The SaaS Podcast - AI, Growth & Product-Market Fit for SaaS Founders

Omer Khan
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Every week, SaaS founders share how they found product-market fit, got their first customers, scaled to $1M+ ARR, and navigated pricing, sales, churn, and AI. Host Omer Khan has interviewed 500+ founders and coached 150+ through revenue milestones. Whether you're bootstrapping to $10K MRR or scaling past $1M+ ARR, The SaaS Podcast delivers proven growth strategies - not theory. Join 5,000+ founders at SaaS Club. New episodes weekly.

  1. 20H AGO

    Vertical SaaS: $0 to $10M ARR With Flat Pricing for Everyone

    Five years to the first million. Zero dollars raised. NFL teams pay the same price as high school teams. Hewitt Tomlin built TeamBuildr into a $10M ARR vertical SaaS company by focusing on one job function and refusing to charge enterprise customers more. Founders will hear why flat pricing drove more growth than premium tiers ever could. Hewitt shares how a single conversation with a college strength coach pivoted TeamBuildr from a social app to industry-specific SaaS, why founders who plateau at $500K ARR have a product-market fit problem, and how building for a job function instead of a market segment unlocked every customer from high schools to the NFL. Plus: Hewitt's take on why he won't build AI features until his customers ask for them - even as his biggest competitor bets on replacing coaches with AI entirely. TeamBuildr has 45 employees, has never raised funding, and still operates on the same co-founder agreement from 2012. This episode is brought to you by: 💖 Gearheart → Book a free consult and get the first 20 hours free 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🏢 Build vertical SaaS around a job function, not a market segment: TeamBuildr focused on the strength coaching workflow rather than targeting colleges or pro teams separately. This unlocked every segment from high schools to NFL teams with a single product. 💰 Flat pricing can drive niche SaaS growth through social proof: Hewitt charges pro teams the same as high schools, trading premium revenue for NFL logos that validate TeamBuildr to the volume market. As a bootstrapped company, this was more pragmatic than building enterprise tiers. 🎯 Stalling at $500K ARR signals a product-market fit problem: Hewitt advises that founders putting in full-time effort but plateauing for consecutive years should stop tweaking their go-to-market and reexamine whether their product actually solves what the market needs. 🤝 Treat early users as partners, not beta testers: Hewitt didn't send logins and wait for feedback. He showed up at conferences, called coaches personally, and built relationships. His first customer Dr. Steve Smith is still someone he stays in touch with 13 years later. 🧠 Listen to what customers want, not what they say they want: Customers describe missing features because they can't articulate the outcome they need. Hewitt's job is to peel back the request and identify the real workflow improvement, then decide what to build independently. 🛠️ Don't build AI features for the sake of building them in vertical software: While competitor Volt bets on AI replacing coaches, Hewitt waits for actual customer demand. He uses AI internally for developer productivity but won't ship customer-facing AI without conviction it enhances the profession. 🚀 Inbound marketing gets stronger as your niche SaaS customer base grows: Hewitt transitioned from cold calling to inbound by telling customer stories. Following HubSpot's principle that the best inbound originates with customers, a growing base made content and social proof more potent over time. Chapters What TeamBuildr does and who it's for How the idea started as a social app in college Revenue, team size, and business structure today Pivoting from athletes to coaches The conversation that changed everything Building the MVP and making the first dollar Getting free users to actually use the product Listening to what customers really want Competing with Excel in a market that didn't know SaaS existed Five years to the first million in ARR How Hewitt knew he had product-market fit Outbound vs inbound on the way to $1M Why half the customers are high schools Charging NFL teams the same as high school teams Building vertical SaaS around AI without replacing coaches Why customers aren't asking for AI yet Lightning round Resources Full show notes: https://saasclub.io/476 Join 5,000+ SaaS founders: https://saasclub.io/email

