you’re hoping to hear stories where their primary drives were activated. Where something awful happened to them.

Even better, you’re hoping that they now have a secondary drive that comes out of their first-hand direct experience. You’re hoping to find people who feel really anxious or worried or fearful about something awful happening to them again. These People map to hurting on the Yardstick of Pain. The more hurting People you find, the bigger your opportunity to create a business.

For example, if you’re a founder of a water bottle startup, you would love to find somebody who was dying of thirst yesterday and now is in a frantic panic to avoid that discomfort. That’s the kind of Person in Pain who might become a customer.

Understanding secondary drives also helps us understand what to avoid. Yes, we can try to tell stories and induce an indirect secondary drive in other people, but that is too much work. We don’t want to be storytellers trying to manufacture a secondary drive. Technically this is possible, but unlikely to lead to success. An awful go-to-market (GTM) strategy is to take people who are fine and try to convince them that they should be hurting. Instead, founders want to serve People who are already hurting, People with a secondary drive based on their direct experience with the problem you hope to solve. If you can find lots of these people, that’s your best indication that your startup might someday get customers.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 032.2 📬, a deep dive into drive reduction theory discussed in Ep032 🎧 (18 mins). The deep dives continue in 032.1: why people who feel fine won’t buy and 032.3: converting interviews into dollars.

As a founder of a startup with no customers, your most important task is to figure out what it would take for People in Pain™ to decide to pay and become customers. Behavioral economics explains this process, specifically through prospect theory, status quo bias and loss aversion.

Over the past few posts, I’ve mentioned the book Thinking, Fast and Slow by the Nobel laureate Daniel Kahneman because it explains so well how people make decisions under uncertainty.

Kahneman’s book includes a section on “prospect theory” that focuses on a “value function graph” that explains why people act differently in response to perceived gains and losses. Most importantly, Kahneman notes that “the response to losses is stronger than the response to corresponding gains.”

Entrepreneurs don’t need to be experts in prospect theory. Here’s what’s important: the value function enables us to predict whether People in Pain might become customers based on how they feel about the problem that our product will solve. Only people in the Loss region of the graph might become customers. For everyone else who is neutral or in the Gain region, the likelihood of them becoming customers is basically zero because loss aversion and status quo bias dominate.

Nascent’s Yardstick of Pain™ maps to the value function and lets founders easily leverage its predictive power. People who are doing fine, or even worse, people who feel joyous will not become customers because they experience status quo bias and loss aversion. They don’t perceive gains from the product to be valuable. Instead, they care more about not losing a good thing so they avoid new products. To quote Kahneman, for these fine and joyous people “the disadvantages of a change loom larger than its advantages, inducing a bias that favors the status quo.”

To be clear, yes, there are lots of problems in this world. However, despite all of these problems, most people, most of the time, feel fine. They’re not open to change. This is what “normal” looks like.

As a founder, you want to solve problems for people who are actually open to solutions. These People are hurting, they’re in the Loss region of the value function graph. Only these People might become customers. In an interview, they might say something like “I hate this problem. What do I have to lose? Anything’s better than this!” From the perspective of behavioral economics, only people that have a negative emotional resonance with the problem might be open to taking a gamble on getting Pain relief from your startup’s product.

Here’s how behavioral economics and the Yardstick enable founders to monetize customer discovery interviews:

• “Hurting” interviewees have some Pain, which we simplify as $1 of Pain. They might be open to paying for Pain relief.

• “Fine” interviewees have no Pain, which is $0. They’re not open to paying for Pain relief because they’re biased to maintain the status quo.

• “Joyous” interviewees have negative Pain, which is −$1. As much as your product can take them from feeling “great” to feeling “spectacular”, they’re more worried about losing a good thing. They’re risk averse and keen to avoid a potential loss so much that you’d need to pay them.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 032.1 📬, a deep dive into loss aversion discussed in Ep032 🎧 (18 mins). The deep dives continue in 032.2: what drives a purchase and 032.3: converting interviews into dollars.

A huge difference between early-stage startups and public companies is how easily we can value companies like Google, as opposed to how hard it is to identify a good startup idea, especially when the startup has no customers. My goal with Nascent is to bridge this gap and make startup ideas measurable in dollars.

Companies listed on a stock exchange publish their performance, which drives their valuations. Last year in 2025, Google said that they made $130B in profit at a 30% growth rate, which caused the stock market to value Google at a $4T market capitalization. By contrast, Spirit Airlines had a negative profit of $2B and the market valued them at just $50M. What I find most compelling about market cap valuations is that they’re based on first-hand data. These valuations tie back to real money that actual customers paid these companies.

As a founder of a startup with no customers, you’re probably hoping for a billion-dollar valuation someday — but how much is your startup idea worth right now?

The only metric I’ve seen come out of discovery interviews is a count, as in a founder saying that they “interviewed 100 people”. Counts are action-based metrics that say nothing about accomplishment. Just because you walked 100 steps doesn’t mean that you’re any closer to your destination; you could’ve just walked in a circle.

What founders desperately need, but have never had, is a way to value a startup idea in dollars. Founders need a way to distinguish 10¢ ideas from $10M ideas. The perspective of Nascent is that (1) every product is a Pain-relief device and therefore (2) the value of the startup idea is determined by the People in Pain that the founder interviews.

