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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 🤗

Review: Should you use Whop.com to promote your SaaS product?

TL;DR: Nope. But your mileage may vary.

Doing a clipping campaign on Whop.com where you pay people to clip your videos and post it on their social media sounds alluring, it sounds new, it sounds oh so very Gen-Z.

But it’s also the metaphorical equivalent of gouging your eyes out with a cold, rusty spoon. You just shouldn’t do it.

OK, there are probably parts of the internet that find the idea of gouging out eyes with cold and rusty spoons rather exciting. Likewise, you might be the type of business that likes to set fire to hundred dollar bills just to light a cigar.

Let’s take a closer look.

What is Whop?

Whop is to Gen-Z what Youtube and Instagram is to millennials. It’s the place for creators to make money shilling shit selling products to their legions of fans. This is not your old school influencer selling other people’s shit, this is creators selling their own stuff.

Apparently Whop is quite successful at this with dozens of media reports of teens making money from it.

What has teens selling shit got to do with SaaS companies?

Somewhere along Whop’s growth journey someone had the rather clever idea that creators could reward their fans for reposting clips on other social networks. Think TikTok videos, Reels on Instagram, and Shorts on YouTube.

You know, the stuff that social networks and investors go starry eyed over because it’s like cocaine for the eyes.

It was a pretty good idea.

Creators upload their videos and their legions of fans devour it like locust in a biblical plague, turning one video into hundreds or even thousands of clips.

The fans earn a few bucks for the views they generate and the Creator turns her fans into a marketing army to spread her influence far and wide.

Still don’t get what this has to do with SaaS companies

Yeah, I’m coming to that.

When so many creators are getting their clips re-shared, then Gen-Z is going to take notice. Few apps sum up Gen-Z marketing better than Cluely, the most super-scary app ever developed if you are responsible for legal stuff in a corporate.

Cluely is built on the back of founders and early employees who are creators first and business people second (they might dispute this, but I said what I said).

If you want a job at Cluely you need to show you have at least 10,000 followers on a social network first and are an influencer in your own right.

Now (and I’m hypothesizing here) the Cluely team, being creators themselves, realized that they could become a “corporate creator” on Whop, upload their own videos and then pay ridiculous sums of money to jobless people who would create clips and upload it to their own social profiles or even create brand new social profiles.

Overnight people’s TikTok and Instagram feeds were being flooded with “cheat on everything” Cluely content, courtesy of (I believe) clippers on Whop.com.

Since nothing stays secret in marketing for long, other AI apps and podcasters started to take notice and upload their own videos and reward clippers for views.

For example, Perplexity, which just scored $200m in funding, is a big user of whop, paying out tends of thousands each month.

So what happened with StreamAlive when it tried to use Whop?

This is rather painful. Like going to the doctors with an embarrassing problem.

At StreamAlive we need to find growth channels that can explode our user base. We’re a product-led growth app with a low price point so we can’t afford to spend hundreds of dollars acquiring customers, or thousands to acquire paid users.

We need low cost, high leverage growth levers, and if all these AI companies were using Whop they must be on to something because they’re all reporting $18bn MRR in 2 months or something ridiculous like that.

The thing about growth marketing is you have a dozen experiments going on at once to find something that works. Whop might be that thing that worked.

Narrator: It wasn’t.

Setting up your Whop account

Our first clue that we weren’t in Kansas any more was when we tried to set up our Whop account.

If you’re used to slick SaaS apps with butter smooth onboarding and emails from the founder ‘personally’ welcoming you, then you’re going to feel like you entered the wild west of apps. There is no law here.

You’re basically left to figure it out.

I couldn’t figure it out so I got one of our Gen-Zs to figure it out.

He couldn’t figure it out either.

Together, we clicked buttons, opened links, and went round and round in circles until we figured that to create a clipping campaign you had to first create a product, but since we didn’t have a product, it wasn’t an actual product, it was, well, I don’t know what it was, we had to create it and set it to free.

Then Whop users could see the product and buy it for free. Or something like that.

THEN when these users bought the free product they were eligible to create video clips from the content that we uploaded.

I still don’t understand it, but that’s what you have to do.

Next you have to create your Content Rewards campaign for your product. You can create your Content Rewards campaign before you have created your product, but people can’t be a part of the Content Rewards campaign until you’ve created a product and they’ve bought it.

