Posts in "SaaS"

How to Find Product-Market Fit for B2B SaaS with 14 Examples

This is a very in-depth article with 14 examples of B2B SaaS companies that found, or failed to find, product market fit. It probably should be a book on Kindle.

TL;DR

The Problem: 42% of startups fail because there’s no market need. Most founders don’t know if they have product-market fit or are just getting lucky with early traction.

How to Know If You Have PMF:

  • The 40% Rule: Survey active users: “How would you feel if you could no longer use [product]?” If ≥40% say “very disappointed,” you likely have PMF.
  • Leading indicators: Organic word-of-mouth, small but passionate user base, customers clearly articulating your value
  • Lagging indicators: Double-digit monthly growth ($10K-$50K MRR range), ≤3.5% monthly churn, retention curves flattening

Key Takeaways

1. PMF is measurable, not a feeling. Use the 40% rule (Sean Ellis test) as your leading indicator. If ≥40% of active users would be “very disappointed” without your product, you’re on the right track. Pair this with retention curves, organic growth, and churn rates to confirm.

2. Nail one specific pain point for one specific audience. Don’t build a horizontal product for “everyone.” Clay found PMF when they focused exclusively on GTM teams. Gamma found it serving consultants/founders/educators who need rapid content creation. Specificity beats breadth every time.

3. Expect 2+ years, not 6 months. The median B2B SaaS takes 2 years to find PMF. Clay took 5. Airtable took 3-4. This requires patient capital or low burn rates. Companies that fail usually have infrastructure costs demanding immediate adoption. Don’t scale (team, marketing, features, funding) until PMF is proven—premature scaling kills more startups than bad products.

4. Sometimes you need to completely pivot, and that’s okay. Slack started as a failed game. Segment started as analytics software. Flickr started as a game feature. If after 18-24 months you have no organic pull, customers prefer your side feature, or you’re running out of runway then pivoting might be your path to PMF. The winners aren’t those who never change course; they’re the ones who recognize when the market is telling them something and act decisively.

You’re worried about product market fit for your product

I’m assuming that if you’re reading this then you are a founder or a marketer under enormous pressure to find leads for your sales team.

You’ve built something. Customers are using it. Some even pay you. But here’s the question that keeps you up at night: do you actually have product-market fit?

According to CB Insights, 42% of failed startups cite “no market need” as their reason for shutting down. That’s not a technology problem or an execution problem, it’s a product-market fit problem. They built something nobody desperately wanted.

YCombinator’s famous motto is: Build something people want.

But as the graveyard of failed startups will testify, knowing what people want lies somewhere between witchcraft and blind luck.

This guide will show you exactly how to know if you’ve found PMF, what it looks like for B2B SaaS specifically, how long it takes, and what to do (and not do) along the way.

What Is Product-Market Fit & Why It’s Different for B2B SaaS

Product-market fit (PMF) is that elusive state where your product pulls customers toward it rather than you having to push it on them.

It’s the difference between Clay spending a jaw-dropping five years with ~20 customers and suddenly hitting 10x revenue growth.

It’s the difference between Airtable struggling to explain what they built and becoming an $11 billion company.

It’s the difference between Gamma building a tool to make beautiful presentations and a tool that gets you a presentation ready in 5-minutes.

Marc Andreessen defined product-market fit simply: “being in a good market with a product that can satisfy that market.” But that’s the poet’s version. For B2B SaaS founders, you need something more actionable.

Product-market fit means:

  • Customers actively seek out your solution without heavy marketing
  • They integrate it into their workflows and can’t imagine working without it
  • Word-of-mouth drives a significant portion of new customer acquisition
  • Retention is strong and people stick around
  • Growth feels less like pushing a boulder uphill and more like steering a rocket

B2B SaaS PMF is different from B2C. Consumer products can go viral overnight. B2B SaaS doesn’t (always) work that way. Your market is smaller, sales cycles are longer, and you’re often replacing entrenched workflows or competitors. The bar for “good enough” is much higher because your product needs to integrate into complex business processes and deliver measurable ROI.

Think about it: a consumer might download TikTok on a whim and get immediate dopamine hits. But a company switching project management tools is weeks of evaluation, stakeholder alignment, change management, risk assessment, legal reviews, security audits, and procurement (ugh).

This is why B2B SaaS PMF timelines are measured in years, not months.

The 40% Rule: A Leading Indicator You Can Measure

Sean Ellis, the growth marketer who helped scale Dropbox and LogMeIn, created one of the most actionable PMF tests: the 40% rule.

Here’s how it works. Survey users who’ve experienced your core product value (used it at least twice in the last two weeks) and ask them one simple question:

“How would you feel if you could no longer use [product]?”

Answer options:

  • Very disappointed
  • Somewhat disappointed
  • Not disappointed (it really isn’t that useful)
  • N/A – I no longer use it

According to Ellis’s research across hundreds of startups, if 40% or more of respondents answer “very disappointed,” you likely have product-market fit. Companies that cleared this threshold almost always achieved strong, sustainable growth. Those below 40% struggled.

Source: Sean Ellis PMF Survey Research

How Superhuman Used This to Reach PMF

Rahul Vohra, founder of Superhuman, turned the Sean Ellis test into Superhuman’s most important metric. In summer 2017, their score was 22%—well below the PMF threshold. They:

  1. Segmented users based on survey responses
  2. Focused exclusively on the “very disappointed” users
  3. Built features this core segment desperately wanted
  4. Ignored feature requests from users who were “not disappointed”

Within quarters, they hit 33%, then kept pushing. By systematically optimizing for the “very disappointed” percentage, they achieved strong PMF.

The brilliance of this approach? It’s a leading indicator. You don’t need to wait for revenue hockey sticks or viral growth to know if you’re on the right track. You can measure it now with 40-50 quality responses.

When the 40% Rule Misleads You

The test isn’t perfect. A few caveats:

Survey the right users. If you survey everyone who’s ever signed up (including drive-bys who never experienced your core value), your score will be artificially low. Focus on users who’ve experienced the product at least twice in the last two weeks.

Don’t obsess over one number. The 40% threshold is a guideline, not gospel. A 38% score with rapidly improving metrics might be more promising than a 42% score that’s stagnant.

Pair it with other signals. The Sean Ellis test should confirm what you’re already seeing in retention cohorts, customer feedback, and growth patterns—not replace them.

The 40% rule is 15 years old: The B2B SaaS landscape back in the 2000s and early 2010s is vastly different to what it is today. Software has commoditized every industry to the point where feature-parity is the norm for most apps. I love using customer.io and Hubspot, but would I be disappointed if I couldn’t use them tomorrow? I’d find a cheaper option.

What PMF Looks Like for B2B SaaS: It’s Not About Features

Here’s what PMF is NOT: having every feature competitors have, achieving a certain revenue milestone, or getting positive feedback from customers.

PMF for B2B SaaS is about solving a specific, recurring pain point for a well-defined customer segment and doing it so well that they can’t imagine working without you.