The good news is that we can extract a dollar-based signal from those discovery interviews. Specifically, we can leverage behavioral economics and psychology because of how they map to the emotional journey of a Person in Pain™ along the Yardstick of Pain™. Nascent assigns values based on how a Person feels about the problem the startup intends to solve:

• $1 of Pain to someone who is hurting, meaning they have some Pain.

• $0 of Pain to someone who is fine, meaning they have no Pain.

• −$1 of Pain to someone joyous, meaning they have negative Pain — the opposite of a problem to solve.

The point of these dollar amounts is to provide an initial signal with directionality, not a precise measurement. What matters is that someone with at least $1 of Pain might pay for Pain relief. Maybe 1¢ or maybe $1,000 — later we’ll refine the estimate, but to start we’ll just use $1 to show they’d consider Pain relief. By contrast, a person with $0 of Pain has no Pain so they won’t pay for Pain relief. Even worse is someone with −$1 of Pain — a founder would have to pay them to use the product.

Over the coming posts, I’ll expand on the big ideas in this episode: why people who feel fine will not become customers, whereas only people who are hurting might pay and the details of converting customer discovery interviews into dollars. This initial signal is a crucial step towards calculating a value for a startup idea: the Estimated Revenue Next Year (ERNY) from the ground up with no customers today, only using discovery interviews.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep032. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

Yes, the opportunity for your startup’s success is based in other People’s Pain. Identifying People in Pain™ is the first and most important step to creating a viable startup so the more hurting people you find, the bigger the opportunity for your startup.

To do this, founders run discovery interviews. Most importantly, the interviewee needs to discuss their emotional state the last time they faced the problem you want to solve. Nascent has a tool called the Yardstick of Pain™ that founders use to analyze the raw transcript from an interview. Specifically, founders categorize an interviewee’s emotions as either hurting, fine or joyous. This is how they felt about the problem previously and how they expect to feel when they encounter the problem again. It’s both historical and predictive.

The Yardstick also shows how a product is a Pain-relief device, like an arrow that moves a Person in Pain along the Yardstick. The origin of the arrow is their current Pain — the experience they described in the interview.

So your goal as a founder is to run discovery interviews and you’re hoping to find an opportunity to deliver Pain relief. Through this lens, the Yardstick of Pain lets you identify which interviewees present an opportunity.

People who are joyous have nowhere to go. They will never be customers.

Technically, if someone is fine, you can try to get them to joyous, but that’s extremely hard. My favorite example of this is the movie Gladiator where Russell Crowe is in a battle at the Colosseum. After he slays the other fighters he shouts “Are you not entertained?!” And that’s the thing — getting people to feel “entertained,” to move from fine to joyous is incredibly difficult. By comparison, it’s easier, not easy, but easier to take people who are hurting and move them closer to feeling fine.

The best problems for your startup to solve belong to accessible, empowered People who have frequent, expensive, excruciating Pain. A good example of somebody who is accessible is a little kid. You can walk around town, bump into one and ask, “Hey, do you want some ice cream?” Of course the answer is yes but the problem is that a child has no power — they would have to get money from their parents. By contrast, billionaires have all the power in the world. They could buy ice cream or anything else they want. But they’re not accessible. Most people in the world will never speak with a billionaire.

So, as a founder, you’re searching for special people who are both empowered to spend money and accessible to you. And if you can find these rare, special people then you want to see if they have frequent, expensive, excruciating Pain. The problem has to happen to these People often — hopefully in the last few days or weeks. It needs to be really costly. And it has to have that emotional resonance, which we categorize as hurting on the Yardstick of Pain.

The more people you can find with these unique traits, the more reason you have to invest time in your startup. And if all the people you speak with are fine or joyous, then that’s also a useful signal it’s probably not worth investing a lot more time in this specific startup idea.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 031.3 📬, a deep dive into the concept that other people’s pain is your opportunity, discussed in Ep031 🎧 (15 mins). Read the rest of the deep dives: 031.1: products imply hidden pain and 031.2: money is a metric for pain.

What is money and why do humans decide to spend it? Money is fundamental to a successful startup, yet I’ve mentored many founders without a meaningful point of view.

For instance, last year I ran a series of workshops where I asked the workshop participants, “As a consumer, what does money mean to you? What does a dollar in your pocket mean to you?” Here are some of their answers:

• “I don’t know. I can’t quite put my finger on it.” This type of response was pretty common.

• “I’m purchasing something that I feel will bring value to my life.” This is true, but not actionable.

• “[Money is] a tool — instead of hungry, I get full; instead of cold, I feel warm.” This describes an emotional transformation, a critical unlock that startups require.

Overall, most workshop participants didn’t have specific, thoughtful opinions about money, despite hoping that their startups would make lots of it. Even when I studied business at Berkeley, we never really got into the essence of money. I think it’s crucial for founders to have a strong, thoughtful point of view.

As a benchmark, Wikipedia defines money as “payment for goods and services,” which is true but useless to entrepreneurs. It’s like saying that “planes fly because they stay in the air.” We need to understand why this happens. Just like pilots need to understand lift, founders need to understand the equivalent force in business, which I believe is based in money and Pain.

To that end, Nascent actually has two definitions for money:

• Money is a metric for Pain, and

• Money is liquid Pain relief

Not all problems are equal. In fact, most problems are worth pennies but there are rare, special problems that are worth millions or billions of dollars. Nascent is all about prioritization. I want you to be clear about what a good problem looks like. You want to solve expensive problems.

