
The SaaS Podcast - AI, Growth & Product-Market Fit for SaaS Founders
by Omer Khan
Is this your podcast?Omer Khan is an independent podcast creator known for his extensive experience in coaching SaaS founders and his deep understanding of the business landscape. Having interviewed over 500 founders and guided more than 150 through significant…
Insights from recent episode analysis
Audience Interest
- SaaS business strategies
- product-market fit insights
Podcast Focus
- interviews with SaaS founders
- scaling to $1M+ ARR
Publishing Consistency
- weekly episodes released
- active for 11 years
Platform Reach
- available on major platforms
- targeting SaaS founders
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
Brands & references
Total monthly reach
Estimated from 18 chart positions in 18 markets.
By chart position
- 🇩🇪DE · Entrepreneurship#1445K to 30K
- 🇬🇧GB · Entrepreneurship#1605K to 30K
- 🇮🇳IN · Entrepreneurship#3930K to 100K
- 🇳🇱NL · Entrepreneurship#1651K to 10K
- 🇲🇽MX · Entrepreneurship#1821K to 10K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
17K to 72K🎙 Daily cadence·479 episodes·Last published today - Monthly Reach
Unique listeners across all episodes (30 days)
56K to 240K🇮🇳42%🇩🇪13%🇬🇧13%+15 more - Active Followers
Loyal subscribers who consistently listen
17K to 72K
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
—
Total Plays
—
Total Reviews
—
* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
From 18 epsHost
Recent guests
Recent episodes
Rick Knudtson (Workshop): The email signal he ignored for 9 months
Sep 3, 2026
51m 11s
Selling Before Building: $1M ARR in Six Months
Aug 27, 2026
50m 09s
Enterprise Sales With No Product: Landing a Big Four Customer
Aug 20, 2026
47m 12s
Featherless AI: When Your Weekend Experiment Makes More Than Your Startup
Aug 13, 2026
47m 47s
Stuck at $50K ARR for 5 Years. Now $1.5M With AI Agents.
Jul 23, 2026
49m 44s
Social Links & Contact
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 9/3/26 | Rick Knudtson (Workshop): The email signal he ignored for 9 months | Nine months in. Close to zero customers. He was ready to hand the money back to investors. Rick Knudtson had already sold one company, so Workshop started with the idea he found interesting: an intranet. Customers kept telling him to fix email instead. The rebuild took 30 days and brought in 10 customers. Rick explains why big enterprises cannot run internal comms on a cheap marketing tool, how a year of newsletters and ungated resources filled the pipeline before Workshop had anything to sell, and what changed when the founding team stopped defending its own idea and started listening to customers. Plus: why Workshop dropped per-user fees for audience-based pricing, and how that changed the way customers expand into new departments. Workshop is an internal communications software platform based in Omaha with around 140 employees and just under 1,000 customers, including Capgemini. It is five years old and past $10M ARR. Rick previously co-founded Flywheel, a WordPress hosting platform sold to WP Engine in 2019. This episode is brought to you by: 🤖 Hobbes → Don't book a demo. Take one. 🔑 Key Lessons 👂 The signal was in the sales calls all along: Prospects named email as their biggest internal comms pain for nine months while Workshop kept building an intranet. Listening to customers only started once the ego from a previous exit got out of the way. 🎯 Finding product-market fit was obvious when it finally arrived: Nine months of selling the intranet earned about three customers. Thirty days on the email product brought ten. That gap told the team exactly where to go all in. 🧱 Pick a first problem you can ship fast: An intranet cannot be built iteratively, so feedback loops stall for months. Email analytics was small enough to ship in 30 days and grow into a wider platform. 🔒 Enterprise email is not a MailChimp problem: Security layers, IT governance, and getting a message into 100,000 inboxes in minutes are why large companies cannot run internal comms on an off-the-shelf marketing tool. 📣 Market for a year before you sell anything: Workshop launched a weekly newsletter on day one, now at 50,000 subscribers, alongside ungated resources and monthly webinars that grew from five attendees to five hundred. 💰 Audience-based pricing removes expansion friction: Workshop charges by employee audience size and by channel rather than per seat, so adding another department never triggers a procurement review or a new negotiation. 🧭 Write the mission first and the values later: A broad mission gave the team direction before the product existed. Values waited twelve months so they described what had actually kept the company alive. Chapters How selling Flywheel led to the internal comms idea Writing the mission statement before the product The intranet bet and why it never found a through line Why enterprise email is harder than founders assume Building a newsletter and resource library before selling Nine months, near-zero customers, and the plan to return the money The bar conversation that led to the 30-day email rebuild Ten customers in 30 days and what product-market fit felt like Audience-based pricing and dropping per-seat fees Lightning round Resources Full show notes: https://saasclub.io/493 Join 5,000+ SaaS founders: https://saasclub.io/email | 51m 11s | ||||||
