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пятница, 30 января 2026 г.

The 5 Critical Hypotheses That Make or Break Your Startup

 



Product-market fit remains one of the most discussed yet least understood concepts in startup building. We've mystified it, treating it like a binary switch that suddenly flips from "no PMF" to "PMF achieved."

But this approach leaves founders navigating without instruments. In my previous article on why 9 out of 10 startups fail, I showed how the product-first obsession of “build it and they will come” leads directly to billions in wasted runway and countless failed companies.

The PMF monolith

The startup world has become remarkably scientific about certain aspects of building companies—growth marketing, software development, even fundraising. Yet when it comes to product-market fit, rigor is abandoned for intuition, leaving founders staring up at an imposing, inscrutable monolith with no clear path forward.

This creates a dangerous knowledge gap. Founders know they need product-market fit, but lack a systematic approach to find it. They're left with unhelpful advice like "talk to customers" or "iterate quickly"—the startup equivalent of "just be yourself" on a first date.

First principles thinking

When facing complex problems, the most effective approach is to break them down to their fundamental components. By applying first principles thinking to product-market fit, we can transform an ambiguous concept into a set of testable hypotheses.

After studying the patterns of successful and failed startups, and consolidating insights from years of product launches, I've identified five critical hypotheses that every startup must validate. These aren't arbitrary or theoretical—they represent the core assumptions that must be true for any business to succeed.

This approach is the difference between spending runway on educated guesses versus running targeted experiments that deliver actionable insights.

The 5 critical hypotheses framework

These five hypotheses form the foundation of product-market fit:

1. Category

This is your strategic playing field—the specific market space where you choose to compete. Think of it as choosing which game you're playing, not just how you'll play it.

When you get it right: You find yourself in a growing market with clear demand signals, where your strengths align with market needs. Investors immediately understand your opportunity. Customers easily categorize and remember you. Your growth trajectory matches the market's natural momentum.

When you get it wrong: You're constantly fighting uphill. Either you're in a shrinking market, or you're positioning in a way that confuses customers and investors alike. You hear "So you're like X meets Y?" Your marketing dollars evaporate with minimal return. Your sales cycles extend because you're constantly explaining what category you're in.

2. Customer

This defines exactly who you're serving—and more importantly, who you're NOT serving. It's a specific segment with identifiable characteristics, common needs, and similar buying behavior.

When you get it right: Your marketing speaks directly to prospective customers' specific pain points. You know exactly where to find them. Your acquisition costs are predictable and sustainable. Your sales cycles shorten because you're answering the exact questions your prospects actually ask. Your product team knows precisely who they're building for.

When you get it wrong: You create "consensus products" that try to please everyone but delight no one. Your marketing messages sound generic because they are generic. Your limited resources are spread too thin across too many customer types. Your customer acquisition is like a slot machine – occasionally you hit a match, but you can't predict when or why.

3. Problem

This validates that the problem you're solving is actually worth solving—not just technically interesting or vaguely annoying, but genuinely painful enough that people will pay to make it go away.

When you get it right: Prospects' eyes light up when you describe their problem. They finish your sentences. You hear "How soon can we start?" instead of "Let me think about it." You don't have to educate customers about having the problem—they're actively searching for a solution. Your sales process feels more like taking orders than convincing skeptics.

When you get it wrong: You find yourself constantly "educating the market" about why they should care. You hear things like "that's interesting" or "nice to have" instead of "I need this yesterday." Your sales cycles stretch as prospects perpetually have "more urgent priorities." You're building a vitamin when the market is looking for a painkiller.

4. Value proposition

This is the bridge between your customer's problem and your solution—it's not what you build, but why anyone should care. It's the powerful "so what?" that makes prospects reach for their wallets.

When you get it right: Your messaging resonates immediately. You can articulate your unique value in a single compelling sentence that makes people nod. Prospects clearly understand why you're different from alternatives. Price objections are rare because the value is obvious. You can communicate your core value without technical jargon or convoluted explanations.

When you get it wrong: You find yourself drowning in feature explanations while customers' eyes glaze over. Prospects constantly compare you to cheaper alternatives. Your team can't consistently articulate why customers should choose you. You resort to competing on price rather than value. Your sales material reads like a technical specification rather than a compelling narrative.