    50 min

  2. MAR 19

    SaaS Product-Market Fit: Zero Code to 8-Figure ARR

    Sarah Ahmad offered her first product for free during COVID. Nobody signed up. Her next company hit 10,000 customers and 8-figure ARR. The difference was SaaS product-market fit - validated before writing a single line of code. Sarah shares how she and her co-founder tested demand with a landing page in the YC community, signed 100 paying customers using Google Drive and a Stripe link, and built Stable into the leading AI-powered virtual mailbox for businesses. She also explains why the SEO playbook that built the company stopped working and what replaced it. Stable serves over 10,000 companies - from solopreneurs to enterprises like DoorDash, GitLab, and Realty Income - with 50-60 employees and operations across 20+ US locations. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 💖 Gearheart → Book a free consult and get the first 20 hours free 🔑 Key Lessons 🎯 Test SaaS product-market fit before writing code: Sarah's first startup Mistro failed because she built the full product before validating demand. With Stable, she validated with a landing page and manual operations - signing 100 paying customers before writing any software. 📉 Zero signups at zero price means no product-market fit: During COVID, Mistro couldn't get users even for free. That signal was clearer than any metric - if people won't use it for nothing, the problem isn't pricing, it's relevance. 🛠️ Use embarrassingly manual MVPs for market validation: Stable's first version was Google Drive, Zoom, and Stripe. Customers sent IDs via email. It was embarrassing, but it captured real demand while the team figured out what to build. 💰 Spend enough on paid ads to get real signal: Sarah's team spent only a few hundred dollars per week on ads - not enough to know if the channel worked. She now recommends spending thousands to saturate high-intent searches before optimizing. 🚀 Word of mouth scales when you solve a real pain point: Stable reached 1,000 customers before hiring anyone for growth, with a team of just 6-7 people at $1M ARR. Genuine product-market fit drove organic referrals without a marketing budget. 🤝 Compensate for a rough product with exceptional customer experience: Sarah and her co-founder personally onboarded every early customer via Zoom and handled all support. People forgive a rough product when you solve a real problem and show up for them. 🏢 Physical operations create a moat AI can't easily replicate: Stable's processing centers and logistics network across 20+ locations give it a defensibility layer that pure software companies don't have. Chapters Introduction First startup Mistro and why it failed Discovering the virtual mailbox opportunity Validating demand with a landing page The no-code MVP with Google Drive and Stripe How Stable differentiated from legacy incumbents Getting to 1,000 customers with a team of 6 The paid ads mistake most early founders make From manual operations to building software How AI is changing the product and industry Testing SaaS product-market fit versus building blind Shifting from product builder to CEO Resources Full show notes: https://saasclub.io/475 Join 5,000+ SaaS founders: https://saasclub.io/email

    39 min

  3. MAR 12

    SaaS Distribution Channel: Partner Deals to $100M ARR

    100 restaurants. Every order processed manually. Zero lines of code. Zhong Xu built Deliverect by turning integration partners into a SaaS distribution channel that scaled his product 10x faster than direct sales. Here's how he reached 80,000 restaurants and nearly $100M ARR through partnerships instead of cold outreach. Zhong shares why he launched with a Wizard of Oz MVP, how he convinced competing software companies to distribute his product, and why he opened 10 offices in a single quarter during COVID to block local incumbents before they could form. Plus: Zhong's take on why AI might turn his platform into commodity infrastructure - and his strategy to stay ahead. Deliverect connects delivery platforms like Uber Eats and DoorDash to restaurant systems across 50 countries. Zhong previously co-founded a restaurant software company that merged with Lightspeed, which IPO'd in 2019. This episode is brought to you by: 💖 Gearheart → Book a free consult and get the first 20 hours free 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🚀 Build a SaaS distribution channel through integration partnerships: Zhong partnered with 10+ software companies who each brought 100 restaurants monthly, reaching 80,000 locations across 50 countries faster than any direct sales team could. 🛠️ Launch with a Wizard of Oz MVP before writing code: Deliverect signed up 100 restaurants and manually processed every order before building anything, proving demand without wasting months on unvalidated features. 🤝 Attribute leads to distribution partners to avoid conflict: Zhong always credited partners for deals regardless of how customers arrived, eliminating the channel conflict that destroys most partnership-driven growth programs. ⚡ Enter every market before local incumbents emerge: Deliverect opened 10 offices in one quarter during COVID, betting that being number 1 or 2 early was cheaper than displacing entrenched local competitors later. 💰 Always charge early customers - free users give less feedback: Zhong found that non-paying customers feel guilty requesting help and stay silent, while even $50/month customers actively engage and provide honest product feedback. 🧠 Deep domain expertise creates unfair SaaS distribution advantages: Zhong's 12+ years in restaurant tech meant he had every partner CEO's phone number at launch, turning cold outreach into warm partnership conversations. 🎯 Build the intelligence layer before you become commodity infrastructure: Deliverect is racing to add AI-powered menu optimization and agent commerce because connectivity alone is replicable, but owning the restaurant intelligence layer is a defensible moat. Chapters Introduction What Deliverect does and how it works 80,000 restaurants and approaching $100M ARR How Zhong's father inspired his entrepreneurial journey Building one of the first tablet-based restaurant platforms Where the idea for Deliverect came from Why four co-founders and why distribution beats product The Wizard of Oz MVP - manual orders for 100 restaurants Resources Full show notes: https://saasclub.io/474 Join 5,000+ SaaS founders: https://saasclub.io/email