PMF Is Defined By:

1. Your Ideal Customer Profile (ICP)

You can’t have PMF “in general.” You have PMF with specific personas in specific situations. Clay didn’t have PMF with “everyone who works with data.” They had PMF with GTM teams and sales agencies who needed to enrich and manipulate prospect data.

Airtable’s Andrew Ofstad admits: “Before we had product-market fit, it was hard to describe the product. We’d say ‘This is a way for you to build software’ or ‘It’s a spreadsheet-database hybrid.'” They had a horizontal product that could do many things—but PMF came when they figured out who it was indispensable for: non-technical teams who needed more than Excel but databases were too complicated and cumbersome to set up.

2. The Job-to-Be-Done

Clayton Christensen’s jobs-to-be-done framework is powerful here. People don’t buy products, they “hire” them to do a job.

Customer.io wasn’t hired to “send emails.” It was hired to “re-engage users who signed up but didn’t convert” or “onboard new customers without engineering work.” That’s the actual job.

If you can’t articulate the job your ICP is hiring your product to do and why your solution is 10x better than alternatives then you probably don’t have PMF yet.

3. Pain Point Severity & Frequency

For a B2B SaaS product to be successful, it must address pain that is:

  • Acute enough that people will pay to solve it
  • Frequent enough to justify a subscription

A tax filing pain point is acute but infrequent (once yearly). That’s a tough subscription business. A competitive intelligence tool sounds good in theory, but companies tend to get far too busy with their own problems to worry or focus on what their competitors are doing until suddenly it becomes a priority – after which it dies down again.

But an email marketing pain point that product managers face weekly? Much better fit for SaaS.

NOT by features. Feature parity with competitors doesn’t equal PMF. Superhuman had fewer features than Gmail but 10x better speed. That was their wedge.

How Long Does It Take to Find PMF? Years, Not Months

Let’s talk timelines. If you’re expecting to nail PMF in 6 months, recalibrate your expectations.

The Data

Research analyzing 24 B2B startups found the median time to PMF was 2 years. Some took longer. A few got lucky earlier.

Clay: 5 years (2017-2022). Despite raising $16M from Sequoia and First Round, they had only ~20 customers paying $30-200/month before January 2022. Their positioning was too broad. Revenue grew 10x the year they finally narrowed focus to GTM teams.

Airtable: 2-3 years in private alpha before public launch. Co-founder Andrew Ofstad: “We realized it would take a long time to get a real MVP out there. You’re competing against spreadsheets that have been around for 30 years.” They saw their first enterprise customer in 2016, four years after starting in 2012.

Customer.io: 18 months to reach $10K MRR. Founder Colin Nederkoorn and his co-founder lived off savings and credit cards for years. “Growth was painfully slow, and we struggled to gain traction. Finding product-market fit was a major hurdle.”

The pattern? Patient capital and low enough burn to iterate for years. The companies that failed were those with massive infrastructure costs (Webvan, Better Place) that demanded immediate adoption they couldn’t achieve.

Sources: West Operators (Clay), First Round Review (Airtable), SaaS Club (Customer.io), Lean B2B Research

What the Journey Looks Like

The path to PMF isn’t linear. Here’s the typical progression:

Months 0-6: Building and Testing

  • Creating MVP with core hypothesis
  • Getting first users (often through founder network)
  • Learning what people actually need vs. what you thought they needed

Months 6-18: The Trough of Sorrow

  • You have users but limited traction
  • Feedback is mixed
  • Unclear if you should pivot or persevere
  • Burn rate creates anxiety

Months 18-24+: Iteration & Breakthrough

  • If you survive, you’ve probably narrowed positioning
  • Core user segment starts showing strong retention
  • Word-of-mouth begins working
  • Growth feels less forced

Not every startup survives the trough. The ones that do typically have patient investors or low burn rates that allow extended iteration.

Measuring PMF: Leading and Lagging Indicators

The 40% rule is your leading indicator, but you need lagging indicators too. These are metrics that confirm PMF after you think you have it.

Leading Indicators (Early Signals)

1. Sean Ellis Test Score ≥40%
Covered above. This is your most actionable early metric.

2. Organic Word-of-Mouth
Are customers voluntarily recommending you to peers? Not because you have a referral program, but because they genuinely want to help colleagues solve the same problem?

3. Narrow, Passionate User Base
Better to have 100 users who love you than 1,000 who are indifferent. Early PMF often looks like a small, obsessed user segment.

Lagging Indicators (Confirmations)

1. Revenue Growth: Double-Digit MoM
According to SaaS PMF research, sustained double-digit month-over-month revenue growth between $10K-$50K MRR is a strong PMF signal. You’re past the “friends and family” stage but not yet at scale where growth naturally slows.

2. Retention Curves Flattening
Your cohort retention charts should flatten after the initial drop-off. If 40% of users are still active 6 months after signup, and that curve is flattening (not continuing to drop), you likely have PMF with that segment.

3. Low Churn (For B2B SaaS)
Healthy B2B SaaS monthly churn is around 2-3.5%. If you’re seeing 5%+ monthly churn, something’s broken. People are trying your product but not sticking. If you have customers that are sticking around for longer, look for similarities between them that can help you identify you ICP, as it’s likely your PMF lies with them.

4. Sales Cycle Shortening
As PMF solidifies, sales get easier. Prospects have heard of you. They come inbound. They close faster because the problem you solve is obvious and painful.

5. NPS (Net Promoter Score) >50
While NPS alone doesn’t prove PMF, scores above 50 indicate strong customer satisfaction and willingness to recommend.

Metric Type ▲▼ Metric ▲▼ Strong PMF Benchmark ▲▼ When to Measure ▲▼
Leading Sean Ellis Test ≥40% “very disappointed” After users experience core value 2+ times
Leading Organic Word-of-Mouth 30%+ inbound from referrals Ongoing – track referral sources
Leading User Passion Intensity Small, obsessed user base Qualitative – support tickets, feature requests
Lagging MRR Growth Rate 10-20% MoM ($10K-$50K MRR) Monthly tracking once past $10K MRR
Lagging Monthly Churn Rate ≤3.5% for B2B SaaS Track by cohort monthly
Lagging Retention Curve Flatten Cohorts retain 40%+ at 6 months Quarterly cohort analysis
Lagging CAC Payback Period ≤12 months Quarterly once sales process established
Lagging Net Promoter Score >50 Quarterly surveys of active users

Sources: Sean Ellis PMF Research, Recurly SaaS Benchmarks, Vitally Churn Data

The Currency Progression Framework: From Attention to Money

One useful mental model for PMF stages is the Currency Progression Framework—what “payment” you’re able to extract from users at different stages:

1. Attention: Users will read your emails, visit your landing page
2. Time: Users will try your product, sit through a demo
3. Reputation: Users will publicly endorse you, give testimonials
4. Commitment: Users will integrate your product into their workflow
5. Money: Users will pay for your product

Framework: Currency Progression Model for PMF Stages

PMF happens somewhere between Commitment and Money. If people are willing to integrate your product into critical workflows (Commitment) and pay for it (Money), you have PMF.

If you’re stuck at “people will try it but won’t pay” or “people say nice things but don’t actually use it,” you’re pre-PMF.

