Forging The Right Problem Fit
The Startup’s First Battle
I’ve seen it happen too many times—great products fail because they don’t solve a real problem. Before considering product-market fit (PMF), I know the first and most crucial challenge is achieving problem fit. While PMF means a product successfully serves a market need, problem fit comes first—it ensures that the problem I’m tackling is real, painful, and worth solving.
I’ve fallen into the trap of building a solution in search of a problem, and I’ve watched others make the same mistake. A classic example is Juicero, a high-tech juicer startup that raised over $100M but failed because consumers realized they could simply squeeze juice packs by hand—making the expensive machine unnecessary. The company built an advanced product without validating if the problem was significant enough to justify its existence. Others pick a problem that isn’t urgent, severe, or frequent enough to drive adoption. In this edition of The Anvil, I’ll break down the best frameworks to validate problem fit and help you set your startup on the right course.
Why Problem Fit Matters
Startups don’t fail because they can’t build a product. They fail because they build something nobody wants. A strong problem fit ensures:
Customer Pull – People actively seek solutions, reducing the need for aggressive persuasion.
Market Validation – You avoid wasting time and resources on a weak idea.
Higher Adoption & Retention – Solving a painful problem means customers stick around.
Stronger Fundraising Position – Investors bet on painkillers, not vitamins.
Frameworks to Validate Problem Fit
Choosing the right framework to validate problem fit depends on the nature of your idea, industry, and target audience. Each framework offers a different lens to assess whether a problem is worth solving. Using these tools early can save you from wasting time and resources on solutions that lack real demand.
1. The Problem Hypothesis Framework
I treat this like the scientific method for startups. I need to test whether the problem is real before jumping into a solution.
✅ I ask myself:
Who has this problem? (Clearly define the target audience)
What is the pain point? (Be specific about the frustration or inefficiency)
How are people solving it today? (Workarounds, alternatives, or ignoring it?)
Why is it a big enough problem? (Is it frequent, costly, or urgent?)
How do I validate this? (Interviews, behavioral data, search trends?)
2. The Jobs-To-Be-Done (JTBD) Framework
People don’t buy products; they hire solutions to accomplish a task. Understanding the core job a customer is trying to accomplish helps refine the problem fit.
🔹 Key steps:
Identify the “job” customers need to complete.
Understand current solutions and why they fall short.
Find pain points in those solutions—are they slow, expensive, or frustrating?
Gauge if customers would switch to a better solution.
💡 Example: Uber replaced unreliable taxis by offering a more convenient, transparent, and seamless way to get a ride.
3. The Mom Test
People lie, especially when they don’t want to hurt my feelings. The Mom Test helps me conduct better customer discovery interviews.
🚫 I avoid asking:
“Would you use this?” (People say yes to be nice)
“Do you think this is a good idea?” (Everyone thinks ideas are good until they need to pay)
✅ I ask instead:
“How have you solved this problem before?” (Reveals real behavior)
“Can you walk me through the last time this happened?” (Gets specific)
“What’s frustrating about your current solution?” (Uncovers pain points)
4. The 10x vs. 10% Rule
If my solution is only 10% better, customers won’t switch. But if it’s 10x better, they will.
💡 I test it:
Does my solution dramatically reduce cost, friction, or complexity?
Is it exponentially faster or easier?
Would users say, “I can’t go back to the old way”?
📌 Example: Gmail was 10x better than Hotmail and Yahoo Mail with its search, spam filtering, and storage.
5. The Pain vs. Frequency Matrix
A quick way I measure if a problem is worth solving is by mapping it on pain vs. frequency.
If my problem falls into the “high pain, high frequency” box, I know I’m onto something powerful.
6. The Market-Pull Test
If a problem truly exists, people are already looking for solutions.
🔎 Ways I validate market pull:
High search volume for related pain points.
Active Reddit/Twitter discussions about frustrations.
Workarounds like spreadsheets, manual hacks, or hiring consultants.
People already paying for bad solutions because no better option exists.
A Futures Thinking Perspective: Validating Tomorrow’s Problems
The frameworks above work well for existing problems, but how do I validate a problem that doesn’t exist yet? Future thinking requires scanning signals of change and anticipating how emerging trends will create new, high-impact problems.
🔮 Example: The Rise of AI-Generated Content A decade ago, AI writing tools were seen as science fiction. But applying the problem fit frameworks early could have validated future challenges such as:
Problem Hypothesis: Will businesses and individuals struggle to differentiate between human vs. AI-generated content?
Jobs-To-Be-Done: What will professionals need in an AI-driven content world? (Verification tools, authenticity markers, or AI-powered assistants?)
The 10x Rule: Will future solutions be 10x better at detecting, enhancing, or personalizing AI-generated content?
Pain vs. Frequency: As AI content generation grows, will concerns over misinformation become a high-frequency, high-pain problem?
Market-Pull: Are early adopters already looking for solutions? (Patent filings, startup activity, and discussions on AI ethics hint at this trend.)
Using these frameworks, I can predict and validate future problems before they become mainstream, giving me a first-mover advantage.
Final Thoughts: The Battle Before the War
Finding a problem fit isn’t glamorous—it’s slow, frustrating, and often humbling. But it’s the battle I must win before fighting for product-market fit. Startups that nail problem fit build products people need, not just products that seem cool.
Key Takeaways:
Validate before you build – Use structured frameworks to ensure the problem is real and worth solving.
Seek customer pull – If people aren’t actively searching for a solution, the problem might not be painful enough.
10x improvement wins – Small, incremental upgrades won’t drive adoption; transformative solutions will.
Future-proof problem fit – Consider how emerging trends might create new pain points before they become mainstream.
💡 If this article resonated with you, share it with a fellow founder or investor. Let’s keep the conversation going—what’s a startup idea you’ve seen fail due to poor problem fit? Comment below or reply to this newsletter!
🔨 Keep forging