If you want to curl up into a ball and cry after trying to understand this workflow, then you are on the same path we were on. We’ll meet at destination f**ked.

So now your product is created, your Content Rewards campaign is active and funded (don’t ask!), you’ll start getting users who want to create video clips of your content and post it on their social networks.

This is where you encounter the first problem.

Users on Whop have no regard for your brand standards or requirements. They are interested in extracting the maximum amount of monies for the minimum amount of effort.

Therefore 100% of clips are generated using apps like opus.pro (but since the users are penniless they are probably using a cheap knock-off from appsumo).

Some clips are from videos that you didn’t even ask them to create clips for. Like this one, which isn’t on any StreamAlive channel as it was at an event and posted by the event organizers.

Many clips contain the user’s personal watermark even when our requirements said: DO NOT USE A WATERMARK

We rejected some of the videos with Creator watermarks and our Whop chat exploded.

WHy YoU reJeCt mY VIdeO :angry face: :crying face:

Apparently creators for our campaign believed that uploading our video to their AI clipping tool which automatically spits out video clips for them to use constitutes “great amount of effort” and they are “protecting my time and investment” by adding their watermark.

Eventually we decided not to fight it. It’s like putting water back into a sieve.

But trying to get people to adhere to the requirements was the least of our problems.

The real problem was with Whop Content Rewards

When you set up your content rewards (the name for asking people to clip your videos and paying them for the views they generate) you enter how much you want to spend and how much you want to pay per 1,000 views.

All very straightforward.

We researched other AI apps and saw they were offering $2-$3 per 1,000 views. We entered a bit lower because we were testing the waters.

You also set the maximum payout that a person can earn PER VIDEO.

Initially we set this to $100 thinking it was per user. Yet another thing that Whop lets you find out for yourself.

Then all the submissions come in and you have to review the video and the account and approve it. The videos have a few dozen reviews so it all looks legit.

But that’s when things get sketchy real fast. The video that you approved last night with a few dozen reviews suddenly gets tens of thousands of views overnight.

Before you know it, every video coincidentally hits the EXACT amount of views needed to get the maximum payout per video.

And then? The views just stop.

Whop has a major bot problem on Content Rewards

We quickly reduced the maximum payout per video down to $25 and the fallout in the chat was even bigger than when we said “no watermarks”.

We were being accused of being frauds and scammers for switching the maximum payouts after clippers had worked “so hard” to get views on the videos.

Never mind that the same people accusing us of being frauds were the ones using bots to generate views to get the maximum payout.

So what happened when we lowered the payout to $25?

Suddenly none of the videos got more than 30k views. That’s all the clippers needed to get the payout so paying the bot views factory more would be a waste of money.

Content Reward video clips always get the exact amount of views needed to get the maximum payout. That’s not a coincidence.

What went wrong?

We did a bit of reading and realized that we should have only accepted users from certain countries. The advice that is available is to block users from India, Bangladesh, Vietnam, Pakistan, Egypt and a dozen other countries.

Of course, you never would have found the setting to do this yourself, because it’s placed under the descriptively named “Control Center”. The only option in the Control Center is to block countries. So why it’s not called “Country Filter” or something that actually describes what it does, I don’t know 🤷

Once in the Control Center you can select which countries to block. Whop even recommends which countries to block, so why doesn’t it do that by default?!

Now that we’ve blocked users from all the bad actor countries we thought we’d see an increase in quality of videos and a believable amount of organic views on the videos they created.

We. Were. So. Naive.

Blocking these countries made ZERO difference. A teenager from Bangladesh who has discovered he can make $100 with $10 of bot views isn’t going to let a geo-IP detection stop him. All the users from the blocked countries are using VPNs to appear like they are in the US or Europe.

The final sting in the tail

According to the Whop analytics, we paid $1,500 to generate about 845,000 views, of which 99.999% were bot views.

It stung quite bad.

But then, as I was writing this Whop review I discovered something that has made the experience even more unpleasant.

Virtually all the StreamAlive videos created by the clippers have been deleted.

The only saving grace, we thought, was that at least now when people search on TikTok or Instagram, they’ll see lots of videos talking about StreamAlive.

But nope. Even that has been taken away.