Questions to Ask Yourself: The Honest Self-Assessment

PMF requires brutal honesty. Here are questions to ask yourself:

Customer Need Questions

  • Can customers clearly articulate the problem you solve? If they can’t explain why they use you, you don’t have PMF.
  • How often do they experience this problem? If it’s quarterly or annually, reconsider your subscription model.
  • What would they use if you disappeared tomorrow? If the answer is “nothing” or “we’d figure it out somehow,” the pain isn’t severe enough.
  • Would they recommend you to peers unprompted? Real PMF drives organic advocacy.

Product Questions

  • What percentage of features do most users actually use? If it’s <20%, you built the wrong things.
  • Are customers using the product the way you intended? If not, either your positioning is off or you’re solving a different problem than you thought.
  • How much of your roadmap is driven by customer requests vs. your vision? Neither extreme is great. PMF requires balance.

Business Questions

  • Is growth primarily inbound or outbound? Pre-PMF companies rely on outbound. Post-PMF companies can’t keep up with inbound.
  • Are you selling or are customers buying? There’s a difference. Selling requires convincing. Buying means they’re already convinced.
  • What’s your CAC payback period? If it takes >18 months to recover customer acquisition costs, your economics are broken.

Avoiding Cognitive Bias

Founders are notoriously bad at objectively assessing PMF because they’re emotionally invested. Here’s how to counter bias:

Talk to churned customers. They’ll tell you the truth. Current customers are too nice.

Survey “somewhat disappointed” users. These are the fence-sitters. Their feedback shows what would turn them into “very disappointed” users.

Look at usage data, not feedback. What people do matters more than what they say. Are they using it daily? Weekly? Or did they log in once and disappear?

Set a kill switch date. Decide upfront: “If we don’t hit X metric by Y date, we pivot.” Prevents endless iteration on a fundamentally broken idea.

Category PMF Signal (✓ = Yes) Pre-PMF Signal (✗ = No)
Customer Articulation ✓ Customers can clearly explain what problem you solve ✗ They struggle to explain why they use you
Pain Frequency ✓ Users experience the problem weekly or daily ✗ Problem occurs quarterly or annually
Alternative Solutions ✓ “We’d be lost without this” or switch to inferior alternative ✗ “We’d figure it out somehow” or “nothing”
Organic Advocacy ✓ Customers recommend you unprompted to peers ✗ No one talks about you unless you ask
Feature Usage ✓ Users engage with 50%+ of core features ✗ <20% feature usage, lots of unused features
Product Usage ✓ Customers use it as intended in their workflow ✗ Workarounds or using it differently than designed
Growth Source ✓ 30%+ growth from inbound/referrals ✗ Growth primarily from cold outbound
Buying vs Selling ✓ Customers come convinced, you’re closing deals ✗ Heavy convincing required, long sales cycles
Unit Economics ✓ CAC payback <12 months, LTV:CAC >3:1 ✗ CAC payback >18 months, negative margins

Framework: PMF Self-Assessment Checklist

What NOT to Do Before Finding PMF

This is critical. Most startup failure modes are doing things too early—before PMF.

Don’t Scale Your Team

As covered in our article on why B2B SaaS startups fail, premature scaling is fatal. Hiring a VP of Sales before you have a repeatable sales process just burns cash. They can’t sell a product that hasn’t found its market.

The Messenger hired 300 staff immediately and burned $50M in 8 months on only $3M revenue. They scaled before PMF and imploded.

Better scaled to 8,000 employees during the real estate boom, then had brutal, repeated layoffs when the market shifted. They’d scaled for growth that wasn’t sustainable.

Wait until you have 20-50 customers closed by founders through a process you can articulate. Only then hire your first sales rep.

Don’t Spend Heavily on Marketing

Paid acquisition before PMF is throwing money into a leaky bucket. If retention is weak because PMF isn’t there, more users just means more churn.

Invest in content that educates your market (like Customer.io did with conversion copywriting resources), not performance marketing trying to force growth.

Don’t Build Too Many Features

Feature bloat is a PMF killer. Airtable knew their MVP bar was high—competing with spreadsheets with 30 years of features—but they didn’t try to match every feature. They built the minimum that delivered their core value proposition and expanded from there.

If you’re below 40% on the Sean Ellis test, more features won’t save you. Better positioning and deeper value for your core segment will.

Don’t Raise Too Much Money

Counterintuitive, but massive funding pre-PMF creates pressure to scale before you’re ready. You’ll hire too fast, spend too much, and run out of runway before finding PMF.

Customer.io’s Colin Nederkoorn took a non-traditional approach to fundraising: “We view funding as a tool to get to the next stage of the business.” They raised only what they needed when they needed it, maintaining control and optionality.

How to Accelerate Your PMF Journey (Without Shortcuts)

You can’t skip the work, but you can avoid common detours.

1. Talk to 40-100 Customers Before Building

Customer development isn’t optional. Clay, Airtable, Customer.io—all of them spent months (in some cases years) in customer conversations before scaling.

Don’t just ask “Would you use this?” Ask:

  • “How do you solve this problem today?”
  • “What have you tried that didn’t work?”
  • “If this worked perfectly, what would change for you?”
  • “What would make this a must-have vs. nice-to-have?”

2. Focus on One ICP Segment First

Horizontal products (like Airtable) took years to find PMF precisely because they tried to serve everyone. Clay’s breakthrough came when they focused exclusively on GTM teams. Revenue grew 10x that year.

Pick your most enthusiastic user segment and make the product incredible for them. Expand later.

3. Ship Fast, Iterate Faster

Airtable spent years in private alpha iterating with early users. They built prototypes, tested with users, got feedback, and repeated. Every. Single. Day.

Don’t wait for perfection. Get something in users’ hands and learn.

4. Use Quantitative + Qualitative Data

The Sean Ellis test (qualitative) should align with retention metrics (quantitative). If they don’t, dig deeper. Maybe your happiest users aren’t representative, or maybe your metrics are misleading.

Knowing If You’re Losing PMF (The Drift)

PMF isn’t permanent. Markets evolve. Competitors emerge. You can drift out of fit.

Warning Signs

Retention curves trending downward. New cohorts should retain as well as or better than old cohorts. If retention is declining, something shifted.

Increasing CAC without corresponding LTV increase. If it’s getting more expensive to acquire customers but they’re not worth more, your economics are deteriorating.

Customers using fewer features over time. Healthy products see increasing feature adoption as users mature. Declining feature usage signals disengagement.

Competitors mentioned more in churn surveys. If “we switched to [competitor]” becomes a common churn reason, you’re being outmaneuvered.

Longer sales cycles despite more resources. If you’ve hired sales reps and ramped up marketing but deals take longer to close, the market is telling you something.

Budgets are being allocated elsewhere. If your renewals are struggling because the clients don’t have the budget for your solution then you could be losing PMF as the team isn’t able to build a strong business case why they should keep your product – or continue paying the price you’re charging.