5. Solution

This is what you actually build—the product, experience, and business model that delivers on your value proposition. It's the execution that brings your strategy to life.

When you get it right: Users intuitively understand your product without extensive tutorials. Your solution delivers the promised value consistently. You're able to develop efficiently because you're building only what matters most. Your economics work because you've designed a solution that's viable to deliver. Users experience that magical "aha moment" when engaging with your product.

When you get it wrong: You create technically impressive products that users struggle to adopt. You over-build features that nobody uses while missing critical functionality. Your unit economics collapse under the weight of delivery costs. Your product roadmap feels like an endless list of fixes rather than strategic evolution.

The testing sequence

The order in which you test these hypotheses is critical.

Most technical founders work backward, building solutions before validating any of their market hypotheses:

  1. Build a solution (because that's what they're good at)
  2. Try to articulate its value (often in technical rather than benefit terms)
  3. Search for problems it might solve
  4. Hunt for customers who might care
  5. Finally, figure out how to position it in the market

This reversed approach is the startup equivalent of building an elaborate treehouse, and then looking for a suitable tree—great craftsmanship, limited utility. It explains why so many startups pivot multiple times before finding fit, or run out of runway first.

By testing market hypotheses first (category, customer, problem), you dramatically reduce the risk of building something nobody wants. Each validated hypothesis creates a foundation that de-risks the next step.

This doesn't mean you can't build anything until all hypotheses are bulletproof. It means allocating your runway proportionally to risk—spending weeks validating market assumptions can save months of wasted development.

Hypothesis-driven execution

Implementing this framework doesn't require sophisticated market research or months of delay. It's about developing a hypothesis-driven mindset where assumptions are explicitly stated, then systematically tested.

Start by documenting your current assumptions for each hypothesis:

  • What exactly is your category? (Be specific)
  • Who specifically is your customer? (Get precise)
  • What precise problem are you solving? (If it takes three paragraphs to explain, reconsider)
  • How are you uniquely valuable? (Focus on benefits, not features)
  • What is the minimum viable solution that delivers that value?

Then design simple experiments to validate each one, beginning with market elements before moving to product elements.

This might mean conducting problem validation interviews without showing your solution. Or testing landing pages with different value propositions before building features. Or experimenting with category positioning to find where you resonate most strongly.

The goal isn't perfect information—it's reducing critical uncertainties before betting your company's future on unvalidated assumptions.

Looking ahead

Finding product-market fit isn't about luck or intuition. It's about systematically validating the core hypotheses that determine whether your startup succeeds or fails.

By breaking PMF into these five components, you transform the intimidating monolith into a series of manageable experiments. Each validated hypothesis chips away at the mystery, revealing the structure beneath and becoming a load-bearing pillar of your eventual success—or a clear signal to pivot before burning more runway.

In future posts, I'll dive deeper into each hypothesis with specific frameworks for testing and measuring progress. But for now, I challenge you to honestly assess your own startup:

Which of these hypotheses have you actually validated with clear evidence?

And which are you treating as assumptions because they're convenient, comfortable, or simply because you've never questioned them?

Your answers will reveal whether you're building on solid ground or setting yourself up for an expensive education in the school of startup hard knocks.


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суббота, 28 января 2023 г.

The Hypothesis Prioritization Canvas

 Over the past 10 years we’ve been lucky to have a tremendous amount of content, practice and experience shared to help us build and design better products, services and businesses.  One of the core concepts being adopted broadly from this body of work is the hypothesis — a tactical, testable statement used to help us frame our ideas in a way that encourages experimentation, learning and discovery. The idea is that we write our ideas, not as requirements, but as our best guesses for how to deliver value and with clear success criteria to tell us whether our idea was valuable and we delivered it in a compelling way.

While there are many templates, the one I’ve been teaching for the past few years looks like this:

We believe
[this outcome] will be achieved if
[these users] attain [a benefit]
with [this solution/feature/idea].

I like this template because the act of filling it out is the first test of the hypothesis. If you and your team can’t complete this template in a way that you believe that’s a good indication you shouldn’t be working on that idea. But, assuming you’ve come up with some good ideas, you end up creating a new challenge for the team.

