The SaaS Podcast: How B2B SaaS & AI Founders Get Customers

By Omer KhanBusiness Entrepreneurship Technology

The SaaS Podcast: How B2B SaaS & AI Founders Get Customers episodes

October 16, 2025First Customers: 200 Free Websites to $27M ARR
50-70 year old customers who hated vendors, distrusted cloud software, and refused monthly subscriptions. Kevin Wagstaff won his first customers by building 200 websites for free and spending 10-12 hours a day in Facebook groups answering questions without ever pitching.
Kevin reveals the SEO strategy he started 12 months before the product existed, the 6am Sunday demo that unlocked 50-75 referrals from a single mastermind group, and how he and his brother bootstrapped Spectora from $5K to $27M ARR by serving early customers instead of selling to them.
Spectora is a modern all-in-one platform for home inspectors serving over 12,000 first paying users with a 100-person team. Kevin and his brother bootstrapped the company from $0 to $10M ARR before raising any funding.
This episode is brought to you by:
💖 ⁠⁠Sprinto⁠⁠ → ⁠⁠Learn more and book a demo today
🚀 SaaS Club Launch → Build your SaaS to $10K MRR
🔑 Key Lessons
🎯 Win first customers by serving before selling: Kevin built 200 free websites for home inspectors and spent a year writing SEO content before Spectora launched, converting service clients into software customers organically.
🛠️ Use services as a wedge to find first customers: Spectora's $1,000 website projects brought 5-6 of the first 10 paying customers into the software ecosystem - hands-on service builds initial traction faster than marketing.
🤝 Earn early customers through relentless community presence: Kevin spent 10-12 hours daily in Facebook groups answering questions genuinely without pitching, building trust that converted skeptics over years.
⚡ Say yes to unreasonable asks from potential first customers: A 6am Sunday demo led to 50-75 referrals from one mastermind group - Kevin's willingness to show up proved he was different from vendors inspectors distrusted.
💰 Bundle to overcome SaaS subscription resistance: Spectora combined report writing, scheduling, payments, and texting into one platform priced below what inspectors paid for fragmented tools.
Chapters
Introduction
What Spectora does and who it serves
$27M ARR, 12,000 first customers, 100-person team
The $5K bootstrap origin story
Spending 9 months interviewing home inspectors
Building a mobile-first MVP for report writing
Starting SEO content 12 months before launch
Building 200 websites as a wedge into software sales
Winning trust with skeptical 50-70 year old customers
The 6am Sunday demo that unlocked 50-75 referrals
From $1M to $10M: SEO, conferences, and word of mouth
Stepping down as CEO after nearly a decade
Lightning round
Resources
Full show notes: https://saasclub.io/457
Join 5,000+ SaaS founders: https://saasclub.io/email
55 min
October 09, 2025SaaS Product-Market Fit: 200K Users With Zero Marketing
20,000 test billing emails sent to real customers. Total chaos. Sergiy Korolov's team built a quick fix - and accidentally discovered SaaS product-market fit. When they shared the tool with the Ruby on Rails community, it spread through word of mouth to 200,000 users with zero marketing spend.
Sergiy reveals why Mailtrap stayed free for five years before monetizing, how 100+ customer interviews guided their market validation strategy, and the "fake door test" that confirmed product-market alignment with 300 survey responses before writing code.
Mailtrap generates seven-figure ARR with 100,000+ monthly active users and a 40-person team. The SaaS product-market fit story started as a side project at Railsware.
This episode is brought to you by:
💖 ⁠⁠Sprinto⁠⁠ → ⁠⁠Learn more and book a demo today
🚀 SaaS Club Launch → Build your SaaS to $10K MRR
🔑 Key Lessons
🎯 SaaS product-market fit can come from solving your own pain: Mailtrap was born from a 20,000-email staging disaster. Building a tool that fixed their own problem created authentic PMF that resonated with the entire Ruby on Rails community.
🚀 Community trust drives growth faster than paid marketing: Sergiy's team was already active in the developer community before sharing Mailtrap. That trust turned developers into organic promoters who grew the user base to 200K with zero spend.