When to Embrace Feature Creep vs. Constrain It

This is nuanced. Some feature expansion is healthy and helps deepen the value for your core ICP. Some is poison, and dilutes your positioning by trying to serve everyone.

This is a really tricky one to navigate. At Unmetric we were focused exclusively on social media benchmarking and competitive analytics. As social media became less about great content and more about paid ads, budgets for social got reallocated from organic content to performance content. They cared less about what their competitors were doing organically and more on what ROI they were getting from their ads.

Unmetric could have built out features to start tracking ads and ad spend, but it would be a big pivot away from our core offering. In the end Unmetric was acquired to become a ‘feature’ of a larger social media publishing tool.

Embrace expansion when:

  • Customers with highest retention request it
  • It deepens the moat for your core use case
  • It’s logical progression of the job-to-be-done

Constrain expansion when:

  • It’s chasing a different ICP or use case
  • Your “very disappointed” users don’t care about it
  • It’s defensive (building features just because competitors have them)

Superhuman’s Rahul Vohra had a clear framework: only build features that increase the “very disappointed” percentage. If a feature request came from “not disappointed” users, it was a no.

Real Examples: Companies That Found PMF

Let’s look at how actual B2B SaaS companies found PMF, with links to founder interviews.

Clay: 5-Year Grind to Overnight Success

West Operators article on Clay’s evolution

Timeline: 2017-2022 (5 years)
The Struggle: Despite $16M from top VCs, only ~20 customers paying $30-200/month by January 2022. Positioning was too broad: “Build tools & workflows to supercharge your team.” Could be applied to literally anyone. No one knew what it meant.
The Breakthrough: Focused exclusively on GTM teams and sales agencies. Revenue grew 10x in a year.
Lesson: Even with great investors and a working product, finding the right positioning takes years.

Airtable: Years Competing with 30-Year-Old Spreadsheets

First Round Review: Airtable’s Path to PMF

Timeline: Started 2012, first enterprise customer 2016
The Struggle: “Before we had product-market fit, it was hard to describe the product.” Horizontal products that can do many things struggle with positioning.
The Breakthrough: Templates, use case clarity, and time. By 2016, they saw the product spreading “team to team” organically.
Lesson: High-quality horizontal products take even longer. Their MVP bar was incredibly high: competing with Excel.

Customer.io: 18 Months to $10K MRR, Then 10 Years to $70M

SaaS Club podcast with Colin Nederkoorn

Timeline: 18 months to $10K MRR, now $70M ARR
The Struggle: “Growth was painfully slow. We lived off savings and credit cards for years.” Struggled with positioning and messaging.
The Breakthrough: Content marketing. Colin learned conversion copywriting and educated his audience, building credibility before officially launching.
Lesson: Sometimes PMF comes from nailing go-to-market, not just product.

Gamma: The “First 30 Seconds” Strategy That Unlocked Viral Growth

PMF Show with Jon Noronha | Lenny’s Podcast with Grant Lee

Timeline: 3 years of building (2020-2023), then systematic 4-month rebuild, explosive growth March 2023

BEFORE: The PMF Problem (Pre-AI, 2020-2023)

Who they targeted: Design-forward professionals who wanted to create “beautiful presentations” but found PowerPoint limiting. Essentially trying to be “Canva for presentations.”

The pain they solved: Making presentations look modern and visually appealing without design skills.

Why it didn’t have PMF:

  • The problem wasn’t painful enough. PowerPoint is “good enough” for most people.
  • Their solution required too much work. Users still had to understand layouts, choose templates, drag-and-drop elements.
  • The product felt like “a toy, not real work.”
  • Won Product Hunt’s Product of the Day, Week, AND Month, but signups flatlined after the spike. No organic growth.
  • After 3 years: “just a few hundred users after burning millions.”

AFTER: The True PMF (Post-AI, March 2023+)

Who they target: Individual knowledge workers who need to create professional content rapidly without design expertise: founders creating pitch decks, consultants building client proposals, educators developing lesson plans, marketers making sales presentations, freelancers building portfolios.

The pain they solve: “I have messy ideas/notes/content and need a polished, professional presentation in minutes, not hours.”

Why THIS has PMF:

  • The pain is acute and frequent. Consultants create client decks weekly. Founders pitch constantly. Educators prepare lessons daily. This isn’t a “nice improvement” on an existing solution, it’s saving them 2-3 hours every time.
  • The alternative is terrible. 80% of users discovered Gamma from a friend or social media because they saw someone transform messy ideas into a polished deck in 30 seconds and thought “I need that.”
  • They deliberately DON’T target designers. Unlike Figma, Gamma expands market by not competing for design professionals. They’re for people who CAN’T or DON’T WANT TO design.
  • The job-to-be-done is clear. Not “make beautiful presentations” (vague). It’s “turn my rough content into client-ready materials in minutes” (specific, measurable, urgent).

The Specific ICP Who Love It:

  • Founders & marketers creating pitch decks and proposals quickly
  • Educators & trainers developing clean, engaging lesson materials
  • Consultants building client deliverables under time pressure
  • Remote teams needing web-based collaboration
  • Non-designers who want professional output without the learning curve

Who it’s NOT for (and Gamma knows it):

  • Data analysts needing complex, precise visualizations
  • Corporate teams locked into strict branding guidelines
  • Designers seeking pixel-perfect control
  • Teams requiring offline PowerPoint workflows

The Systematic Rebuild (Not Luck):

In early 2023 with only 12 months of runway left, CEO Grant Lee set a brutally simple rule: “The first 30 seconds in Gamma had to feel like a superpower.”

They gave themselves a 4-month sprint to completely rebuild the onboarding experience around AI. The team:

  1. Flattened the learning curve dramatically. The old version required users to “do so much work to just even comprehend what we were doing.” The new version: paste messy content or write a short prompt, watch Gamma turn it into a clean, structured presentation in 10 seconds.
  2. Made the “aha moment” instant. Within 30 seconds of signing up, you’ve already experienced Gamma’s magic. Most users click “Generate,” write 10-15 words, and watch AI create each element of their presentation live. They didn’t need time to slowly understand—they saw value immediately.
  3. Built experimentation into everything. Coming from Optimizely, the team runs experiments on 20-25 AI models simultaneously. They test different models, prompt strategies, layout patterns, diagram styles. For example, testing Claude 3 Haiku against their existing setup showed a 30% increase in user satisfaction, translating to 20% lift in free-to-paid conversion.
  4. Invested heavily in design taste. One-third of Gamma’s team are designers. The product wasn’t just fast, it was beautiful. Good design created delight and delight created sharing.

The Launch (March 2023):

Before AI: 8 months to reach 60,000 signups total
After AI: Less than one week to add the next 60,000 signups

They went from 2,000 → 5,000 → 10,000 → 20,000 signups per day. Organic growth picked up, word-of-mouth took off, retention curves looked healthier.

The Viral Moment (It Wasn’t Just Luck):

Yes, founder Grant Lee posted a provocative tweet and Paul Graham’s reply went viral (2,000 → 60,000 signups/day). But here’s what people miss: the viral traffic stuck because the product delivered on the promise.

