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Why Product Market Fit for Startups Fails (And How to Get It Right)

product market fit for startups shweta agrawal
Blog Author: Rina Alexin

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If you’ve ever worked with early-stage founders, you know this: product market fit for startups is rarely lost in execution. It’s usually lost long before a single line of code is written. 

That truth came through loud and clear in my recent conversation with Shweta Agrawal on Productside Stories. Shweta’s a seasoned product leader whose work spans Philips, Brightcove, and more than a decade of advising founders across health tech, fintech, edtech, and beyond. And she’s seen every possible way PMF (product market fit) can go sideways.   

As we talked, I realized how many teams (whether a one-person startup or a 500-person enterprise) fall into the same traps. The same shortcuts. The same assumptions. The same desire to move fast… without doing the one thing that determines whether product market fit for startups is even possible: 

Talking to real customers. 

What follows is the story Shweta shared and the lessons every founder and product leader should take from it. 

 

When Founders Rush the Journey to Product Market Fit

Shweta said something early on that made me laugh because I’ve seen it so many times: founders wanting to “launch a product in two months.” 

Not an alpha.
Not a prototype.
Not an MVP.
full product. 

She gave one example of a founder who had already designed the website, the pitch, and the entire AI writing tool intended “for everyone.” Writers, journalists, book authors… or maybe just anyone, really. When she asked him how many customers he’d spoken with, the answer was as familiar as it was painful: 

“None. But I think this is a real problem.” 

Another founder was building an AI learning platform for seniors, people over 60. The whole site was up. The idea was fully formed. And yet when asked who she’d talked to? 

No one. 

Another founder spent months building a mental-health wearable that would mix sound and music to ease anxiety. They were even trying to raise money. But when Shweta asked how many pilot customers they had? 

Zero. 

I paused during the interview. Because this isn’t a startup problem. It’s a human problem. When we see a problem ourselves, it becomes hard to imagine other people don’t see it the same way. That’s exactly how product market fit for startups quietly slips out of reach: the founder becomes the customer. 

And you can’t find PMF if you’re building only for yourself. 

 

“I Want to Launch Before Someone Else Does”

When I pushed on why founders skip discovery, Shweta explained something important: it’s not that they don’t value it. It’s that they feel pressure. 

Pressure from the market.
Pressure from AI hype.
Pressure from the speed of other startups.
Pressure from the belief that whoever “launches first” wins. 

But the cost of going fast in the wrong direction is far higher than going slower in the right one. 

One founder learned that the hard way. They spent months developing a complete product before talking to customers. When they finally launched? 

No one wanted it. 

So they had to start over. This time, talking to hundreds of customers, looking for patterns, building alpha tests, creating focus groups, and slowly shaping what the MVP needed to be. 

It took more time. But it saved them from repeating the same mistake twice. 

This is the heart of product market fit for startups: it’s not a magical moment. It’s a set of evidence points that show people are using your product consistently, paying for it, renewing, and returning. 

You can’t sprint your way to evidence. You have to gather it. 

 

The Notebook That Had “Everyone” as the ICP

One of my favorite stories Shweta shared involved a smart notebook: a physical book paired with a pen that syncs your handwritten notes to the cloud. 

The founders were convinced it was universal. Students! Professionals! Anyone taking notes! 

In early conversations, people said they’d use it. Great. That must be PMF, right? 

But when they launched pilots, only two or three customers actually used the product, and not very often. 

The early enthusiasm didn’t sustain. The novelty didn’t translate to real behavior. And the glaring question emerged: 

Why wouldn’t someone just use an iPad? 

When they realized students wouldn’t pay hundreds of dollars for a notebook, they pivoted away from the “everyone” market. They moved toward enterprise buyers who had the budget and use case. 

It’s a perfect example of how product market fit for startups isn’t something you “declare.” It’s something market behavior confirms (or contradicts). 

And sometimes, as in this case, the market forces you to narrow before you can ever scale. 

 

The Most Underrated Skill: Letting Go of Your Own Assumptions

Shweta told story after story that came back to one theme: the hardest part of achieving PMF is being willing to be wrong. 