What the hell is going on with Whop?

All of this begs the question: What the hell are all these other AI apps and influencers doing paying out thousands of dollars for bot views?

The people running the campaigns are not stupid. They know that all the views are bot views. Whop TELLS you that these views are bot views. But month after month they continue to pay out thousands of dollars.

WHY?

I have a theory.

For companies like Cluely and Perplexity and Replit the amount paid out is less than a rounding error in their marketing budgets. These companies have got so much money that they are probably tapped out on so many other channels, they need to find somewhere to spend their money to show growth and momentum.

So they come to Whop.

And it makes for an incredible story that the media just LOVES.

I have 372 employees creating clips of my content on social media 24 hours a day

WOW! Tell me more! Journalists love this kind of angle.

Social media goes gaga over a hook like this.

The next reason is that now, if you were to search your favourite doom scrolling app for something related to Cluely, Perplexity or one of the other AI apps that pay out thousands of dollars for bot views, you see a never-ending wall of video clips.

These apps suddenly look BIG, if everyone is talking about them and creating videos about them.

A barbaric despot dictator once said:

Quantity has a quality of its own.

And I think in a round about way that’s what the play is here for the massively funded AI apps. Flood the zone with clips to make it look like “everyone is talking about you”.

And they are talking about you because you’re telling people you have an army of influencers.

Then, tell investors that you have figured out untapped growth channels that costs literal pennies to ‘hire an army of influencers’ and who is going to closely inspect every single one of those 372 accounts on TikTok and try and figure out if they are legit or bot accounts?

Suddenly a unnoticed requirement that all these other apps made in their Content Reward programmes made sense.

They said that clippers had to create new accounts with the brand name in the account and upload the clips from there.

Fewer clippers will delete the throwaway account than videos from their actual account.

We were so, so, so naive.

Where do we go from here?

If by some chance this article has ranked in Google or in ChatGPT for people asking if Whop.com is legit or if the content rewards programme works for B2B SaaS companies, then hopefully you have your answer.

Whop.com is a place to get hundreds of thousands of bot views on dozens or even hundreds of videos across TikTok, Instagram, and Meta.

If your goal is to show investors and the media that you have a super-popular app that everyone is talking about on social media, then it’s probably the cheapest and most effective method you can find.

If you thought that you were going to get visibility and raise awareness for your app, you are going to be so incredibly disappointed.

Will Generative AI Kill SEO for SaaS? How Founders Can Still Get Discovered

Generative AI and Google’s AI Overviews are cutting clicks on informational keywords by 30–40%. SaaS companies are losing vanity traffic, but higher-intent visitors are still converting. SEO isn’t dead. The play now is to focus on brand search, structured answers, multi-format content, and new channels like AI assistants and marketplaces.

The gut punch nobody asked for

If you run a SaaS business, you’ve probably noticed something strange blood-curdling in your analytics in the last few months.

Traffic that used to trickle (or flood) in from Google is down. Like WAY down.

And when you search your own keywords, Google is now doing a cheery AI summary at the top, basically swallowing your hard-earned content and spitting it back out in 67 words.

Thanks, AI.

The fear is obvious: if ChatGPT, Gemini, or Perplexity can answer buyer questions directly, will anyone ever click through to your site again?

This post looks at what is really happening with Google’s AI Overviews and LLMs, why the biggest hit is on informational traffic, and how SaaS founders can adapt their discovery strategies before SEO as they know it slips away.

The impact of AI on SEO: traffic and click-through rates are falling

This is not just paranoia. Multiple studies confirm what founders and marketers are whispering in Slack groups:

  • Pew Research (2025) found that when an AI Overview appears, users click a traditional result in 8% of searches versus 15% without the summary. That is basically halving your odds.
  • Ahrefs (2025) showed position-one CTR on affected queries dropped from 7.3% to 2.6%, a 34.5% reduction.
  • BrightEdge (2025) reported CTR is down around 30% since AI Overviews rolled out, with B2B Tech queries now showing AI answers in more than 70% of cases.
  • Amsive saw CTR declines averaging 15.5% across 700,000 keywords, with non-branded queries hit hardest.

This erosion is most visible in informational searches, where users are happy to take the AI summary and move on.

Wait, what is an informational search?