💰 Run 100+ interviews before setting your pricing: Instead of guessing, Mailtrap interviewed users across segments and matched qualitative feedback with product analytics to find which features correlated with paid conversion.
📊 Mandatory signup surveys reveal your real ICP: Mailtrap added required clickable questions about intent and role during signup. Activation rates stayed flat, but the team could filter analytics by cohort to find which segments drive revenue.
🛠️ Validate features with fake door tests before writing code: When users requested email campaigns, Mailtrap added a menu item linking to a survey. They collected 300 responses in weeks - proving market validation without any development cost.
Chapters
Introduction
What Mailtrap does and the 20,000 email disaster
Sharing with the Ruby on Rails community
From internal tool to SaaS product-market fit
Why Mailtrap stayed free for five years
Running 100+ customer interviews for pricing
Why fewer clicks did not boost conversion
The mandatory signup survey that changed everything
The fake door test for email campaigns
Expanding from email testing to email sending
The brand perception challenge
Lightning round
Resources
Full show notes: https://saasclub.io/456
Join 5,000+ SaaS founders: https://saasclub.io/email
56 min
October 02, 2025Bootstrapped SaaS Growth: Two Revenue Crashes to $10M
Five years of 60-hour weeks. Nights and weekends. Then COVID wiped out every customer overnight. Jonathan Kazarian's bootstrapped SaaS growth story is one of the most dramatic in SaaS history. He built Accelevents to $1M ARR while working full-time at a hedge fund, then watched revenue drop to zero. He borrowed $75K from his father's retirement and 10x'd revenue within 8 months.
Jonathan reveals how he fueled bootstrapped SaaS growth by pre-selling virtual event features with Figma mockups before building them, why growing without funding forced creativity that better-funded competitors lacked, and the 19-second support response time that became his competitive moat. You will also learn the bootstrap growth playbook of replacing cold outbound with event-led dinners.
Accelevents serves over 1,000 customers at $10M ARR with 60 people - proof that bootstrapped startup growth can survive multiple near-death experiences including COVID wiping out all revenue and the 2022 tech bubble cutting revenue in half.
This episode is brought to you by:
💖 Gearheart → Book a free strategy session + get 20% off select services
🚀 SaaS Club Launch → Build your SaaS to $10K MRR
🔑 Key Lessons
⏰ Bootstrapped SaaS growth does not require quitting your job: Jonathan worked 60 hours per week nights and weekends for 5 years, hitting $1M ARR before going full-time. He and his co-founder alternated support shifts to stay available 24/7.
📉 Pre-sell features when bootstrapped SaaS growth faces a crisis: When COVID wiped out all events, Jonathan pre-sold virtual features using Figma mockups before writing code, hitting a $1M run rate within three months of zero revenue.
🛠️ Hire for emotional investment, not just technical skill: Jonathan cycled through 21 Upwork contractors who disappeared during critical weekend events before finding a developer who genuinely cared.
🍽️ Replace cold outbound with event-led growth dinners: Accelevents hosts intimate dinners for senior event professionals with a strict no-pitching rule, generating higher response rates than any cold outreach.
⚡ Turn support response time into a competitive moat: Accelevents maintains a 19-second median response time 24/7/365. In industries where deadlines are immovable, fast support beats better-funded competitors.
Chapters
Introduction and the Charlie Munger quote
Origin story - a cancer fundraiser that became a product
The 5-year grind - 60-hour weeks nights and weekends
Going through 21 Upwork contractors
Going full-time at $1M ARR in 2020
COVID wipes out all revenue overnight
Pivoting to virtual events and bootstrapped SaaS growth with Figma mockups
The two revenue crashes - March 2020 and 2022
Event-led growth - hosting dinners to win enterprise customers
The 19-second support response time standard
Retention strategy for one-off vs annual customers
Lightning round
Resources
Full show notes: https://saasclub.io/455
Join 5,000+ SaaS founders: https://saasclub.io/email
40 min
September 25, 2025AI-Powered SaaS: 6 Years of Service Data to $18M ARR
Six years of logging every task. Thousands of hours of executive assistant data. Richard Hollingsworth turned proprietary agency logs into an AI-powered SaaS that went from $1M to $18M ARR in nine months. Fyxer's models outperformed generic LLM wrappers from day one because they were trained on real workflows.