The traffic spike was so massive their servers crashed for three days. But when they came back online, the surge continued. Users who’d experienced the ‘first 30 seconds magic’ were desperate to get back in. That wasn’t dumb luck. That was a product finally delivering on its promise.

Sure, the viral tweet was the accelerant but the fuel was the rebuilt onboarding that made every new user want to share.

After the Viral Moment (The Real Work):

Most startups would have immediately scaled marketing spend and hiring. Gamma did the opposite. Instead of “growth at any cost,” they tightened fundamentals:

  • Improved activation rates
  • Smoothed first-run experience
  • Strengthened retention curves
  • Made shareability frictionless

Only when data showed sustained pull did they layer on growth tactics:

Micro-Influencer Strategy: Grant personally onboarded early creators 1:1, teaching them to explain Gamma in their own voice. Focused on thousands of niche creators (educators, productivity experts) instead of celebrity mega-creators. LinkedIn converted 4-5x better than other platforms.

Product-Led Virality: Every Gamma created includes a “Made with Gamma” watermark. Collaboration features drive team expansion. The product itself became the growth loop.

Results:

Lesson: The Paul Graham tweet created a spike. But PMF came from systematically perfecting the first 30 seconds until the product was so delightful people couldn’t help but share it. Awards and press don’t equal PMF. Real PMF feels like “pull” not “push.” You know you have it when organic growth sustains itself without constant marketing.

Fast: What Happens When You Scale Without PMF

Timeline: Shut down April 2022 after ~2 years
The Problem: Burned $10M/month on only ~$600K annual revenue (200:1 ratio). Hired 400 employees before the product worked reliably.
Lesson: All the money and marketing in the world can’t fix a broken product-market fit. Fast had neither a working product nor real market demand.

When to Pivot: B2B SaaS Companies That Found PMF After Complete Reinvention

Sometimes the path to PMF requires abandoning your original vision entirely. These companies started building one thing, realized the market didn’t want it, and pivoted to something completely different, often keeping only their team or a small technical component.

Slack: From Failed Game to $27.7B Acquisition

Stewart Butterfield might be the king of pivots. His company Tiny Speck spent years building an online game called Glitch. The game launched in 2011, returned to beta, and by 2012, Butterfield declared it wasn’t viable.

But the internal communication tool they’d built to coordinate between US and Canadian offices? That was special.

Slack officially launched in 2014 and became a unicorn the same year. Four years later: 8 million daily active users, $7B+ valuation. 2021: Salesforce acquired Slack for $27.7 billion.

The pivot wasn’t obvious. Butterfield had to convince his team to shut down the game they’d spent years building. He conducted internal votes. The first vote went to continue the game. He campaigned harder. The second vote narrowly went to Slack. That democratic process was critical because he team had to feel bought in, even if it “wasn’t completely democratic.”

Lesson: Sometimes the side project you built to solve your own problem is the real product. Pay attention to what users actually love, not what you wish they loved.

Segment: Analytics Product Failed, Data Pipeline Thrived

Segment started trying to build a competitor for Google Analytics. To enable that, they built an SDK that could stream data to multiple destinations. Customers loved the SDK. Nobody used the analytics backend.

The product they’d intended to build failed. But they’d accidentally built something valuable: a customer data platform that became the infrastructure layer for thousands of companies.

That’s a true pivot because they kept the core technology (the SDK) but completely changed the value proposition, customer base, and go-to-market.

Flickr: From Game Feature to Photo Revolution

Before Slack, Stewart Butterfield co-founded Ludicorp, which developed another online game called Game Neverending. Embedded in that game was a photo-sharing feature called Flickr.

When they realized the limited financial potential of the game, they shut down Game Neverending and focused entirely on Flickr. It became one of the best photo-sharing platforms in the early 2000s.

Butterfield literally did this twice. Turned dying games into revolutionary communication platforms. Third time’s a charm?

The Difference Between Pivoting and Traveling

Not all pivots are created equal. SkyFlow CEO Anshu Sharma distinguishes between true “pivots” and what he calls “traveling”:

Traveling (Slack, Flickr): Completely new company. Nothing in common—different product, different customers, different GTM. You’re essentially shutting down one company and starting another.

True Pivot (Segment): Same core technology, but different value proposition or target market. You’re evolving, not reinventing.

Most successful “pivot” stories are actually traveling. And that’s fine—but understand the difference. Traveling requires more courage because you’re throwing away more.

When Should You Pivot?

Pivoting is brutal. You’re admitting your original vision was wrong. Your team might fracture. Sunk cost fallacy screams at you to keep going.

But here are signals it’s time to consider a complete pivot:

No organic pull after 18-24 months. If you’ve been building for two years and still relying entirely on outbound to get customers, the market might be telling you something.

Customers love a side feature more than the core product. Pay attention to usage data. If people are “misusing” your product in consistent ways, they’re showing you what they actually want.

Funding runway is short and growth is flat. If you have <12 months of runway and no path to breakout growth, a pivot might be your only option besides shutting down.

A massive market shift creates new opportunity. Gamma languished for 3 years, then ChatGPT dropped and they pivoted to AI-powered presentations. That timing was everything.

The hardest part? Distinguishing between “we haven’t found PMF yet” and “we’re building the wrong thing.” Clay took 5 years to find PMF but never fully pivoted—they just narrowed positioning. Gamma spent 3 years then completely pivoted to AI.

There’s no formula. But if you’re asking yourself “should we pivot,” you’re probably already 6 months late on making that decision.

Books & Resources for Going Deeper

Want to dive deeper into PMF? Here are the essential resources:

Books

Lean B2B: Build Products Businesses Want by Étienne Garbugli
The definitive guide to B2B customer development and PMF. Step-by-step process from idea to validated business model. Essential for B2B founders.

The Lean Product Playbook by Dan Olsen
Actionable framework for iterating to PMF. More software-product focused, great for established companies launching new products.

The Mom Test by Rob Fitzpatrick
How to talk to customers so they tell you the truth about whether your product sucks. Essential for customer development interviews.

Crossing the Chasm by Geoffrey Moore
Classic on moving from early adopters to mainstream market. Especially relevant for B2B SaaS selling to enterprises.

Communities & Forums

Indie Hackers – Founders sharing revenue, growth tactics, and PMF journeys in public
SaaS Club Community – Focused specifically on B2B SaaS growth and metrics
Lenny’s Newsletter Community – Product-focused, many PMF discussions
r/SaaS on Reddit – Active community of SaaS founders

Moving Forward: PMF Is a Milestone, Not a Destination

Here’s what to remember about product-market fit:

It takes longer than you think. Median is 2 years for B2B SaaS. Clay took 5. Airtable took 3-4. Don’t get discouraged at month 6.

It’s specific, not general. You don’t have PMF with “small businesses.” You have PMF with “sales agencies with 5-20 people who need to enrich prospect data daily.”

It’s measurable. The 40% rule gives you a concrete benchmark. Survey your most engaged users. If ≥40% would be very disappointed without you, you’re probably there.

It’s not permanent. Markets evolve. Stay paranoid. Keep measuring. Keep talking to customers.