In SEO, searches are often grouped into three types:

  • Informational: The user wants an answer or explanation. Example: “fun Zoom icebreakers” or “what is application performance monitoring.”
  • Navigational: The user is looking for a specific brand or site. Example: “StreamAlive login” or “HubSpot pricing.”
  • Transactional: The user intends to take action, like buying or signing up. Example: “best webinar engagement tools” or “buy Slack alternative.”

Informational queries are the most vulnerable to AI Overviews and chatbots because they can be answered in a single summary, without the need to click through to a website.

And the kicker? These summaries often cite Wikipedia, Reddit, YouTube, or your competitor’s blog. You might still be fueling the machine, just not getting the click.

Why informational keywords are the biggest casualty

The biggest hit is on informational queries like “what is X,” “how does Y work,” or “fun Zoom icebreakers” (more on that later).

These searches were the top-of-funnel bread and butter for SaaS marketing teams. No content strategist worth their thesaurus would be caught without a bunch of blog posts titled “What is a CRM?” or “What is a sales enablement tool?”

Now? Google owns your click.

And ChatGPT owns your customer education.

Monday.com’s share price tanks

On the second quarter earning’s call, Monday.com admitted that their organic search strategy had taken a major hit from the AI overviews. All the top of the funnel keywords it had ranked for around team management and project management were now being answered in the search results.

People don’t need to click through to Monday.com’s 2,500 word article.

The impact of this admission was stark. A 40% drop in the share price over the last month.

It’s a bloodbath out there for SEO-driven websites that relied on Google to send them traffic and leads.

The impact of AI overviews on StreamAlive’s web traffic

StreamAlive hasn’t been immune to the rollout of AI overviews either.

We built hundreds of pages around meeting icebreakers using programmatic SEO. These pages pulled in thousands of visitors, but conversion was awful, about 0.6%.

In the last six months, traffic to those pages has halved because Google’s AI Overview can now do an equally good job answering “fun zoom icebreakers.”

But here’s the interesting part: conversions actually went up.

The conversion rate on those pages is now almost 1.3%. The visitors we lost were never going to sign up anyway. The people still clicking are the ones are more motivated and have a higher intent to solve their meeting icebreaker problem (if such a thing exists).

Another interesting trend that has happened in August is the traffic to the icebreaker pages has gone up for the first time in five months AND the conversion rate has gone up.

Is Google’s AI overviews helping to pre-sell people on the need for meeting icebreakers, warming them up before they click through to StreamAlive?

It’s a theory.

What this does reveal however is a counterintuitive truth: traffic loss is not always a business loss.

If you built your funnel on fluff traffic in order to gain ‘exposure’, AI is stripping it away. What you are left with may be smaller in volume but higher in intent.

I suspect the traffic loss for Monday.com will be alarming, but not catastrophic as it loses traffic on keywords that didn’t directly convert.

Case study: playing the AI self-full filling cycle game

Now here’s where the new game of generative AI for visibilty gets a bit meta.

We’ve been using generative AI to create lots of top of funnel content for StreamAlive. As you saw above, total signups from these pages have dropped slightly, but given that traffic halved, conversion has gone up.

It almost feels like AI is creating content for AI to reference because now we are seeing more visits from ChatGPT and Perplexity to these AI-generated, programmatic pages. That is bizarre and slightly worrying for the future of generative AI, but right now it is also an opportunity.

The takeaway we’ve got from our observations so far is: generative AI is not only taking traffic away, it is also a channel you can feed.

Well-structured, relevant, and multi-format content (text, video, documentation) gives the models something to cite. We have found that when we publish content in several formats around the same topic, we are more likely to dominate the AI summaries.

Here’s a screenshot from a Google search which shows what we’ve been able to achieve using multiple content types around target keywords.

Not only is StreamAlive heavily cited in the AI overview with links to our YouTube videos and use case pages, it’s also ranking multiple pages from the website at the top, above Microsoft’s own website!

How B2B buyers are using generative AI for research

It is not just Google. Buyers are shifting their discovery habits into generative AI tools.

  • Forrester reports 89% of B2B buyers now use generative AI somewhere in the buying process.
  • TrustRadius found 72% encountered Google’s AI Overviews during software research, with 90% clicking at least one cited source.
  • Adobe says AI-referred traffic to websites has already grown more than 10x in the past year.