Richard reveals why targeting professional services instead of tech workers was the AI-powered SaaS breakthrough, how a single Facebook ad signup became a $1.2M enterprise deal closed in 7 days, and the "unreasonable effort" framework that kept this AI startup intense as it scaled from 4 to 40 people. You will also learn how building with AI from a service background creates a data moat no AI business competitor can replicate.
Fyxer is an AI-powered SaaS email assistant that predicts and drafts emails for busy professionals. Richard previously bootstrapped the UK's largest executive assistant agency to $5M revenue.
This episode is brought to you by:
💖 Gearheart → Book a free consult and get the first 20 hours free
🔑 Key Lessons
🎯 Service data creates an AI-powered SaaS moat: Fyxer's 6 years of EA task logs provided training data AI-first startups could not replicate, making their product more accurate than generic LLM wrappers from launch.
🧪 Test AI against humans before launching your AI-powered SaaS: Fyxer pitted 10 human assistants against their AI and only shipped when the AI won on accuracy for a workflow customers paid $60/hour for.
💰 Target industries where email directly drives revenue: Real estate brokers and recruiters convert better because more meetings equals more money. Tech workers tolerate email but lack the same pain.
🚀 PLG signups compound into enterprise deals: Individual users sign up with work emails, creating company footprints. Ranking by draft volume turned $30/month users into $1.2M contracts.
🔥 Maintain intensity with one weekly question: "What will you put unreasonable effort into this week?" kept Fyxer's team focused as headcount grew from 4 to 40.
Chapters
Introduction and the "Unreasonable Effort" mantra
What Fyxer does: AI-powered SaaS email assistant
Revenue and growth: $1M to $18M ARR in 9 months
From farming to tech: Richard's background
Building the UK's largest EA agency
Logging every task to build the AI roadmap
GPT-3 moment: the breakthrough they waited for
Testing AI against 10 human assistants
Targeting professional services, not tech
The $1.2M deal closed in 7 days
Land and expand: PLG to enterprise sales
Lightning round
Resources
Full show notes: https://saasclub.io/454
Join 5,000+ SaaS founders: https://saasclub.io/email
47 min
September 18, 2025B2B SaaS Sales: How Firing SMBs Led to 8x Growth
SMBs were 70% of revenue but churning fast with misaligned feature requests. Bernard Aceituno fired them all and focused on B2B SaaS sales in the mid-market. The result was an 8x revenue multiplier in one year, with deals closing in 2-6 weeks instead of months.
Bernard reveals why the mid-market sweet spot of 100-1,000 employees moves faster than Fortune 500 for B2B SaaS sales, how Stack AI's Hacker News launch generated 20 meetings in 48 hours with zero B2B selling effort, and the "Monte Carlo" approach to testing B2B sales strategy channels without wasting time on mediocre experiments.
Stack AI is a no-code AI platform serving 100+ enterprise customers including Nubank. The company has raised $16M and generates high seven figures in ARR with a SaaS sales process that closes deals in 2-6 weeks.
This episode is brought to you by:
💖 Gearheart → Book a free consult and get the first 20 hours free
🔑 Key Lessons
🎯 Cut customers who hurt your B2B SaaS sales focus: Bernard found SMBs were 70% of revenue but churned fast. Firing them freed Stack AI to 8x revenue through focused B2B SaaS sales alone.
🏢 Target the mid-market sweet spot for enterprise deals: Companies with 100-1,000 employees have real budget but move faster than Fortune 500, where 95% of AI pilots fail due to legacy processes.
🚀 Launch visually to generate pipeline: Stack AI's Hacker News post generated 20 enterprise meetings in 48 hours - the visual no-code builder was instantly compelling without paid marketing.
🤝 Do founder-led sales until $500K-$1M ARR: Only founders can connect a lost deal to a product change. Bernard hired his first AE at $2M ARR but wishes he started at $500K-$700K.
💰 Expand accounts with forward-deployed engineers: One team's $100K contract can grow across 30-40 teams through a structured AI strategy process with IT leaders.