Don’t scale before you have it. Hiring, marketing spend, fundraising—all should wait until PMF is clear. Premature scaling kills more startups than anything else.

Most importantly: PMF is the prerequisite for everything else. Until you have it, nothing else matters. Not your growth strategy, not your competitive moat, not your brand. Get PMF first. Then scale.

Now go survey your users. Ask them how disappointed they’d be if your product disappeared. If the answer is “very” from ≥40%, congratulations then you’ve found something rare. If not, you know exactly what to work on.

Oh, and if you made it this far…

Well done 🤗

5 reasons why (your) B2B SaaS startups fail

You’ve poured your heart into building a B2B SaaS product. The early customers love it. Your team believes in the vision. You’ve even raised some funding. You also know the unfortable truth that approximately 90% of SaaS startups fail, and 42% shut down because there’s simply no market need for what they’ve built, but that’s not going to happen to your startup, right?

Those of a delicate disposition might wish to stop reading and close the tab.

This article is not supposed to be a negative, bearish take on startups. It’s a cautionary tale of what to look out for on your journey to unicorn status.

Take, for example, Quibi, which managed to burn through an astonishing $1.75 billion before shutting down after just six months. Color Labs couldn’t survive despite a $41 million investment. Fast could only make $600k revenue from $124.5m invested.

Or, you could just be really unlucky (complacent?) like CloudNordic which was hit by a ransomware attack in 2023 that destroyed all customer data, forcing closure.

The scale is staggering.

In 2024 alone, 966 U.S. startups shut down—a 25.6% increase from 2023. These companies took an estimated $6-$8 billion of VC money with them to the grave. AngelList saw 364 winddowns in 2024, up from 233 in 2023. Each number represents visionary founders, inspired teams, and googly-eyed investors who lost everything.

Time PeriodFailure RateSurvival Rate
After Year 121.5%78.5%
After Year 2~30%~70%
After Year 548.4%51.6%
SaaS-Specific (3 years)92%8%

Sources: U.S. Bureau of Labor Statistics, LinkedIn Research

Let’s dive into what really kills B2B SaaS companies, backed by data from real failures.

Source: CB Insights startup failure analysis

1. The Misaligned Problem: Wrong Pain, Wrong Frequency, Wrong Timing

Product-market fit isn’t binary, it exists on a spectrum. For B2B SaaS, you need a pain point that’s both acute and recurring. But there’s a third dimension that kills startups just as often: timing.

The Pain Frequency Problem

Your solution must address pain that recurs frequently enough to justify subscription revenue. A business might need tax filing once yearly and that’s real pain, but not frequent enough for $99/month SaaS.

Eventloot, a wedding planning SaaS, built a platform that didn’t actually solve wedding planner problems. Delite, a B2B wholesale platform, didn’t satisfy any urgent customer necessity. RateMySpeech invested heavily in a product appealing to only 5% of their target market.

If customers only feel the pain quarterly or annually, you’re building a product business, not a subscription business, and different economics apply.

The Timing Trap: Too Early or Too Late

Market timing can make or break B2B SaaS. Be too early, and you’ll burn through capital educating a market that isn’t ready. Be too late, and you’re fighting established players.

Too Early = Death by Education Costs

When a category doesn’t exist yet for your product, educating your market why they should use your product risks burning through your runway before they are ready to use your product. The failed startup graveyard is littered with category creating products that were way ahead of their time, and, consequently, ahead of what the market wanted.

Webvan pioneered online grocery delivery in 1996, raising $800 million. They promised 30-minute delivery windows a decade before the infrastructure existed. They burned $1.2 billion convincing people to buy groceries online when most barely trusted e-commerce. They collapsed in 2001. Twenty years later, Instacart executed the same model successfully.

Better Place raised substantial funding for EV battery-swapping technology but failed in 2013, years ahead of market readiness. Tesla proved the market existed, but only after building it slowly over a decade.

Thought Machine launched Vault, a cloud-native core banking platform, in the mid-2010s designed to replace legacy banking systems. The product was technically brilliant, but traditional banks weren’t ready to make that leap. The cultural and regulatory readiness simply wasn’t there yet.

Babylon Health faced similar resistance with its AI-driven healthcare solutions. The idea of AI handling medical consultations made healthcare providers and patients uncomfortable – it was simply too far ahead of current practices.

Unless you have OpenAI levels of funding, endeavour to not be a building a category-creating product. I guarantee it’ll end up as an example on this list.

Absence of competition is a red flag, not a signal.

The Multi-Year Grind to PMF

OK, but on the flip side, there are companies that survive long enough for the market to catch up. Clay took five years (2017-2022) to find product-market fit. Despite raising $16M from Sequoia and First Round, they had only ~20 customers paying $30-$200/month before January 2022. Their message was so broad it resonated with nobody.

The breakthrough came when they focused exclusively on GTM teams. Revenue grew 10x that year. But it required five years of iteration.

Airtable faced similar struggles. Co-founder Andrew Ofstad admits: “Before we had product-market fit, it was hard to describe the product.” They struggled to articulate value until customers finally understood. (Sidenote: I’m still not sure who Airtable is catering to. Suggestions in the comments, please!).

The difference? Clay and Airtable had patient capital and low burn. Webvan and Better Place had massive infrastructure costs demanding immediate adoption.

When the Market Moves On

Sometimes the timing problem isn’t being too early or too late, it’s being unable to adapt as the market evolves beneath you. Your product had a moment, but consumer behaviour shifted, competitors executed better, or the entire category moved in a different direction.

Yammer, the enterprise social network Microsoft acquired for $1.2 billion in 2012, seemed poised to dominate corporate communications. I remember using Yammer back in 2012 and thought it was great having an internal social network for the company. When someone suggested we look at Slack I took a look and declared that we already had chat in the Google Workspace, why would we need another chat tool. (Needless to say, I’ve since changed my tone on Slack!).

When Microsoft launched Teams in 2016 as a direct competitor to Slack, it had better integration and a more modern approach, making Yammer irrelevant. By 2023, Microsoft killed the Yammer brand entirely, absorbing it into Viva Engage. The market didn’t disappear, it just moved to a better execution.

Evernote pioneered digital note-taking and reached 150 million users by 2015, with 9.6 million yearly downloads in 2017. Then came Notion, offering databases and customization. By 2023, Evernote’s downloads had plummeted 82% to just 1.7 million. The market wanted connected workspaces, not just note storage. Evernote couldn’t pivot fast enough.

Hootsuite tells perhaps the most complete story of a market that moved on. Founded in 2008, Hootsuite pioneered social media management when brands were racing to build organic social presence. At its peak, the company had 1,400+ employees and was planning a $200 million IPO.

But the market fundamentally shifted: brands moved from creating organic social content to running paid ads, dramatically reducing their need for scheduling and publishing tools. Simultaneously, their entire product became a checkbox feature in platforms like HubSpot and what was once a standalone business got commoditized into marketing automation suites.