| 8/27/26 | Selling Before Building: $1M ARR in Six Months | Ten thousand ads, all built by hand. Julius Körfgen left that grind to build Uplane, software that automates it, then sold to his first customers before writing a line of code. Uplane reached a million dollars in ARR in about six months. Julius makes the case for selling before building: the cold outreach that got strangers on calls, the one-week sprint from discovery call to working demo, and why he refuses to run a free pilot. Without a dollar attached, he argues, you cannot tell a real business case from a polite conversation. Plus: why Julius threw out per-seat pricing and now charges a share of ad spend, so Uplane only earns more when the customer's campaigns do better. Uplane runs around twenty people across San Francisco and Berlin. Julius and his two co-founders raised their first funding round close to a year before the product existed, AG1 is a customer, and a project with Deutsche Bahn is underway. This episode is brought to you by: 🤖 Hobbes → Don't book a demo. Take one. 🔑 Key Lessons 🤝 Sell before you build: Julius closed customers before writing a line of code. His discovery calls ended with a promise to return in a week with a solution, which forced both a real deadline and a real answer about demand. 🎯 Frame outreach as learning, not selling: His cold LinkedIn messages said he had just left his job and was exploring an idea, and asked for a few questions. People opened up about problems they would never have shared with a pitch. 💰 Never run a free pilot: Without a dollar attached you cannot tell a business case from a polite conversation. Julius has watched founders stay attached to an idea for months because nobody ever asked them to pay for it. ⚡ A week is long enough to build the thing you promised: Three founders and one week produced demos that won real customers. Scrappy was fine; fake was not, and he argues AI removes the excuse for a mock-up that does nothing. 💰 Align pricing with the outcome you claim: Uplane charges a fixed fee covering costs plus a variable share of ad spend. Julius says it makes the pitch easier, because he only earns more when the customer's campaigns do better. 🏢 Be reachable faster than an agency can be: Uplane answers customers within 120 seconds. Julius treats speed of response as the main structural advantage an early-stage company has over an incumbent agency. 🧠 Volume is not the constraint anymore: AI made producing ads nearly free, so the bottleneck moved to picking the roughly ten percent that perform. Companies pushing more output without connecting it to analytics are solving the wrong half. Chapters Introduction What Uplane does and the problem it solves Ten thousand ads by hand Deciding to leave and build it The cold LinkedIn outreach that worked Standing out when everyone uses AI to personalise The first customer Why free pilots are a trap The one-week sprint from call to demo The 120-second response rule Throwing out per-seat pricing Attribution and charging on ad spend Guardrails and atomic content Lightning round Resources Full show notes: https://saasclub.io/492 Join 5,000+ SaaS founders: https://saasclub.io/email | 50m 09s | ||||||
| 8/20/26 | Enterprise Sales With No Product: Landing a Big Four Customer | Two founders. Two engineers. No product. Christian Lund closed one of the Big Four accounting firms as Templafy's first customer before the software existed, by selling a point of view instead of a demo. When that customer asked to start with ten people, he didn't say no. He said "yes, if." Christian breaks down his approach to selling to enterprise without a product, why he answered every ten-person pilot request with "yes, if," and how fixing the proof criteria upfront turned trials into company-wide deals. He also explains why disqualifying prospects beats trying to convince them. Templafy now runs at eight figures in revenue with a couple of hundred employees. Christian and his co-founder spun it out of an on-premise document business, raised their first funding round close to twelve months before the product existed, and are now rebuilding the company again for the AI shift. This episode is brought to you by: 🤖 Hobbes → Don't book a demo. Take one. 🔑 Key Lessons 🏢 Sell your point of view before you sell product: During a technology shift, large enterprises buy people who understand the transition. Templafy won a Big Four firm on domain expertise alone, then co-created the product with them. 