Chapters
Introduction and the "Risk" mindset quote
What Stack AI does and company metrics
From MIT PhD to startup founder
The first product pivot - from data labeling to workflows
The Hacker News launch - 20 B2B SaaS sales meetings in 48 hours
The ICP problem - trying to serve everyone
The decision to focus on enterprise mid-market
Which verticals work best for AI
The importance of founder-led sales
Running experiments without mediocrity
Lightning round
Resources
Full show notes: https://saasclub.io/453
Join 5,000+ SaaS founders: https://saasclub.io/email
41 min
September 11, 2025Product-Market Fit Lost and Found After a 100x Spike
Negative 110% gross margins. Then COVID demand spiked 100x overnight - and nearly killed the company anyway. Pat Kinsel spent years chasing product-market fit while losing money on every transaction. When the pandemic brought 100x growth, most of those customers were urgency buyers who churned when COVID ended.
Pat reveals the product-market fit journey behind Proof's rise to nearly $100M ARR - how he used a $0 landing page for market validation before writing code, why 10 years of lobbying across 47 states became a moat competitors cannot replicate, and how losing PMF after COVID forced a complete rebuild around enterprise. You will learn why product-market alignment sometimes has to be found more than once.
Pat previously sold his startup to Twitter and spent time in venture capital. Proof (formerly Notarize) has raised $260M and now serves thousands of enterprise customers across identity verification and transaction security.
🔑 Key Lessons
🎯 Validate product-market fit before writing code: Pat built a $0 Unbounce landing page and ran Google Ads to prove people searched for online notary services - measuring acquisition costs and conversion rates first.
📉 Fix unit economics before scale arrives: Proof had negative 110% gross margins, losing money on every transaction. They reached 1% margins just before COVID spiked demand 100x.
🏛️ Turn regulatory complexity into a durable moat: Pat lobbied for 10 years to change laws in 47 states. This red tape became a barrier competitors cannot replicate.
⚠️ Urgency buyers do not equal product-market fit: COVID brought 100x demand, but many customers signed for business continuity, not strategy. When the pandemic ended, they churned.
🚀 Expand TAM by evolving from point solution to platform: Rebranding from Notarize to Proof opened identity verification, fraud prevention, and e-signatures - finding product-market fit again in enterprise transaction security.
Chapters
Introduction and favorite quote
What Proof does and the business of certainty
Revenue, team size, and funding ($260M raised)
Origin story: The notary error that sparked the idea
Validating demand with a landing page and Google Ads
The first MVP: A mobile app for online notary
Slow early growth: 3 years to product-market fit at $1M ARR
Negative 110% gross margins and fixing unit economics
COVID hits: 100x demand spike overnight
Post-COVID reality: Customers churned when urgency faded
Rebranding from Notarize to Proof
Lightning round
Resources
Full show notes: https://saasclub.io/452
Join 5,000+ SaaS founders: https://saasclub.io/email
44 min
September 04, 2025Product-Market Fit: 2 Failures to $200M ARR at Pendo
Two failed startups. Zero product-market fit. Then an obsession that built a $200M ARR company. Todd Olson spent a year doing founder-led sales, refused to hire salespeople until $500K ARR, and would not scale until he saw real signs of product-market fit. That obsession paid off - Pendo now generates over $200 million in annual recurring revenue.
Todd reveals how he validated product-market fit by tracking installs instead of revenue for an entire year, why raising prices 10x overnight proved PMF was real, and the market validation approach of obsessing over the problem while creating a category nobody was searching for. You will also learn why product-market alignment depends on founder-led sales that surface missing features.
Todd built auto-tracking into Pendo so customers did not need developers adding tracking code. Today, Pendo serves 1,400+ customers with about 880 employees and has raised over $479M.
🔑 Key Lessons
📉 Two failures drove product-market fit obsession: Todd's first two startups failed to find fit. After reading "Four Steps to the Epiphany," he obsessed over validating product-market fit at Pendo before scaling anything.
🎯 Track installs, not revenue, to validate product-market fit: For Pendo's first year, Todd only measured installs - putting code in a customer's product - reaching 50 before any paid deal.
🤝 Founder-led sales reveals what is missing from your product: Todd refused to hire salespeople until $500K ARR. Staying in every deal surfaced missing features like surveys that won Pendo's largest customer.