    50 min

  4. MAR 5

    Bootstrapped SaaS: $200 Customer to $4M ARR Solo

    Joel Griffith's first customer paid $200 a month. His infrastructure cost $50. He was profitable from day one. But it took three years of nights and weekends before his bootstrapped SaaS hit $500K ARR. Then Google Cloud launched a competing product and a startup raised $60M to go after his market. His growth did not flinch - because eight years of content had built a bootstrapped SaaS moat that funding could not replicate. You will learn how to get first customers for a bootstrapped SaaS by teaching on GitHub and Stack Overflow, why a self-funded SaaS content engine that compounds over 8 years outlasts any viral spike, and how to scale a bootstrap operation beyond what you can handle solo by partnering instead of hiring. Joel Griffith is the founder of Browserless, a browser automation platform approaching $4M ARR with under 10 people. Joel is a jazz trumpet player turned engineer who went through five failed B2C ideas before building a profitable SaaS by solving his own pain as a developer. He has never raised a dollar. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🎯 Solve your own pain for bootstrapped SaaS success: Joel failed at five B2C ideas before realizing the problems he understood best were engineering problems - leading to a business that was profitable from day one. 🤝 Get first customers by teaching, not pitching: Joel's first 10 customers came from answering GitHub issues and Stack Overflow questions about browser automation, building trust before mentioning his bootstrapped SaaS. 🚀 Build a content engine that compounds over years: Eight years of blog posts, forum answers, and open source contributions now drive almost all inbound for this self-funded SaaS at nearly $4M ARR. 🏢 Partner to fill skill gaps instead of struggling through them: At $60K MRR solo, Joel partnered with Polychrome for hiring, sales, and legal instead of trying to learn everything himself. 💰 Bootstrapped SaaS beats VC-backed competitors through relationships: When Google Cloud and a $60M-funded startup entered his space, Joel's growth did not change because customers valued direct access to a founder with domain expertise. Chapters Introduction What is Browserless and who is it for Business size: nearly $4M ARR, under 10 people Five failed B2C ideas before finding developer-market fit Three years as a side project before going full-time Running solo to $60K MRR as a one-person bootstrapped SaaS Getting the first 10 customers from GitHub and Stack Overflow First customer: $200/month, profitable from day one Content engine still driving almost all inbound at $4M ARR Partnering with Polychrome to handle operations Competing with a $60M-funded startup and Google Cloud How AI agents created new demand for browser automation Lightning round Resources Full show notes: https://saasclub.io/473 Join 5,000+ SaaS founders: https://saasclub.io/email

    50 min

  5. FEB 26

    Enterprise Sales: $6K in SEM to a $300M Revenue Machine

    Vineet Jain arrived in the US with $100 and built Egnyte to over $300M in enterprise sales revenue - without freemium. While Box and Dropbox gave products away and raised billions, Vineet charged from day one. His first enterprise sales pipeline started with $6,000 in SEM. It took 12 years to hit $100M - then just 3 more to reach $300M. You will learn why enterprise sales can outperform freemium in crowded markets, how to land Fortune 86 enterprise customers as a 12-person startup through B2B sales discipline, and the inside sales strategy that kept cost of acquisition low while scaling to 400 staff selling to enterprise. Vineet Jain is the co-founder and CEO of Egnyte, a content collaboration and security platform with 23,000 enterprise customers and 1,400 employees. Egnyte has raised just $137.5M with no funding since 2018. In 2016, Gartner named Egnyte a leader alongside competitors that had raised billions more. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🏢 Enterprise sales can outperform freemium: Egnyte refused to offer free tiers while competitors gave products away and raised billions. Charging from day one built a sustainable B2B sales engine now generating $300M+. 💰 Start your enterprise sales pipeline with SEM: Vineet spent $6K on search engine marketing in month one. That systematic approach scaled to millions per quarter and still drives 60% of pipeline through inside sales. 🎯 Lead with compliance to win enterprise customers as a tiny startup: Egnyte landed a Fortune 86 company within its first 25 deals by focusing on enterprise certifications and content governance. 🛠️ Build hybrid when the market says go cloud-only: 30% of Egnyte's enterprise customers use hybrid deployment for use cases where pure cloud fails - like construction sites needing LAN-speed access to massive files. 🚀 Scale inside sales in low-cost cities to keep CAC low: Egnyte built offices in Spokane, Raleigh, and Salt Lake City instead of expensive tech hubs, keeping selling to enterprise cost-effective at 400 staff. Chapters Introduction What Egnyte does and company overview Revenue milestones - $100M in 12 years, $300M in under 5 more Arriving in the US with $100 and building from nothing First startup Valdero - raised $7.5M and failed Starting Egnyte with 4 co-founders and no funding Going enterprise sales only when everyone said do freemium The hybrid cloud bet Landing the first enterprise customers with $6K in SEM A Fortune 86 company visiting a 12-person startup Consensus is the shortest path to mediocrity AI strategy and the Egnyte Copilot launch Lightning round Resources Full show notes: https://saasclub.io/472 Join 5,000+ SaaS founders: https://saasclub.io/email