🤝 Answer pilot requests with "yes, if" rather than no: Christian never refused a proof of concept. He attached conditions on proof criteria, budget, timeline, and the rollout that follows, and walked away when they were missing. 🎯 Define what you are proving before any trial starts: A POC to see whether someone likes the product proves nothing. Agreeing the exact pass conditions upfront turns a trial into a decision rather than an experiment. ⚡ Setting the criteria shapes the competition: Because Templafy defined the proof points first, prospects who later ran competitive evaluations often used Templafy's criteria to score every vendor in the process. 🧠 Disqualify rather than convince: Christian's team filters for buyers who already accept the market is changing. He argues sales has nothing to do with convincing people, and that defending buyers cost too much time to pursue. 🚀 Land wide, then go deep: Enterprise security and procurement cost the same for ten users or a hundred thousand, so Templafy pushed for company-wide rollouts first and expanded into specific team use cases afterwards. 📉 Being too far ahead is a real cost: Templafy's AI messaging ran ahead of what buyers wanted. Christian's rule is that you can be fifteen percent ahead of the market but not eighty, or you lose the conversation entirely. Chapters Introduction What Templafy does and the size of the business Seeing the cloud shift and spinning out of the on-premise business Two founders, two engineers, and a year of unlearning Selling thought leadership instead of product Targeting 800 people with specific messaging Raising funding twelve months before the product Why every enterprise customer is its own market The ten-person pilot problem "We didn't say no, we said yes if" Writing the criteria your competitors get scored on Disqualification as a sales strategy Resetting the company again for AI: fifteen percent ahead, not eighty Uphill skiers, downhill skiers, and the lightning round Resources Full show notes: https://saasclub.io/491 Join 5,000+ SaaS founders: https://saasclub.io/email | 47m 12s | ||||||
| 8/13/26 | Featherless AI: When Your Weekend Experiment Makes More Than Your Startup | He spent two years building his own AI model. Over one launch weekend, a side experiment out-earned it. Eugene Cheah killed the original product and rebuilt Featherless AI around what customers actually paid for. He explains why he concluded people wanted these models more than they wanted his, and how he made the call to walk away from two years of work. Eugene breaks down how GPU hot-swapping changed the unit economics of AI inference, why he charged a flat monthly rate while the rest of the AI industry billed per token, how stripping the technical explanation off the homepage kept improving conversion, and why Reddit and Discord drove his earliest customers. Featherless AI now provides instant access to more than forty thousand open source AI models, on the way to a target of all three million on Hugging Face. It reached multiple seven figures in ARR within about a year, and has since raised a Series A led by Airbus Ventures and AMD Ventures. 🤖 Hobbes → Don't book a demo. Take one. 🔑 Key Lessons 🔄 Let the experiment beat the plan: Eugene spent two years on his own AI model, then a side experiment made more money than it over one launch weekend. He renamed the company and rebuilt around what customers actually paid for. 🧠 Attachment to your own technology is the trap: The pivot was emotional, not technical. People wanted these models more than his model, and he had been holding his own mission back by insisting it run on his architecture. 💰 Flat pricing sells to the CFO, not the engineer: Per-token billing meant teams could not answer "what will this cost?" A fixed monthly rate removed bill shock and unblocked procurement. 🎯 Removing explanation improved conversion: Featherless kept stripping the technical story off the homepage, eventually removing their own research from the top. Conversion improved each time. 🚀 Go where nobody is competing: The top hundred models have ten providers each. Beyond that, Featherless is usually the only one. A quarter of an uncontested market beat a slice of the crowded top. 🤝 First customers came from where the complaints already were: Reddit's LocalLlama and Ollama communities and Discord were full of people asking how to run models they could not host. ⚡ A constraint you solve for yourself can become the product: They built GPU hot-swapping because they had thousands of fine-tuned models and could not afford thousands of GPUs. That workaround turned out to be the company. Chapters What Featherless AI does and the size of the business Starting as an open source model project One GPU per model, and not enough money Building GPU hot-swapping The weekend the experiment made more money than the platform What they hoped to learn from the experiment Finding demand on Reddit and Discord The mission: AI beyond English and Chinese Realizing he was holding his own mission back Why flat-rate pricing instead of per-token Removing the explanation and improving conversion Hosting the long tail of open source models Competing where no one else is The Series A and what comes next Resources Full show notes: https://saasclub.io/490 Join 5,000+ SaaS founders: https://saasclub.io/email | 47m 47s | ||||||