💰 A 10x price increase proves product-market fit is real: Todd raised Pendo's minimum from $99 to $1,000/month overnight. The team panicked, but closed just as many deals.
🛠️ What you refuse to build becomes your differentiator: Todd skipped track events for five years despite every competitor offering them. Auto-tracking became Pendo's key advantage.
Chapters
Introduction and the Fred Smith quote
Starting as a programmer at 14
The dot-com boom and first startup
Second startup and failure to find product-market fit
Reading Four Steps to the Epiphany
Living the Pendo problem at Rally Software
Saying no to sessions and track events
Getting first 50 installs and first paying customer
Founder-led sales to $500K ARR
The 10x price increase that proved product-market fit
Figuring out the ideal customer profile
Lightning round
Resources
Full show notes: https://saasclub.io/451
Join 5,000+ SaaS founders: https://saasclub.io/email
46 min
July 17, 2025Building AI Products: The Positioning Shift to 7 Figures
He raised over $50M for TeamFlow, then fired two-thirds of his team when COVID ended. Flo Crivello pivoted to building AI products with Lindy, an agent platform that lets anyone automate workflows without code. The first version was so broken it sent emails saying "the user wants me to send an email to 50 software engineers."
Flo reveals the AI product development lessons that took Lindy from a broken V1 to high 7-figure ARR, including the "Notion head fake" positioning strategy that made building AI products accessible by positioning against something familiar. You will learn why LLM products need to start with familiar positioning, how shipping embarrassingly broken AI features helped find pioneers, and when to rebuild everything at 100K MRR.
Flo previously worked at Uber and spent years building a Twitter audience with 20 tweets a day. A single demo video converted that audience into 70,000 waitlist signups for Lindy in March 2023.
🔑 Key Lessons
🎯 Position your AI product against the familiar, not the alien: "AI employee" was too futuristic for a broken product. "If Zapier and ChatGPT had a baby" tapped into existing mental models when building AI products.
🚀 Ship an embarrassingly broken AI product to find pioneers: Lindy V1 sent emails that literally quoted the user's instructions. Early adopters forgave it because they bought the vision.
🪜 Climb the ladder of abstraction when building AI products: Lindy started as "update Salesforce after meetings," then generalized to any CRM, then any tool. Start specific, then keep generalizing.
📱 Build audience before launch with daily social content: Flo tweeted 20 times a day using a script to track volume. One demo video converted years of audience into 70,000 waitlist signups.
💰 Rebuild at 100K MRR if the AI product paradigm is broken: Flo spent 5-6 months rebuilding because the architecture could not deliver. When 99.9% of revenue is in the future, do not optimize for the present.
Chapters
Introduction and what Lindy does
Flo's background at Uber and TeamFlow
How COVID killed TeamFlow's growth
How the idea for building AI products emerged from Salesforce automation
The brutal pivot: firing two-thirds of the team
Launching with a demo video and 70,000 waitlist signups
When the AI product did not work
Positioning: from AI employee to Zapier of AI
The Notion head fake strategy
Rebuilding while serving customers
When MattVidPro's YouTube video accelerated growth
Lightning round
Resources
Full show notes: https://saasclub.io/450
Join 5,000+ SaaS founders: https://saasclub.io/email
42 min
July 10, 2025SaaS Churn: 100K Signups but Only 100 Active Users
100,000 signups in the first month. A SaaS churn rate of 99.9%. Richard White had only 100 people actually using Fathom daily after Zoom featured them in their marketplace. Instead of panicking, he used those low-quality signups as the perfect testing ground to fix broken onboarding.
Richard reveals how he attacked SaaS churn as the "riskiest metric" before acquisition or monetization, why 99% of signups had zero meetings on their calendars creating catastrophic customer churn, and how reducing churn through a "fake meeting" feature delivered a 10x activation improvement. You will also learn his 60-day monetization ultimatum that forced the team to start selling before the product was ready.
Richard previously ran UserVoice for over a decade. Fathom now generates eight figures in ARR with 80 employees, serving around 175,000 companies. The churn rate fix that started with bad signups became the foundation for everything that followed.