    51 min

  6. FEB 19

    Product-Market Fit: From Vitamin to $100M Painkiller

    Adam Markowitz spent seven years selling a nice-to-have in edtech. Then he built Drata and found product-market fit so strong that prospects called to complain his sales team was too aggressive. He signed 100 customers in six weeks and 1,000 in year one. The difference between a vitamin and a painkiller is product-market fit. You will learn how to validate product-market fit before writing code by talking to dozens of companies and auditors, why dogfooding your own product creates instant market validation, and how a "give before you take" AWS partnership made Drata a top 5 ISV on Marketplace in under two years. Adam Markowitz is the co-founder and CEO of Drata, a trust management platform with over 8,000 customers across 60 countries, 600+ employees, and $100M+ ARR. Drata achieved product-market alignment by solving a compliance pain Adam experienced firsthand at Portfolium, which was acquired for $43M. The company has raised over $300M. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🎯 Product-market fit shows in buyer urgency: Drata signed 100 customers in 6 weeks and 1,000 in year one - versus years to close the first 5 university customers at Portfolium where PMF was missing. 🛠️ Dogfood your product before selling it: Drata refused to accept customers until they used their own tool to get SOC 2 compliant, giving them instant credibility and proving product-market fit under real conditions. 🔍 Validate by talking to every stakeholder: Adam spoke with dozens of companies and auditors before writing code, discovering identical pain patterns that made the initial product scope and market validation obvious. 🤝 Give before you take with strategic partners: Drata brought thousands of first-time customers to AWS Marketplace before asking for anything, becoming a top 5 global ISV in under two years. 📉 Product-market fit means selling a painkiller: Seven years in edtech taught Adam what a vitamin feels like. At Drata, customers lined up because compliance was blocking their deals. Chapters Introduction What Drata does and the trust problem it solves Revenue, customers, and team size From astronaut dreams to NASA's Space Shuttle program Building Portfolium and selling for $43M The long road to product-market fit in edtech How the Portfolium pain led to founding Drata Validating the problem before writing code Using Drata to get their own SOC 2 before selling Signing 100 customers in six weeks Building the Auditor Alliance partner program The AWS Marketplace strategy and give-before-you-take Why aggressive sales culture was intentional AI tailwinds for compliance and trust Lightning round Resources Full show notes: https://saasclub.io/471 Join 5,000+ SaaS founders: https://saasclub.io/email