The result has been brutal with repeated layoffs: 30% of staff in August 2022 (400 people), another 5% in November 2022, 70 more in January 2023, and another 20% (hundreds more) in October 2025. They postponed their IPO indefinitely. The market didn’t disappear, brands still post on social media, it just stopped needing a dedicated tool for something that became a feature.

The pattern repeats: Box and Dropbox pioneered file sync but were commoditized when Google Drive and OneDrive bundled it for free. Google Docs eliminated the need for file syncing entirely. Basecamp created project management but watched Asana, Monday.com, and ClickUp capture the market with modern interfaces and deeper features.

These weren’t bad products that failed to find PMF. They had product-market fit. The problem? The market evolved, and they didn’t evolve with it fast enough. Either their product roadmap couldn’t keep pace, their architecture made pivoting too expensive, or they were simply outmaneuvered by more agile competitors.

The difficult truth: Even when you nail product-market fit, you’re racing against time before someone builds something better or the market shifts. The companies that survive aren’t just the ones that find PMF, they’re the ones that can continuously re-find it as the market moves.

2. The Platform Dependency Trap: When Your Foundation Crumbles

Building your business on someone else’s platform means accepting existential risk. Social media analytics destroyed by API restrictions. Scheduling apps killed by policy changes. Integration tools that became worthless overnight.

The Twitter API Massacre

In 2023, Twitter increased API pricing from free to as much as $42,000 per month. For analytics platforms built on Twitter data, this was an extinction level event.

I’ve spoken with founders of social media analytics companies entirely dependent on platform APIs. When networks became restrictive about data, their ability to deliver insights evaporated. Customers churned because the product couldn’t provide promised value. The ground simply disappeared beneath their feet.

Apollo calculated that Reddit’s API pricing would cost them $1.7 million monthly. The app shut down. PostMyParty saw seven years of work jeopardized when Meta shut down API access, affecting 10,000+ customers.

CartHook, a Shopify app for post-purchase upsells, thrived until Shopify restricted their core functionality. They had to pivot completely and rebuild from scratch, rendering years of work worthless.

Perhaps the most infamous example of platform dependency is Zynga. The gaming company behind FarmVille reached 60 million daily users and made up 19% of Facebook’s revenue in 2011. Their IPO filing acknowledged their “potentially fatal flaw”: a complete dependence on Facebook’s platform. When Facebook ended their special relationship in 2012 and changed payment policies to take a larger revenue cut, Zynga’s fate was sealed. The company survived only because they eventually diversified, but it cost them years and billions in market value.

The False Security of Platforms

Early on, platforms love third-party developers. They talk about “ecosystems” and “partnerships.” But platforms embrace developers until those developers become competitive threats.

How to Reduce Platform Risk:

  • Diversify data sources. Don’t rely on one platform
  • Own your customer relationships directly
  • Build proprietary value beyond the underlying data
  • Have contingency plans if your primary API disappears

Platform risk is often unavoidable early on and in many instances is a smart move as you gain a network effect by building for an existing, captive market. But understand that every API call is a potential single point of failure for your business.

3. The Money Problem: When Unit Economics Don’t Work

According to CB Insights, 38% of startups fail because they run out of cash. But “running out of cash” is really a symptom: failure to find a market that needs your product so badly that they are willing to pay for it, poor unit economics, unsustainable customer acquisition costs, and broken pricing.

The Customer Acquisition Cost Death Spiral

Your customer lifetime value (CLV) must significantly exceed your customer acquisition cost (CAC). Ideally 3:1 or better. Many startups discover too late their CAC is simply too high.

An enterprise SaaS might spend $15,000 to acquire a customer paying $500/month. That’s 30 months to break even. But at 3% monthly churn, average customer lifetime is 33 months. You’re barely breaking even on acquisition, let alone covering operational expenses.

The Churn Rate Reality

Churn silently kills SaaS businesses. It’s possibly the most important metric that a SaaS company can track. According to 2025 Recurly research, median monthly churn is 3.5%. For smaller startups, rates can hit 5-10% monthly.

Source: Recurly 2025 Churn Report, Cobloom Research

At 5% monthly churn, you’re replacing your entire customer base every 20 months. That might feel like you’re building a business, but you’re actually filling a leaky bucket. This is why so many SaaS companies hit the $20-$30m glass ceiling and fail to grow from there. They can bring in new customers every month but even at modest churn rates they are simply replacing the revenue that they’re losing.

The Everpix Cautionary Tale

Everpix had a beautiful product users loved, raising $2.3 million from respected investors. But they had negative gross margins, which meant they were spending more to acquire and serve customers than those customers would ever pay.

When it came time to pay Amazon Web Services, Everpix ran out of cash and shut down in 2013. Their P&L: $566,000 in legal costs, $360,000 in operations, $1.4 million in salaries for seven employees—against only $254,000 in revenue. The math didn’t work.

Successful SaaS startups obsess over unit economics. They know their CAC by channel, track cohort retention religiously, and understand exactly when they’ll achieve profitability. Failed ones discover their economics are broken when it’s too late.

As with every SaaS failure, there are exceptions to the rule. Uber lost an eye-watering sum of money acquiring customers and only in the last few years has been able to break event. Most AI companies, OpenAI, Anthropic, xAI, etc. are burning through literally billions of dollars to be the last app standing and grab the winner takes all prize.

Most apps don’t have tens of billions of dollars to spend to win a category.

The Fast way to spend $124.5m of VC money

Fast was aiming to take on Shopify with its one-click checkout. It raised $124.5m to take on this challenge, but the unit economics had a galaxy-sized hole in them. They were spending $10m per month on an annual revenue of $600k. By comparison, Bolt, one of their competitors, was doing $40m revenue a year in the same period.

4. The Technical Reality Gap: When Reliability Doesn’t Match Marketing

B2B SaaS startups fail when they promise what their technology can’t deliver. Like Elon Musk, but without the army of fanboys. The sales pitch is compelling, demos polished, but the software just doesn’t work. This gap creates trust problems that are hard to recover from.

When Technical Debt Becomes Bankruptcy

According to a 2024 survey, 80% of leaders reported technical debt caused delays and higher costs. For startups, these delays are fatal.

Sources: Morning Consult/Unqork Survey 2024, Virtusa Research

Zeus Living is a perfect example. The furnished housing rental startup exploded during the pandemic when remote work surged. They invested heavily in 2021 to “get more homes.” But when interest rates spiked post-pandemic, their infrastructure couldn’t adapt. The company couldn’t pivot its technical architecture or business model fast enough.

Rubica, a cybersecurity SaaS, had the right product at the right time. But when COVID-19 hit, their target customers cut spending dramatically. They couldn’t adapt their go-to-market strategy fast enough. The irony is that if they had survived to today, cybersecurity is one of the fastest growing industries in SaaS right now.

Fast, which I talked about earlier, also talked a good talk, but merchants found it hard to integrate, their customers found the checkout button buggy, and the product didn’t live up to the marketing hype the company had whipped up.

Building Reliability While Moving Fast

Successful startups invest in monitoring from day one, practice defensive coding with automated testing, plan for scale even when small, and are honest with customers about capabilities.