Translation: buyers are not only searching in Google, they are asking ChatGPT, Gemini, Perplexity, and Claude for recommendations and answers. The funnel is starting inside AI.

1,000% increase in traffic from ChatGPT

This is clearly illustrated in StreamAlive’s traffic from ChatGPT. In September 2024, Google Analytics tracked just 15 visitors from ChatGPT. By August 2025 there has been a 10x increase to over 170 visits.

That’s just 2% of our overall traffic at the moment, but the traffic from ChatGPT (and other LLMs) converts at over 15% compared to search engine traffic which converts at around 8% overall.

Strategies for SaaS discovery beyond Google

Rumours about the death of SEO are being greatly exaggerated right now.

But the rules have mutated, as they have always done ever since two Stamford graduates built a curious little app call backrub.

What marketers and SaaS founders need to do is adapt to this new normal.

1. Stop chasing vanity traffic

If AI eats the fluff clicks that were never going to convert, let it. Better to have fewer, higher-intent visitors than a flood of people who were never going to sign up anyway.

2. Optimize for being cited in AI Overviews

Structured, authoritative content is more likely to be pulled into AI summaries. Even if users do not click, being cited still influences buyer perception when they shortlist tools.

3. Double down on brand search and demand capture

Make sure that when buyers do move past the AI summary, they are looking for you by name. Stronger brand building, community presence, and consistent messaging are not optional anymore.

4. Diversify discovery channels

Relying only on Google in 2025 is like relying on Yellow Pages in 2005. Buyers are in Slack groups, marketplaces, YouTube, newsletters, and yes, inside LLMs. Spread your bets and test referral sources outside Google.

5. Publish in multiple formats

We have found combining video, blog, and documentation content makes it more likely we dominate AI summaries. Multi-format answers give AI more to latch onto.

6. Keep producing good content

After 25 years in SEO, one thing is constant: every few years the rules change. Generative AI is a monumental shift, but buyers still need information. Better to be present in AI summaries than invisible.

The future of SEO for SaaS in the age of AI

SEO has always been cyclical. Every five years, a “search is dead” narrative pops up. But generative AI is a bigger disruption than mobile-first indexing or featured snippets.

Here is the likely future:

  • Informational queries will continue to be answered directly in AI tools.
  • Transactional and branded queries will still drive traffic to SaaS websites.
  • Content that AI can reference will carry disproportionate influence, even if it drives fewer clicks.
  • Brand strength will determine whether buyers search for you by name, not just your category.

Wrapping up: clarity in the AI traffic apocalypse

The panic is real. Traffic graphs are heading south. But the real story is not that SEO is dead. It is that the buyer journey is mutating, and AI is the newest middleman in town.

If your SaaS depends only on ranking for “what is [category],” you have got a problem. If you adapt, focus on brand, get cited, and diversify channels, you will come out leaner and stronger.

And if you are sitting there thinking, “Okay, but what the hell do I actually do for my business?” that is where I can help. Book an AI clarity call and we will figure out how your SaaS can survive (and maybe even grow) in the AI traffic apocalypse.

Will Generative AI Kill SEO for SaaS?

Q1. Is SEO dead because of AI Overviews?
No. AI Overviews cut clicks on informational terms, but high-intent traffic still converts. Shift strategy rather than quit.

Q2. What keywords are most at risk?
Broad informational queries. “What is,” “how to,” and listicles lose the most visibility.

Q3. What should SaaS focus on now?
Brand search, comparison and pricing pages, structured answers, and multi-format content.

Q4. Do AI citations still drive buyers?
Yes. Volume is small. Less than 2% of the traffic the StreamAlive website recieves is from ChatGPT, but LLM referrals can convert better than classic organic.

Q5. What is a good conversion rate for traffic from ChatGPT?
StreamAlive converts 16% of visitors from ChatGPT into signups for its product. This is double the conversion rate of its organic search traffic which is 8%.

Q6. Should we block AI crawlers?
Only if you have a clear reason. If you want inclusion, allow compliant bots and keep pages crawlable.

What are UTM tracking codes

Let’s start with a definition.

A UTM tracking code is a snippet of text added to the end of a URL that helps track the performance of campaigns using Google Analytics. They can be used to differentiate how different channels, content and creatives in the same campaign are performing.