What I mean by “liquid” is that money is easily exchanged as opposed to a gold bar or real estate.

Essentially, I want you to think about Pain as a potential that a product can release, similar to the build-up of water behind a dam. The more, the better. Our goal is to transform that potential energy into something useful. The dam allows water to flow, creating kinetic energy. This is similar to how a product relieves Pain. More importantly, the dam also generates electricity. Similarly, a product delivering Pain relief outputs cash money.

The big idea is that people have Pain and they want their Pain to be relieved. Most of the time, they can do it themselves. Occasionally, something special happens, and people can’t relieve their own Pain. That’s when there’s this huge build-up of Pain that’s just dying to get released. So the other option for Pain relief comes from buying a product. In other words, People in Pain™ pay money for the Pain relief they expect a product to deliver.

If you want to think deeply about money, I highly recommend the writings of Lars Doucet. Most importantly, understanding the relationship between products, money and Pain will give you a better chance at identifying People in Pain with the potential to be the first customers for your startup.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 031.2 📬, a deep dive into the concept that money is a metric for pain discussed in Ep031 🎧 (15 mins). Read the rest of the deep dives: 031.1: products imply hidden pain and 031.3: other people’s pain is your opportunity.

The perspective of Nascent is that the essence of business is transforming a Person in Pain™ into a paying customer. This is true for businesses that make products that you’re already familiar with and for the products you hope to create with your startup. Understanding this concept enables founders to distinguish between people who will never become customers and others who just might.

For instance, you might see someone hiking in the woods and think to yourself, “yeah, they look fine”. You’re probably correct — but they were not always fine. Before the journey, the hiker was scared of getting lost in the woods and worried about the burden of lugging gear by hand. These negative emotions drove the hiker’s actions: they bought a compass and a backpack to get Pain relief. The compass relieved their fear of getting lost. The backpack relieved their burden of carrying equipment. Those products are Pain-relief devices, which is why, in the end, the hiker feels fine.

How can we tell that they went from feeling scared and worried to being ok? The compass and backpack are visible clues. But we’re not mind readers. So, most importantly, we have a conversation and they tell us in their own words how they felt before the hike and then after buying products.

Their journey of using products had a beginning, middle and end. At first, the hiker was a Person in Pain who was hurting. Then they bought products to get Pain relief. The compass. The backpack. Whatever else they needed for the hike. And that’s why now they’re doing fine.

As entrepreneurs, we want to deeply understand this transformation. What matters is that the Person in Pain paid for the product to take them along that journey. Without that initial condition of hurting, the Person in Pain does not buy a product.

Our challenge is that it’s easy to envision money and products, but it’s difficult to articulate the hidden Pain that those products imply. As you navigate the world, I encourage you to try to say aloud the Pain implied by the products around you. Right now you’re probably somewhere with a door nearby. 🚪 You could look at the door and say it implies a fear of revealing sensitive information, of not wanting to be overheard. You might also say that the door implies a worry about disturbing others with loud noises.

I’d love for you to try to develop this skill of articulating the relationship between products and Pain. Look at two or three objects in your life and try to articulate the Pain that they imply. After you’ve done that for some existing products, repeat it with your startup idea. What are the fundamental Pains that you want your startup to solve? Let me know what you find. I’d love to hear about it.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 031.1 📬, a deep dive into the concept of hidden pain discussed in Ep031 🎧 (15 mins). The deep dives continue in 031.2: money is a metric for pain and 031.3: other people’s pain is your opportunity.

Founders want customers, but ironically, the best way to get customers is by seeing the world in reverse. What kind of people are customers before they buy? Why do people pay money in the first place? Answering these questions will help you avoid the most common problem in startups: wasting a year on a bad startup idea.

The whole reason that a Person in Pain™ might become your customer is for your product to take them on an emotional journey with a beginning, middle and end. First, a person starts with meaningful Pain — they’re “hurting”. This motivates them to pay money for a product to feel better.

The perspective of Nascent is that humans make decisions in a 3-part system: a Person in Pain who is hurting decides to pay money for a product to get Pain relief. Most importantly, money and products are visible, but Pain is invisible. This means that we can only see the end of the journey, not the beginning. For instance, a customer at a shop might pay a dollar (the middle of the journey) to buy ibuprofen (the product) to relieve a headache (the end of the journey). We can see the money and the packet of ibuprofen. But we cannot see the headache — the Pain at the beginning of their journey. The Pain is invisible. This perspective on Pain applies to every product within the built world, including the products you hope to make with your startup.

Here’s the journey of a Person in Pain becoming a customer. It starts with a person who is hurting. Then they buy a product for Pain relief so they’ll feel fine.

Looking at this journey in reverse reveals who will not become a customer for your startup. People who are already fine will not buy your product — they’re already at the end of the journey. People who are joyous are even worse — they’d ask you to pay them. Only People who are hurting might become customers.

As a founder of a startup with no customers, your most important task is searching for people who are hurting. The more hurting People you find, the bigger your opportunity.

Over the coming posts, I’ll expand on the big ideas in this episode: why products imply hidden Pain, Nascent’s two definitions of money, and Pain as a signal of opportunity.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep031. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

You may have noticed something different lately with the Nascent podcast and newsletters. Here are the details.