A stark recent example is 11x.ai, an AI SDR platform that raised $74 million from top VCs like Andreessen Horowitz and Benchmark. The technology promised to replace human sales development reps with AI agents. But the company experienced 70-80% churn rates because the product simply didn’t deliver on its slick marketing promise.

ZoomInfo reported the AI “performed significantly worse than our SDR employees.” One customer used it for six months and booked zero meetings. The technology couldn’t match the marketing promise, leading to massive customer churn and eventual scandal.

Allegedly 11x was able to show sales traction by signing on clients with generous money back guarantees locked into the contract – and many companies activated that money back guarantee. However (allegedly) 11x was less than diligent with their book keeping to say that the customer had churned and money had been returned.

The fastest way to kill a SaaS startup isn’t slow development, it’s building something that doesn’t work as advertised. In B2B sales, trust is everything.

5. The Team Problem: When Human Issues Sink the Ship

Technology problems can be fixed. Product problems can be pivoted. But team problems? Often terminal. According to CB Insights, 23% of startups fail due to not having the right team.

Co-Founder Conflict

You started with shared vision. But as the company grows, cracks appear. Disagreements on direction, complementary skills becoming conflict, unequal weight pulling. Co-founder conflict contributes significantly to failures. This conflict bleeds into the organization. Teams pick sides. Decision-making halts. Best employees leave.

The Hiring Mistakes

Zirtual, a virtual assistant marketplace, is a cautionary tale. High burn rate and management issues brought the firm to bankruptcy. Despite customers who loved the service, internal dysfunction destroyed the business.

Freshconnect failed after mistakes with team focus and bad hiring. Co-founder Tarun couldn’t secure additional funding. Not because the market didn’t exist, but because the team couldn’t execute. The company was acqui-hired, with most of the original team laid off.

The Acquihire Reality

Let’s talk about what actually happens when B2B SaaS startups fail. Media reports “acquisitions” and “acqui-hires” as success stories. But the reality for most team members is brutal.

In typical acquihires, the acquiring company buys talent, not your product. The sales and engineering team are often kept on, everyone else is dead weight. Marketers are usually the first casualty of any cost cutting. The company cherry-picks who they want, usually founders, key engineers, and the top performing sales people. Everyone else? Laid off.

In 2024-2025, we saw “reverse acquihires” where tech giants poached entire teams from AI startups without buying companies. Character AI had Google license their technology for $2.7 billion and hire their co-founders, leaving the rest to fend for themselves. Adept, once valued at $1 billion, saw Amazon hire key staff while the company struggled.

I’ve even heard stories of startups being ‘acquired’ only for it to be an IP acquisition, not a company acquisition. The tenured staff with vested stock options get nothing because the company hasn’t been acquired, only the technology and IP. Absolutely brutal stuff.

These aren’t success stories. They’re soft landings for founders while everyone else faces unemployment.

The Fatal Mistake: Scaling Before PMF

This is the most seductive trap: you raise Series A, and everyone expects you to “act like a real company.” So you hire aggressively. VP of Sales from Oracle. Growth Marketing guru from the billion dollar SaaS brand. Sales development team. You go from 5 to 25 people in six months.

One problem: you haven’t found product-market fit yet.

No sales talent can fix a product nobody wants. No growth marketing can create demand where none exists. When you scale before nailing product and go-to-market, you’re pouring gasoline on an unlit fire.

Better scaled to 8,000 employees during the 2020-2021 real estate boom. When interest rates rose, they faced brutal layoffs. The CEO fired 900 employees over Zoom in 2021, then continued cuts through 2024.

The Messenger launched in May 2023 with 300+ staff and imploded in 8 months. They burned $50 million while generating only $3 million in revenue. By January 2024, they shut down completely, letting all 300 staff go with zero severance.

Moxion Power raised $100 million Series B in 2022 to scale manufacturing. By July 2024, they suddenly furloughed all 400 employees. By August, they filed for Chapter 7 with $100-500 million in liabilities. They grew too quickly before resolving technical issues or achieving sustainable sales.

Fast added 400 staff members, paid eye-watering sums of money to celebrities, and spent lavishly on offices and perks, all before they had a product that the market wanted. They closed down having taken $124.5m of VC money, and made just $600k a year. For every $200 they spent, they managed to turn that into just $1.

The 2020-2021 Funding Aftermath

The premature scaling epidemic worsened because of 2020-2021. Many startups received seed funding “probably before they were ready”. Rapid capital encouraged high burn rates and “growth-at-all-costs mentalities.”

The result? In 2024, 966 startups shut down, up 25.6% from 2023. More than 95,000 U.S. tech workers were laid off in 2024 alone.

Most weren’t companies with bad products. They failed because they scaled too fast, hired too many people, and burned through capital before proving their business models.

If you’re going to build a sales organization, here’s the only sequence that works:

The right sequence:

  1. Founders sell until 20-50 deals (repeatable process)
  2. Hire first sales rep to validate it can be taught
  3. Only after that rep succeeds, hire sales leader
  4. Scale gradually as each stage proves out

Skip steps, and you’re pouring money into a team that can’t succeed because the fundamentals aren’t proven yet.

Moving Forward: What Sets Survivors Apart

If 90% of SaaS startups fail, what makes the 10% different?

They validated pain frequency before scaling. They diversified away from platform risk. They obsessed over unit economics. They built reliability into their DNA. They got the people right.

What you can do right now:

Validate pain frequency. Talk to 20 potential customers. Ask how often they experience your problem. If “occasionally” or “quarterly,” rethink your model.

Be prepared to take the most difficult decisions of your life if you discover that the need your product is addressing doesn’t have a market or a recurring frequency, like Ishita Arora did when she shut down her startup, DaySlice and returned what was left of the investor money.

Toni Hohlbein took the impossible decision to shutdown GrowBlocks when it became apparent that SaaS companies didn’t have the hair-on-fire pain when it came to revenue operations. Sales leaders couldn’t explain the value to the CFO of paying $30k for a dashboard that helped visualize their sales operations.

Assess platform risk. List every external dependency. What happens if each disappears tomorrow? If “game over,” start diversifying.

Know your numbers. Calculate actual CAC by channel, churn rate by cohort, and CLV. If the math doesn’t work now, it won’t at 10x scale.

Audit technical debt. Be honest about corners cut. Pay down debt before it compounds.

Evaluate your team. Are the right people aligned on the mission? Are you creating an environment for their best work?

Don’t be dismissive of new trends. The market you have product-market fit in today might shift tomorrow. Someone with better UX, modern tech stack, or smarter positioning can render you obsolete. Build a culture of continuous improvement and customer obsession. Talk to users weekly. Watch competitors monthly.

Ask yourself quarterly: “If we were starting today, would we still build it this way?” If the answer is no, start evolving before a more agile competitor forces you to.

The B2B SaaS market is brutal. Immense competition, high expectations, razor-thin margins for error. But understanding why companies fail is the first step to being one that succeeds.

Your startup might face all five challenges. The question isn’t whether you’ll encounter these problems, it’s whether you’ll recognize them early enough to act.