    1h 2m

  7. FEB 12

    SaaS Product-Market Fit Lost at $9M ARR Then Rebuilt

    Livestorm went from $2M to $9M ARR in one year during COVID - then lost SaaS product-market fit. Gilles Bertaux expanded into meetings and sales demos, turning Livestorm into a smaller Zoom. After a failed Series C, he rebuilt SaaS product-market fit by narrowing to enterprise webinars for European marketers in banking and pharma. You will learn why explosive growth can mask fragile SaaS product-market fit, how to rebuild PMF by narrowing positioning instead of expanding features, and why shifting from PLG to enterprise sales required replacing almost the entire sales team. Gilles Bertaux is the co-founder and CEO of Livestorm, a webinar platform for enterprise marketers. The company generates nearly $20M ARR with 3,500 customers and has raised $35M. Gilles built Livestorm as a university project in 2016, grew it through SEO and Quora, then navigated the product-market alignment challenge of post-COVID market validation. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 💖 Gearheart → Book a free consult and get the first 20 hours free 🔑 Key Lessons 🎯 SaaS product-market fit can be lost by expanding too broadly: Livestorm added meetings and sales demos after COVID, becoming a smaller Zoom with no clear differentiator and declining conversion rates. 📉 Explosive growth can mask fragile PMF: Going from $2M to $9M ARR felt like traction, but 85% of customers were on monthly plans - one click away from churning overnight. 🏢 Narrow positioning wins against giants: Livestorm stopped competing feature-for-feature with Zoom and differentiated on three dimensions - European company for security, marketers only, and specific industries. 🔄 Enterprise sales requires rebuilding, not retraining: Reps who closed inbound leads could not cold-call 10,000-person companies. Gilles replaced almost the entire sales team with enterprise outbound specialists. 💰 A failed fundraise can force the right strategic shift: When Series C investors said no, Livestorm had to become profitable - pushing toward enterprise customers on annual contracts who pay more and stay longer. Chapters Introduction What Livestorm does and revenue milestones Building Livestorm as a university project The disastrous first webinar launch SEO, Quora, and co-marketing as early growth engines How SaaS product-market fit shifted after COVID Going from $2M to $9M ARR in one year Post-COVID churn and the virtual event collapse Losing SaaS product-market fit by becoming a smaller Zoom Rebuilding positioning around Europe, marketers, and industries The painful shift from PLG to enterprise sales Lightning round Resources Full show notes: https://saasclub.io/470 Join 5,000+ SaaS founders: https://saasclub.io/email

    1h 2m

  8. FEB 5

    AI SaaS to $5.3M ARR by Solving What Others Faked

    Every wireframing tool claimed to use AI - but they were faking it. Adam Fard tested the competition, found they were swapping templates, and built an AI SaaS that actually generates wireframes from scratch. UX Pilot went from side project to $5.3M ARR in under two years. You will learn how to validate an AI SaaS opportunity by testing competitor claims, why a code-first architecture creates a competitive moat for an AI-powered SaaS product, and the content strategy that built a 600,000-subscriber newsletter without generic educational content. Adam Fard is the founder of UX Pilot, an AI startup that helps product design teams create wireframes and ship UX work faster. He bootstrapped the company using revenue from his UX agency, growing from $3M to $5.3M ARR in just 5 months with 15,000 paying subscribers and a 30-person team. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 💖 Gearheart → Book a free consult and get the first 20 hours free 🔑 Key Lessons 🎯 Test competitor claims to find AI SaaS opportunities: Adam discovered other wireframing tools were faking AI generation by swapping templates, revealing a genuine technical gap nobody else could solve. 💰 Fund your AI SaaS with existing revenue: Agency income removed VC pressure and let Adam iterate for 6-7 months on fine-tuning LLMs and component-based approaches without chasing growth. 🚀 Focus on one hard problem instead of building with AI for everything: While competitors built no-code tools that did everything, Adam focused exclusively on AI wireframe generation for the design phase. 📈 SEO still works for AI-powered SaaS: Despite claims that SEO is dead, Adam captured high-intent keywords around design, UX, and AI generation by being one of the first products to target them. 🛠️ Talk about product updates, not educational content: Adam got more newsletter engagement sharing UX Pilot features than sending generic UX education - 600,000 subscribers engaged more with product news. Chapters Introduction What UX Pilot does and who it's for Revenue, team size, and growth metrics Running a UX agency when ChatGPT launched The user question that sparked the AI SaaS idea Testing competitors and discovering they were faking AI Why creating wireframes with AI was technically hard Building an MVP and exploring fine-tuning LLMs Building a 600K subscriber newsletter from product signups Getting to the first million in ARR with LinkedIn and SEO The inflection point from $3M to $5.3M ARR in 5 months Lightning round Resources Full show notes: https://saasclub.io/469 Join 5,000+ SaaS founders: https://saasclub.io/email

    51 min
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4.8
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About

Every week, SaaS founders share how they found product-market fit, got their first customers, scaled to $1M+ ARR, and navigated pricing, sales, churn, and AI. Host Omer Khan has interviewed 500+ founders and coached 150+ through revenue milestones. Whether you're bootstrapping to $10K MRR or scaling past $1M+ ARR, The SaaS Podcast delivers proven growth strategies - not theory. Join 5,000+ founders at SaaS Club. New episodes weekly.

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