I first published the Nascent newsletter in January 2024 followed by my first podcast in February 2024, as part of an effort to build in public. Throughout 2024 and 2025, I published only 18 times because I focused on running workshops instead. These workshops showed me that some (but not all) founders of startups with no customers are “hurting” and a dedicated strategic playbook could provide “pain relief”. My challenge was that I kept having one-off conversations about this, which felt frustrating since they didn’t generate any lasting assets.

To that end, in March 2026, I resumed publishing Nascent with Episode 019 and announced my plan to publish a weekly podcast along with a companion summary newsletter for the next 100 weeks. Little did I know that a 1:1 ratio of podcast to newsletter would be brutal. I did this for 10 weeks, through Episode 029, and found it to be like sprinting a marathon in marketing that left no time for my true passion: supporting founders directly, not just publishing guidance from the sidelines.

So starting with Episode 030, I’ve got a new plan. At least for now, every podcast episode will have an accompanying series of newsletters — an initial summary, followed by deeper dives into key points from the podcast. A ratio of roughly 1:4, one podcast with four newsletters. To hopefully make it easier to follow, I’m using a numbering system that shows the relationship between the podcast and newsletters. When I publish a new podcast, it comes with a summary (e.g., Episode 030). Then the following week I’m publishing 030.1 as the first deep dive, the next week 030.2 as the second deep dive and so on.

So if you’re new to Nascent, I recommend that you start by reading/listening to Episode 019 and work forward from there. As always, I welcome your feedback and look forward to continuing to support founders of startups with no customers. Nascent is especially useful for founders of funded startups that are pivoting — if that’s you, let’s talk. Schedule time with me here: https://nascentidea.com/

Ok, founders. You got this!

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. For more, check out Spotify, Apple Podcasts and YouTube.

No, founders cannot innately generate meaningful analyses of discovery interviews, but it’s a skill they can learn. Running discovery interviews and interpreting the results is a type of data transformation. We can measure the reliability of this data transformation using Krippendorff’s Alpha, which I measured for Nascent. The takeaway: I saw a dramatic increase in founders’ reliability after training. Here’s how the measurement worked.

Back in Episode 028, I described a case study where a founder named Flora used Nascent to evaluate her idea for a startup called BundleShop — an app for moms to shop for bundles of stuff for their kids. Flora recorded interviews with a bunch of moms and we analyzed the interviewees’ emotions.

The BundleShop case study was the focus of my content analysis for Nascent. Specifically, I ran workshops where participants analyzed Flora’s conversations using Nascent’s data transformation scheme, the Yardstick of Pain™. Nascent categorizes an interviewee’s emotions as either hurting, fine or joyous. I instructed workshop participants to listen to brief audio clips from Flora’s five interviews and categorize the interviewees’ emotions.

I used the workshops as an opportunity both to train founders and to measure K-Alpha. I was careful to measure K-Alpha both before and after training for 79 participants. I gave the workshop participants general guidance (“search for Pain”) for the first two interviews, which resulted in a K-Alpha = 0.1, meaning that participants’ ratings were essentially random. They might as well have flipped a coin to decide whether an interviewee was hurting, fine or joyous.

To train the participants, I pointed out key details in the first two interviews, such as how an interviewee’s tone and word choice relate to the level of emotional Pain. After the first two interviews, I considered the participants trained and let them categorize the final three interviews without me interrupting. For these post-training clips, Krippendorff’s Alpha jumped to 0.8, indicating much more reliability.

I want to be clear that I consider this measurement just the beginning of what I hope to accomplish with Nascent, since it comes from just 79 raters evaluating 5 interviews for 1 startup. Still, this dramatic increase from randomness to reliability has huge implications for founders of startups with no customers. As much as founders are told to run interviews and make inferences, this is not something that founders can do inherently. But the jump from 0.1 to 0.8 shows that it’s a skill founders can learn.

Founders need to be aware of content analysis but don’t need to be experts, in the same way that a baker uses a thermometer but doesn’t need a PhD in physics. If you’re a founder interpreting a discovery interview, ask yourself what data transformation scheme you’re using and whether you measured it with content analysis or something similar. If not, be skeptical of the takeaways.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.3 📬, a deep dive into how I measured K-Alpha for Nascent’s data transformation, as discussed in Ep030 🎧 (17 mins). Read the rest of the deep dives: 030.1: analyzing interviews as data transformation and 030.2: content analysis techniques.

Entrepreneurs have a huge opportunity to avoid fooling themselves. Founders already “get out of the building” to run interviews and get feedback on their startup idea. For conventional customer discovery, this means validating assumptions about a business model. For Nascent, this is characterizing the emotions of People in Pain™. Whatever the approach, we can use content analysis techniques to measure how reliably we reach conclusions.

Analyzing discovery interviews is a form of data transformation where founders go from unstructured interview transcripts to specific categories, like “potential customer” and “not a customer”. Analyzing interviews is part of a field of study called content analysis, developed by Klaus Krippendorff, which has been largely focused on the social sciences, at least until now. I believe it unlocks huge opportunities in entrepreneurship, specifically to limit how much founders fool themselves into pursuing bad startup ideas.

I’m fascinated by the breadth of content analysis, so I want to offer a quick history and then apply it to tech startups.