Anyone can create and use a UTM tracking code and you can use them in virtually any place where you can control the link back to your website.

When a person clicks on a link which includes a UTM code, the browser address bar will look something like this:

In order to get any value from using UTM codes, you need to use Google Analytics as this is the tool that captures and processes the data from your UTM codes.#

Continue reading

What are lead magnets?

Let’s start with a lead magnet definition:

A lead magnet is used by a company as an incentive for the visitor to hand over their email address. In B2B marketing a lead magnet is often in the form of a downloadable PDF. Other types of lead magnets could be discount codes when a visitor signs up for a newsletter, a webinar or a free tool.

For B2B marketers, getting a visitor’s email address is the first significant step towards building a relationship with a potential customer. 

The goal of a lead magnet is to offer something that the visitor values enough that they are willing to share their personal information with you.

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RIP Pagerank – No More Pagerank Updates?

Pagerank. It’s a little green bar that can mean the difference between your site earning thousands of pounds a month and nothing. Well, that has been the story up until now. An entire link buying industry has sprung up around the little green graphic.

Google was “supposed” to update the pagerank of all the sites in mid July. Now, 3 months later and there is still no sign of this happening. Pagerank is not being updated.

Further research has led me to conclude that Pagerank as we know it is dead. Google has constantly stated that it doesn’t rank websites according to pagerank (it’s a very common misconception that higher pagerank automatically means higher rankings), and Matt Cutts, an engineer at Google, has said that pagerank is not a big deal in Google and exporting the data to the toolbar is seen as a none event.

There’s no official word from Google as of yet on the status of Pagerank and it’s future, so it might not be officially dead, but they’ve never taken this long to update the toolbar before.

Still, pagerank had it’s uses. You could gauge the level of popularity of a website if it had a high PR and determine whether it was worth getting those valuable backlinks. Now that PR is dead (but certainly not forgotten) it leaves webmasters and internet marketers to rely on other sources, namely Alexa and Compete.

Both of these sites try and estimate the level of traffic to a site and quite frankly, both of them do a rubbish job. They take their sample data from users that have installed their toolbar. This means that if a site gets 100,000 visitors a month but none of them have the toolbar, and another site gets 1,000 visitors a month and 10% of them have the toolbar installed, the latter website would be ranked higher.

So what are we left with now to determine the value of a link or advertising on a website? It’s very difficult. Say what you want about Pagerank, but it was an exceptionally useful tool for determining the cost of a link or advertising.

Top 5 On-Page Optimization Tips

When most people think of search engine optimization (well ok, only those that are actually nerdy enough to know what it is of course!) they immediately think about meta tags, keyword density and doorway pages.

Like many things when it comes to SEO, what once worked no longer does.

Take meta-tags for example. Way back when the internet was still a baby, meta tags were introduced to help search engines (at the time the big search engine was AltaVista…Google hadn’t even been invented) work out what the site was about. It wasn’t long before people started abusing the Meta Tags and when the next generation of search engines came about the importance of the meta tags diminished forever.

There are some self styled gurus that will tell you that you need the optimum keyword density to rank well in the search engines. The truth is, if there were an optimium density then it would be very easy to rank in the search engines. The best thing to do is to keep your writing natural and focus on the reader first, search engine second.

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Are You Making These Top 5 SEO Mistakes?

To the average internet user the acronym SEO is just yet another bit of gobbledegook internet jargon tossed around by web geeks and nerds. To some of us web geeks and nerds SEO is the be all and end all of internet promotion. The holy grail of appearing at number one spot on Google is a dream many of us aspire to bring in to reality…but often fall dismally short in Supplemental Hell.

So often the different between getting a good ranking and a bad ranking is down to how you approach the optimization of your site. As with most things in life there’s a right way and a wrong way. Do it the wrong way and you’re looking at a life in Supplementalville, do it right and you get to live on the converted home page bringing in so many visitors you won’t know what to do.

Sidenote: Google’s Supplemental Index are results that it gives when it can’t find anything definite that you are searching for. Web pages in the supplemental index are pages that don’t have enough inbound links for Google to ‘trust’ the page enough to serve it up as a main result.

If you want to get good rankings, then make sure you avoid these top 5 SEO mistakes:

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