SO MANY HYPOTHESES, SO LITTLE (DISCOVERY) TIME

If you only have one hypothesis to test it’s clear where to spend the time you have to do discovery work. If you have many hypotheses, how do you decide where your precious discovery hours should be spent? Which hypotheses should be tested? Which ones should be de-prioritised or just thrown away? To help answer this question I’ve put together the Hypothesis Prioritisation Canvas. This relatively simple tool and a companion to the Lean UX Canvas can help facilitate an objective conversation with your team and stakeholders to determine which hypotheses will get your attention and which won’t. Let’s take a closer look at the canvas.


WHEN SHOULD WE USE THIS CANVAS?

If you’re familiar with the Lean UX Canvas, the Hypothesis Prioritisation Canvas (HPC) comes into play between Box 6 (writing hypotheses) and Box 7 (choosing the most important thing to learn next). If you’re not familiar with it, the HPC comes into play once you’ve assembled a backlog of hypotheses. You’ve identified an opportunity or problem to solve, declared your assumptions and have come up with ideas to capitalise on the opportunity or solve the problem.


WHAT KINDS OF HYPOTHESES WORK WITH THIS CANVAS?

The HPC is designed to work with any hypothesis you come up with. It can work with tactical, feature-level hypotheses as well as business model hypotheses and everything in between.

HOW DO WE USE THE CANVAS?

The canvas is a simple matrix. The horizontal axis measures your assessment of the risk of each hypothesis. This is a team activity and is the collective best guess of the people assembled of how risky this idea is to the system, product, service or business.  The challenge with assessing risk is that every hypothesis is different. Because of this, your risk assessment will be contextual to the hypothesis you’re considering. For example, you may have to integrate modern technology with a legacy back end system. In this case the risk is technical. You may be reimagining how consumers shop in your store which is risky to your customer’s experience. Maybe you’re considering moving into an adjacent market after years focusing on a different target audience. The risk here is market viability and sustainability. Every hypothesis needs to be considered individually.

The vertical axis measures perceived value. The key word here is “perceived.” Because this is a hypothesis, a guess, the value we imagine our ideas will have is exactly that, imagined. It won’t be until a scalable, sustainable version of the idea launches that we’ll know whether it lives up to our expectations. At this point we can only guess the impact the idea will have on our business if we design and implement it well.

We take each hypothesis we’ve created to solve a specific business problem and map it onto the HPC’s matrix. Once we’ve completed this process, we assess where each hypothesis landed.


BOX 1 — TEST

Any hypothesis that falls into this box is one we should test. Based on what we know right now this is a hypothesis with the chance of having significant impact on our business. However, if we get it wrong it also stands the chance of doing damage to our brand, our budget or our market opportunity. Our discovery time is always precious. These are the hypotheses that deserve that time, attention, experimentation and learning.

BOX 2 — SHIP & MEASURE

High value, low risk hypotheses don’t require discovery work. These are ideas that have a high level of confidence and, based on our experience and expertise, stand a good chance of impacting the business in a positive way. We build these ideas. However, we don’t just set and forget these solutions. We ship them and then measure their performance. We want to ensure they live up to our expectations.

BOX 3 — DON’T TEST. USUALLY DON’T BUILD.

This is, perhaps, the least clear quadrant because there are ideas that may fall here that have value despite the “low value” indication on the matrix. To be clear, hypotheses in Box 3 don’t get tested. In most cases they don’t get built either however there will be times where ideas land in this box that we need to build a successful business but that won’t differentiate us in the market. For example, if you’re going to do any kind of commerce online you’ll need a payment system. In most cases, how you collect payment is not going to differentiate you in the market. These types of ideas often end up in Box 3. They’re table stakes. We have to have them to operate but they won’t make us successful on their own. In these cases we build them, ensure they work well for our customers but don’t do extensive discovery on them prior to launch.

BOX 4 — DISCARD

Hypotheses that we deem to have low value and high risk are thrown away. Not only do we not do discovery on them, we don’t build them either. These are ideas that came up in our brainstorm that we’ve not realised won’t add the value we’re seeking.

Ultimately the value of the HPC will be realised if and how your team uses it. Take it out for a spin. It’s intended to be a team activity. Let me know how it works for you, where it can be improved and whether you find it useful or not.

I’m excited to hear your feedback.

JEFF GOTHELF

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