Back in the 1700s, there was a scandal in Sweden about whether certain religious hymns were “dangerous” or safe. The whole debate was about categorizing religious hymns. A few hundred years later, a similar challenge arose with categorizing newspapers: How do we really know the New York Times is liberal or the Wall Street Journal is conservative? These diverse situations prompt a fundamental question: when people analyze unstructured text — hymns, newspapers, transcripts of discovery interviews — how can we know if our analysis is meaningful and reliable?

Before I share how Krippendorff solved this challenge, first I’ll share the easiest and silliest scheme for transforming raw data into categories. First, you take the unstructured text and just throw it in the trash. Then you simply flip a coin to generate a category. Of course, this is a joke, but what matters is that randomly flipping a coin will generate results. It’s just that the results will be meaningless. This joke reveals a core concept that leads to founders fooling themselves: It’s easy to accidentally invent a fancy coin-flipping machine and not realize it.

A core insight of content analysis is to measure how a data transformation scheme compares to random chance. Specifically, Krippendorff’s idea was to train human raters to apply categorization rules (“a coding manual”) to categorize texts — and then to compare the humans’ results to random chance. Essentially asking: How do the raters compare to coin flips?

One way to make that comparison is a metric called Krippendorff’s Alpha. K-Alpha goes from 0.0 where the categorization scheme is completely random up to 1.0 indicating perfect reliability — all the raters are in perfect alignment. Roughly speaking, high inter-rater reliability is a K-Alpha of 0.8 or higher, whereas a K-Alpha below 0.6 indicates that the scheme is not reliable, i.e., it might as well be a coin-flipping machine.

Content analysis empowers founders to go from asking the wrong question, “Do we have a process for analyzing interviews?” to instead ask the more meaningful question: “How reliable is our process?”

Every time a founder speaks with someone about a startup idea, they’re making inferences. Content analysis just lets us do it reliably. In future posts, I’ll show you how I used these tools to measure the reliability of Nascent itself.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.2 📬, a deep dive into the concept of content analysis discussed in Ep030 🎧 (17 mins). Read the rest of the deep dives: 030.1: analyzing interviews as data transformation and 030.3: how I measured the jump in Krippendorff’s Alpha.

Analyzing discovery interviews, going from conversations to conclusions, is a form of data transformation. When you consider customer discovery from this perspective, it unlocks an opportunity. Founders can use content analysis techniques to measure the reliability of how they reach conclusions.

An entrepreneur has just one priority when they have a startup idea: search for a signal about their startup’s likelihood to get customers. And the best way to do that is through discovery interviews, by speaking with people who might become the startup’s first customers.

As a mentor, I’ve seen that founders often struggle with discovery interviews. In terms of data gathering, founders have told me that they’re unsure what questions to ask. And then with data analysis, founders also say that they don’t know how to make sense of the answers that they get.

Nascent addresses the data-gathering challenge by offering founders a mental framework: a startup is a project to create new, valuable knowledge about People in Pain™. For data analysis, Nascent provides founders with a tool called the Yardstick of Pain™ to characterize the emotions of an interviewee. All this to say, founders’ challenges around data gathering and data analysis are important, but there’s an even bigger issue with the reliability of our analysis. How do we know that the conclusions we draw are reliable?

At a high level, analyzing interviews is a data transformation. Founders take a raw, unstructured interview transcript and reduce it down to something like Category A and Category B. Specifically, Nascent has founders use the Yardstick of Pain to categorize interviewees as “hurting, fine or joyous”. Similarly, conventional customer discovery has founders categorize assumptions about a business model as “valid or invalid”. Even in a quick chat, when a founder says to a friend, “I’ve got an idea for a startup -- let me know what you think”, the founder is transforming data from the conversation into takeaways about the startup idea. In all of these cases, founders tell themselves stories about what they learned in the conversations.

The Nobel Prize winner Daniel Kahneman says in his book Thinking, Fast and Slow:

High confidence means that we’ve structured a coherent story, not that the story is true.

For instance, when a gambler in a casino blows on their dice, it means that they’ve told themselves a coherent story that blowing cool air brings good luck. As founders, it’s easy to tell ourselves a coherent story about our takeaways from a discovery interview. Data transformation based on vibes is a recipe for fooling ourselves.

What we really need is to analyze interviews reliably. The good news is that there are tools from other fields that we can apply to our challenge, specifically content analysis and a metric called Krippendorff’s Alpha.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.1 📬, a deep dive into the concept of data transformation discussed in Ep030 🎧 (17 mins). The deep dives continue in 030.2: content analysis techniques and 030.3: how I measured the jump in Krippendorff’s Alpha.

Yes, founders trick themselves when they analyze interviews, even though interviews are the most effective way to evaluate a startup idea. The catch is that founders struggle to analyze interviews reliably. In fact, until now, founders have never measured the reliability of their interview analysis so we have every reason to believe that the analyses are no better than randomly rolling dice. This drives founders’ most common outcome: a year wasted on a bad startup idea. The entire goal of Nascent is to provide founders with a toolkit that dramatically reduces that time down to days. Measurement of both interviews AND reliability is the key to better outcomes.

Judgments based on vibes result in lots of wasted effort. Founders today are kind of like medieval bakers sticking their hands in an oven to judge the heat. Sometimes the bread is burnt. Sometimes it’s raw, uncooked dough. Either way, the result was often a mess, at least until bakers began measuring temperature. Measurement unlocks improvement.