🔑 Key Lessons
🎯 Fix SaaS churn before chasing acquisition or revenue: Richard focused on churn as the "riskiest metric" first - proving people would use Fathom daily before worrying about growth, because a product nobody retains is just expensive customer churn.
🔄 Turn bad signups into a SaaS churn testing lab: When 99% of 100K signups were inactive, Richard used them as a zero-risk environment to iterate on onboarding without damaging real relationships.
🛠️ Build trust before asking users to commit: Fathom's "fake meeting" feature let users test the AI bot with pre-recorded video, solving the trust barrier and reducing churn with a 10x activation improvement.
⏱️ Set aggressive deadlines to force monetization: When the 2022 funding market crashed, Richard's 60-day ultimatum forced his team to launch a paid plan before it was built - hitting $100K ARR in month one.
🧠 Treat your second startup like speed-running a video game: Richard compared Fathom to playing Minecraft after 10,000 hours - open-ended questions become multiple choice when you have done it before.
Chapters
Introduction
What Fathom does and the AI note-taking market
Business size: eight figures ARR, 80 employees
Richard's decade running UserVoice
The trust problem with AI meeting bots
Building the "fake meeting" feature to fix activation
Zoom marketplace launch: 100K signups in month one
The SaaS churn crisis: 100K signups, 100 daily active users
Using bad signups as a zero-risk onboarding testing ground
The 60-day monetization ultimatum
Selling a team plan before it was built
Lightning round
Resources
Full show notes: https://saasclub.io/449
Join 5,000+ SaaS founders: https://saasclub.io/email
54 min
July 03, 2025SaaS Product Validation: 7 Years Before the Fit Clicked
Seven years. Near-zero revenue. Multiple failed prototypes. Rob Woollen's SaaS product validation journey at Sigma Computing is one of the longest in SaaS history. He raised $8M, built prototype after prototype, and received nothing but "polite feedback" until one lunch with Snowflake's CEO changed everything.
Rob reveals the SaaS product validation signals that separate polite interest from real demand, why he rebuilt the entire product at $1M ARR because the interface "still wasn't quite right," and how validating a SaaS idea means obsessing over the problem while iterating endlessly on the solution. You will learn why pre-product validation through market feedback can take years when creating a new category.
Sigma Computing now generates over $100M ARR with 600+ employees and 1,400+ customers. Rob's team rebuilt their product in 30 days to integrate with Snowflake, and that single market validation moment - hearing "I want this" instead of polite squinting - launched the growth trajectory.
🔑 Key Lessons
🎯 SaaS product validation means obsessing over the problem, not the solution: Sigma never changed the problem they solved - only the interface. Seven years of failed prototypes proved that problem clarity matters more than speed.
💡 Polite feedback is a warning sign during SaaS product validation: For years, Sigma got lukewarm responses. Real demand sounds like Snowflake's CEO saying "I want this - when can I start using this?"
🔄 Rebuild even when you are winning if the product is not right: At $1M ARR, Rob rebuilt Sigma's product because the interface still was not right. That intuition bet fueled the leap to $100M ARR.
🧠 Founders must be "entirely irrational" to persist: Rob kept going through seven years of near-zero revenue because he still believed they would build a huge company.
🤝 Earn your stripes before expecting partners to bring deals: Sigma proved they could get people in almost every department using cloud data, making them an attractive partner for Snowflake.
Chapters
Introduction and what Sigma Computing does
The tale of two companies: 7 years of zero revenue
Raising $8M and the first seven years of SaaS product validation
Building the team and the first "colossal failure" prototype
Losing two founding engineers and shrinking to three
Why founders must be "entirely irrational"
The Snowflake meeting that changed everything
The messy reality of product-market fit
Building champion relationships and early traction
Deciding to rebuild the product at $1M ARR
The partnership flywheel with Snowflake
Lightning round
Resources
Full show notes: https://saasclub.io/448
Join 5,000+ SaaS founders: https://saasclub.io/email
50 min

About The SaaS Podcast: How B2B SaaS & AI Founders Get Customers

From the publisher's feed

Building software got easier. Getting customers didn't. Every week, a founder building B2B SaaS or an AI product tells you how they got their first customers, and how they kept them: what worked, what didn't, and what they'd do differently.