One founder insisted 5–10 customer interviews were enough. Another assumed their experience alone gave them the insight they needed. Another believed the need was “obvious” because they felt it personally. 

But PMF comes from: 

  • Customers who renew 
  • Customers who spend more time in your product 
  • Customers who come back daily or weekly 
  • Customers who pay every month 
  • Customers who would be upset if your product disappeared 

None of these things are assumptions. They’re behaviors. 

And behaviors tell the truth. 

 

How Product Market Fit for Startups Shapes Go-to-Market Success

Toward the end of our conversation, we talked about GTM, not as something you do after finding PMF, but something shaped by PMF. 

Your ICP changes.
Your positioning changes.
Your messaging changes.
Your partnerships change.
Your pricing changes. 

Everything becomes clearer once product market fit for startups is real. 

Shweta described founders expanding internationally without considering cultural differences, compliance, or even how parents in India think about mental health solutions for students (“This is for mental resilience” sells better than “This is for anxiety”). Even the same product requires different messaging and distribution depending on the region. 

You can’t get any of that right unless you deeply understand who you’re building for and how they behave. 

 

Where You Go Next With Product Market Fit for Startups

Spending time with Shweta reinforced something I see across so many founders who eventually succeed: they stay curious longer than they stay certain. They pause when others rush. They talk to real customers. They rethink their assumptions. They pivot when the evidence tells them to. 

And they redefine what founder discipline really looks like. 

  • Listen to the full conversation with Shweta Agrawal on Productside Stories — available now on Spotify, Apple Podcasts, and Amazon Music. You can also watch it on YouTube. 
  • Want to strengthen your own ability to validate markets, uncover real customer needs, and build the right product before you build the big product? Explore our Optimal Product Management Certification — the course designed to help PMs and product leaders shift from reactive delivery to strategic, customer-centric judgment. 
  • Now it’s your turn. Which part of Shweta’s journey resonated most with you? Have you ever had to unlearn your own assumptions in the pursuit of PMF? Share your reflections and tag @Productside on LinkedIn. We’d love to hear how you’re navigating your own path to product market fit. 

About The Author

Rina Alexin

Rina Alexin, the CEO of Productside holds a BA with honors from Amherst College and an MBA from Harvard Business School. She is also a member of the AIPMM.

Frequently Asked Questions

Most startups fail to achieve product market fit because they rely on assumptions instead of customer evidence. As Shweta described in our conversation, many founders launch full products in “two months” without talking to users, skip alpha or beta stages, or assume they are the customer. This leads to building solutions for imagined problems rather than validated ones. Product market fit emerges only when customers actually use, return to, and pay for your product — and that requires rigorous discovery first.
While there’s no universal number, Shweta advises founders to think far bigger than the typical five or ten interviews. She recommends aiming for hundreds — enough conversations to see clear patterns, contradictions, and real user behavior. The founders she’s helped most successfully often spend months interviewing customers, synthesizing insights, and testing assumptions before writing code. This level of discovery dramatically increases the odds of building something people will actually use.
Real product market fit isn’t a feeling — it’s behavior. According to Shweta, evidence includes customers returning regularly, spending meaningful time in the product, renewing subscriptions, and paying month after month. Another test she mentioned is the “disappointment metric”: if you shut down the product tomorrow, would at least 40% of customers be upset? If the answer is yes and you’re retaining a significant portion of your early users, you’re likely on the right track.
Weak usage doesn’t mean failure — it’s a signal. Shweta shared a story of founders building a $400 smart notebook they believed “everyone” would want. Early pilot customers barely used it. Instead of forcing the original direction, she encouraged them to pivot: narrow the ICP, rethink the value proposition, and target buyers (like enterprise professionals) who could actually benefit and pay. When pilots underperform, the goal isn’t to patch the product — it’s to revisit the assumptions underneath it.
Founders can avoid premature building by investing heavily in discovery and validation. In our conversation, Shweta emphasized using prototypes, focus groups, and alpha tests long before committing engineering resources. She also encourages founders to ask users what they currently use, what they pay for, and what would make them switch. Tools and prototypes — even low-fidelity ones — allow founders to test desirability without burning time or capital. The goal is to validate the problem before validating the solution.