To that end, I’m excited to share two concepts that will do for startups what Celsius and Fahrenheit did for baking: content analysis and Krippendorff’s Alpha. Most founders have never heard of these tools but they desperately need to.

Fundamentally, content analysis frames founders’ process of analyzing interviews as a data transformation challenge. Founders go from raw, unstructured interview transcripts to specific, defined categories. Founders typically use interviews to decide whether the interviewee is a potential customer (Category A) or not a customer (Category B), but this approach is ad hoc. Klaus Krippendorff developed content analysis as “a research technique for making replicable and valid inferences from texts.” What this means for founders is that we can structure and measure our analysis of discovery interviews. Specifically, Krippendorff’s Alpha measures how reliably founders execute the data transformation (“the inter-rater reliability”) from completely random (K-Alpha = 0) to perfect reliability (K-Alpha = 1). Krippendorff’s Alpha measures how much founders are tricking themselves, when the interview analysis feels meaningful but is no better than rolling dice. 🎲

As far as I can tell, I am the first person to apply content-analysis techniques to customer discovery interviews to evaluate startup ideas. Specifically, last year I measured reliability of 79 “human raters” analyzing discovery interviews. Before training, their analysis was essentially random — their K-Alpha was 0.1. They didn’t really know what they were searching for, even though I told them to look for emotional pain (i.e., interviewees who might care about the startup idea). After I trained them, their K-Alpha jumped dramatically to 0.8, meaning their analysis was much more reliable.

When someone tells a baker that the oven is hot, they don’t accept it at face value. The baker asks for the temperature. In that same way, as a founder, if someone tells you that an interview means something, I hope you’ll ask them: How did you measure it? And if they didn’t use content analysis or something similar, it’s likely that they’re tricking themselves.

Over the coming posts, I’ll expand on the big ideas in this episode: 030.1: analyzing interviews as data transformation, 030.2: content analysis techniques and 030.3: how I measured the 0.1 → 0.8 jump in Krippendorff’s Alpha. The Ep030 video (17mins) tells the whole story.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep030. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

The recipe for success that works for legendary founders won’t work for you because it relies on their intuition. It’s unfortunate that founders look to advice from Paul Graham, Reid Hoffman and Peter Thiel because these legends cannot explain their innate sense for spotting good startup ideas. As for the rest of us, we can’t mimic intuition — repeat founders and pivoting founders have learned this the hard way. The good news is we can replicate intuition with measurement.

Reid Hoffman says to jump off a cliff and assemble the plane on the way down. This advice works for him because he has an innate sense for whether the plane will fly. The rest of us don’t so Hoffman’s advice is a recipe for disaster.

Peter Thiel lists seven questions every business must answer, including “Have you identified a unique opportunity that others don’t see?” He recognizes finding a high-value opportunity is critical but Thiel doesn’t explain how to know when you have one.

Paul Graham has “an internal compass” for recognizing good startup ideas — but he never articulated how it works:

I seem to have some sort of internal compass that helps me out. Maybe I could come up with some heuristics for recognizing genuinely interesting ideas. That’s important enough to write a whole essay about and I don’t know the answer. I probably should write something about that, but I don’t know.

If your first attempt at a startup failed, the bug was likely with your intuition, not your ability or effort. For normal founders without an innate sense for good startup ideas, Nascent is a toolkit, strategy and measurement system to overcome this challenge. Specifically, Nascent offers you frameworks for understanding startups with no customers along with discrete, actionable steps for evaluating a startup idea. The legendary founders get to skip this and barely realize it. The rest of us need to vet startup ideas explicitly. And if we don’t, then we’ll likely waste a year on a bad idea.

Why is this so hard? The most challenging type of business to create is a startup discovering a new type of customer with an unmet need. And the most challenging moment for that customer-breakthrough startup is before the startup has customers. A founder of a customer-breakthrough startup needs to create knowledge about (1) the problem, (2) the people with a problem and (3) the technology solution. And at the beginning, when a startup has no customers, the founder has the least amount of knowledge so they face the biggest challenge.

Ultimately, a successful customer-breakthrough startup will be based on knowledge that comes from customers. Founders of startups with no customers face a Catch-22: How can they get customers so they can create knowledge to get more customers? This question is insidious and misleading because most startups will never meaningfully get customers and kick off that virtuous cycle. The better question is: What are the chances of the startup ever getting customers? To answer this, the legendary founders leverage their intuition. The rest of us need to begin by identifying People in Pain™.

Anyone who’s ever been a customer of anything ever, always began as a Person in Pain. The first and most crucial step is searching for People in Pain who emotionally resonate with the problem that the startup will solve. Founders need to search for these People in Pain who are hurting as the first signal that the startup might someday have customers. The catch is that customers are visible (you can see them paying money) whereas People in Pain are invisible (you cannot see their feelings). Most people in this world are Blockers who will never care about the startup. However, if you’re lucky, somewhere buried in the Blockers are a few People in Pain. Your job as a founder is to find a few of those hidden People in Pain before you waste a year.

Want to put this into practice? Your first step is to record one conversation with someone who might benefit from your startup and categorize the Pain. In the coming posts, I’ll detail how to take these inputs and turn them into Estimated Revenue Next Year, Nascent’s metric for evaluating a startup idea with no customers.

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

I believe that speaking with people is the best way to vet a startup idea, but only when founders know what they’re looking for. Unfortunately, most founders aren’t sure what to search for, which is why it’s so common for founders to waste a year pursuing a bad startup idea.

What’s most important? Founders need to understand interviewees’ feelings about the problem the startup will solve. Nascent is a strategy for founders of startups with no customers that includes a tool called the Yardstick of Pain™ to characterize interviewees’ emotions.

Here’s a case study with a real founder named Flora who came to me to vet an idea for her startup. She only wanted to work on it if there was a good chance it would get customers. We applied Nascent to vet her startup idea in days, not years, beginning with characterizing emotions.

As an entrepreneur and a mom, Flora noticed that shopping for kids is overwhelming and wanted to solve this problem with “BundleShop”, an app for moms to shop for bundles of stuff for their kids. The idea for the app doesn’t matter -- only that it implies overwhelmed moms — People in Pain™ who might become customers. So our plan was for Flora to interview moms and categorize each interviewee’s emotions using the Yardstick of Pain as either hurting, fine or joyous.

Side note before I share takeaways from the case study: Normally, this newsletter is a summary of the podcast for folks who don’t have time to listen. In this case, I strongly encourage you to at least listen to the interview clips, starting here.

This case study was the focus of workshops that I ran last year, so I want to share some of the lessons learned. One recurring theme was that a number of participants’ biases led them to misinterpret the interviews. For instance, in one interview a mom talked about all the many places she went to shop for her kid’s birthday party. Her tone was completely indifferent. Nonetheless, a participant was convinced that the mom must be hurting because traveling to all of those places is clearly a pain. Yes, going around town is a pain for the workshop participant, but that’s not the question. The goal of the exercise was to categorize the experience for the interviewed mom, and that interviewee was fine. This type of mischaracterization is a driving factor that leads founders to believe that their startup is going to get customers when the chances are actually doubtful.

After training, participants began to identify interviewees’ emotions. For instance, they latched on to the audio clip of another mom who said, “that [shopping] sometimes makes me anxious.” These types of negative emotions -- anxiety, stress, worry -- are exactly what founders need to search for.

As a founder, your ultimate goal is to create a product that moves customers along the Yardstick of Pain. People who are joyous have nowhere to go. People who are fine theoretically could move up to joyous, but the chances are so low that it’s not worth trying. Only people who are hurting and want to become fine might be your startup’s first customers.

Want to put this into practice? Over the past few posts, I’ve asked you to record conversations with people who might benefit from your startup. The next step: listen to those recordings and categorize the pain of each interviewee using the Yardstick of Pain. This is the first step towards quantifying a startup idea in dollars with an ERNY™ value (Estimated Revenue Next Year).

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

Most founders don’t know what they’re looking for in discovery interviews so they don’t know if they found it. Founders need a meaningful, structured way to make sense of interview data. I believe this is possible. Moreover, with the right tools, founders can be decisive in days (not years!) about choosing a startup idea worth pursuing.

If an architect told you, “we eye-balled the dimensions of your house; we didn’t use a ruler,” you’d expect the house to collapse. But in entrepreneurship, when a founder speaks with a potential customer about their startup idea they often conclude, “Yeah, that was validating,” and their co-founder agrees: “Sounds about right.” They’re falling into the trap articulated by Richard Feynman: “The first principle is that you must not fool yourself, and you are the easiest person to fool.”

I spent my early career building test systems for consumer products where I learned that test systems must have consistency and repeatability. The way founders analyze interviews today is inconsistent and ad hoc. The bug is with the approach to data, not the founders. Previously, we talked about Nascent’s four-part approach to data in discovery interviews:

1. Gather data by “Getting Out of the Building” 🏢

2. Capture data with audio recordings 🎤

3. Categorize data like a nurse searching for Pain 👩‍⚕️

4. Iterate like a wildcatter making incremental investments 🛢️

The first step in categorization is applying a tool I call the Yardstick of Pain™. During the interview founders ask questions centered around: “When was the last time you had this experience? How did it feel?” Founders then categorize the interviewee’s emotions into exactly one bin: hurting or fine or joyous.

Most interviewees will reply to these emotional questions with something like “Yeah, I did it and it was okay.” -- they’re fine. Occasionally, an interviewee might say “Oh, that happened to me last week and it was fantastic” -- they’re joyous. And if we get lucky, someone says “Ugh. I did that and it was horrible.” That person is hurting. And that’s the first sign that a Person in Pain™ might someday become a customer.

How many interviews do you need? Conventional discovery programs typically require 100 interviews over the course of months, such as NSF I-Corps. With Nascent, our goal is to work in batches of five interviews over a few days, like a wildcatter prospecting for oil. Wildcatters don’t go a mile deep before deciding; they drill a few feet at a time, look for signal, then decide whether to keep going.

Nascent is the strategy that I wish I would have had for every time I had an idea for a startup. I’ve run hundreds of discovery interviews but still wasted years pursuing bad ideas. Nascent would have clarified what I was searching for (People in Pain!) and the Yardstick of Pain would have let me categorize my interviewees so that I could make a quick decision.

Want to put this into practice? Look around you right now. Every product you see in this world implies People in Pain. Tylenol implies people with headaches. Chairs imply people who have a sore back from standing up. Pick a product near you and try to articulate aloud: What is this product? And what Pain does it imply? Once you can do that with existing products, you can apply it to the products that don’t yet exist, i.e., the product you want to build with your startup. In the coming posts, I’ll detail how to go from categorizing interviewees using the Yardstick of Pain bins to quantifying them in dollars with an ERNY™ value (Estimated Revenue Next Year).

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year ($) for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

Why do founders often waste a year on a bad startup idea despite running “customer-discovery interviews”? Most founders accept low-quality data that they’d NEVER accept elsewhere. Specifically, founders “capture” data using their memory and their notes -- self-reported data that’s a recipe for getting fooled. Instead, they need recordings to actually capture what interviewees say. I believe that with the right structure and focus, founders could be decisive in days about investing time in their startup idea.

If someone told you that they met a person who is 20-feet tall, you’d probably reply: “Prove it. Show me the guy and bring a tape measure.” But I’ve worked with so many teams of founders where one says “I interviewed a customer” and their co-founder says “Yup, sounds about right.” No asking for proof, just blind acceptance. They’re falling into the trap articulated by Richard Feynman: “The first principle is that you must not fool yourself, and you are the easiest person to fool.”

Humans are wonderful people, but we’re horrible at data capture. Our memories are faulty. Our notes require interpretation, which mixes accurate and erroneous data. Fundamentally, a startup is a project in creating new, valuable knowledge. The data that a founder gathers is the basis of that knowledge. This means that a faulty process for running interviews leads to a chain of events: bad data = misunderstandings = wasted year.

The bug is with the approach to capturing data, not the founder. You can use Nascent as a strategy to avoid fooling yourself, beginning with this four-part structure:

1. Gather data by “Getting Out of the Building” 🏢

2. Capture data with audio recordings 🎤

3. Categorize data like a nurse searching for Pain 👩‍⚕️

4. Iterate like a wildcatter making incremental investments 🛢️

Recordings are the foundation of your project. Historically, recorded conversations have been taboo, but that changed in 2020 with COVID. That year most of us spent our lives online and accepted recordings. It’s now become normal to record Zoom meetings with a note-taker bot like Otter.ai. It can still be awkward to record in-person conversations, but I’ve found that interviewees now often agree to recordings. The unlock is that interviewees want to be helpful (that’s why they talk with founders in the first place!) so founders secure consent by highlighting that recordings make interviewees even more helpful. I’ve found this statement works about 80% of the time:

What you’re saying is helpful. I don’t wanna be distracted taking notes.

Would you mind if I recorded our conversation?

Want to put this into practice? Go record one conversation with one person who might benefit from your startup. That’s your first step to build a solid foundation for your knowledge-creation project. In the coming posts, I’ll detail how to analyze those recordings to get a meaningful understanding of the potential for your startup to get customers.

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year ($) for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

A subscriber asked: Isn’t searching for People in Pain just marketing? Nope.

In Episode 022, I said that the only thing that matters for founders of startups with no customers is to search for invisible People in Pain™, which I illustrated using the People-to-Prospect Funnel™. Then I walked through an example applying this to a food-cart pod where the prospects and customers are visible. Meanwhile outside the pod, the people walking by are mostly blockers (people who won’t become customers) as well as rare, special People in Pain -- they’re hungry but don’t realize the food carts want to serve them.

This framework in Episode 022 prompted a comment on YouTube:

the people outside the fence are possible customers. Prospects. You can put a sign that says come get some hot dogs. Isn’t that called marketing? Therefore, Finding those people in pain is marketing .

Nope. Marketing is a project to deploy existing knowledge. Searching for People in Pain is a project to decide whether to try to get that knowledge in the first place. This seemingly simple question is about a conventional hot-dog stand business where all the components are visible. The distinction is even more important for a customer-breakthrough tech startup where all the components are invisible.

To see the difference, imagine a data disaster where a marketer wakes up one day with no customer data. All of their databases were somehow wiped out but at least the business itself is still running. So the marketer can get more customer data, turn the data into knowledge and use that to make marketing decisions. As a benchmark, advertisements typically have a 1% conversion rate and cost about $10 for 1,000 ad impressions. In other words, even when a marketer has knowledge about their target audience, 99% of their advertisements are just spam wasted on blockers in an effort to send a message to the few, special People in Pain.

Now, think about the founder of a startup with no customers. Every day is a data disaster for founders. Every morning begins with a full cup of coffee and an empty database. Even worse, there’s no clear starting point because there are no customers to learn from. There is no knowledge to create a targeted marketing campaign. Today, most founders tackle this challenge by using assumptions, not knowledge. Then, after a year, the founders recognize that the startup will never get customers and that they have nothing to show for all their effort. This sucks.

To respond to the question directly: Yes, any hot-dog stand owner can just put up a sign and, yes, that could be called marketing. However, the effectiveness of the marketing campaign is completely dependent on the invisible, underlying knowledge. Without knowledge, marketing is useless: the ad spend gets absorbed completely by spamming blockers, not messaging the People in Pain. Without knowledge, marketing cannot drive new prospects and customers.

Founders of startups with no customers face a cold-start problem. For these founders only one question matters: If you pursue a startup and embark on a knowledge-creation project, how valuable might that knowledge be and for whom? Nascent is a strategy for answering this question by quantifying a startup idea in dollars ($). Until you have a signal that there might be any value to creating knowledge, then putting up a sign or running any other marketing campaign is a distraction.

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As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.