| 7/23/26 | Stuck at $50K ARR for 5 Years. Now $1.5M With AI Agents. | Five years at $50K ARR. Ten failed projects. Lending the business money out of his own bank account. George Georgiadis came close to shutting Happier Leads down. Instead he broke through the revenue plateau and reached $1.5M ARR with zero employees. George explains what moved the number: an end-to-end platform instead of a narrow point tool, cold email as his cheapest channel because he owns the mailboxes and the data, and running a SaaS with AI agents he built himself to handle support and bug fixing around the clock. Plus: why he turned down a $1M offer to sell, and why he is hiring again after reaching seven figures alone. Happier Leads identifies anonymous website visitors, qualifies them with AI, and engages them by email. George Georgiadis bootstrapped it from a $50,000 AppSumo campaign to $1.5M ARR with no outside capital. This episode is brought to you by: 🍎 Product Fruits → Book a demo tailored to your product 🔑 Key Lessons 📉 A plateau is a depth problem, not an effort problem: George wore every hat for five years at $50K ARR and never went deep enough on one channel to make the unit economics work. 💰 Own the infrastructure your channel depends on: Building his own mailboxes and using the 175-million-contact database he already owned pushed cold email costs low enough to send millions profitably. 🎯 The point tool that felt like a mistake became the moat: Building identification, qualification, enrichment, and email sending into one platform took seven years, but no competitor covers the full path. 🤝 Cold email works on precision, not personalization theater: He picks the exact company and job title, keeps the message short, and withholds links until the prospect replies to protect deliverability. 🛠️ AI replaces a team only when the data lives in one place: Ripping out HubSpot, Intercom, and Pipedrive for self-built tools gave his AI brain the visibility it needs to fix bugs unattended. 🚀 Lifetime deals buy time, not revenue: The $50,000 AppSumo campaign got consumed by server and data costs within two years, but the reviews, word of mouth, and runway were worth more. 🧠 A solo operator owns a job, not a company: Even at $1.5M ARR with AI doing the heavy lifting, George is hiring because a business that stops when he stops cannot be sold. Chapters Cold open: five years stuck, then $1.5M What Happier Leads does $1.5M ARR with zero employees, bootstrapped From Greece to London and 10 failed projects Where the Happier Leads idea came from Clearbit quoted $20,000 so he built his own Funding the product with AppSumo lifetime deals Buying the data, building the business on top The real cost and hidden upside of lifetime deals Five years stuck at $50K ARR 80% development, 20% marketing and sales Building end to end instead of a point tool Nearly quitting and lending the business his own money What finally changed: going deep on unit economics Cold email becomes the main acquisition channel What makes cold email work at scale Running the business with self-built AI agents Self-healing software and KPI monitoring Why he's hiring again after zero employees Lightning round Resources Full show notes: https://saasclub.io/489 Join 5,000+ SaaS founders: https://saasclub.io/email | 49m 44s | ||||||
| 7/16/26 | SaaS pricingcustomer success+3 | Ron Hash | QuickFaxSkimmer+1 | — | SaaSpricing model+3 | Product FruitsCODE | 56m 45s | ||
| 7/9/26 | SaaSrevenue growth+3 | Farzad Rashidi | Respona | — | SaaS churnrevenue growth+5 | Product FruitsCODE | 58m 29s | ||
| 7/2/26 | bootstrappingcybersecurity+3 | Danny Jenkins | ThreatLockerMSPs | worldwide | bootstrapped startupcybersecurity+6 | — | 54m 00s | ||
| 5/28/26 | startup governancefounder control+3 | Eric Ries | TwilioHarvard Law School+3 | — | startup governancefounder control+3 | GearheartCODE | 46m 29s | ||
| 5/21/26 | community-led growthSaaS+4 | Mark Abbott | Traction ToolsNinety+4 | — | SaaS growthcommunity building+5 | GearheartCODE | 50m 08s | ||
Want analysis for the episodes below?Free for Pro Submit a request, we'll have your selected episodes analyzed within an hour. Free, at no cost to you, for Pro users. | |||||||||
| 5/14/26 | founder-led salesB2B sales+4 | Yega Kumarappan | PaperfliteQuora+5 | — | founder-led salescustom demos+8 | GearheartCODE | 44m 11s | ||
| 5/7/26 | bootstrapped SaaSentrepreneurship+3 | Tibo Louis-Lucas | TMAKERTweet Hunter+1 | — | bootstrapped SaaSTMAKER+5 | GearheartCODE | 49m 10s | ||
| 4/30/26 | AI startupMVP development+4 | Marius Meiners | Peec AIAntler+1 | — | AI startupMVP+5 | Respona | 36m 20s | ||
| 4/28/26 | open source SaaSbusiness growth+3 | Ev Kontsevoy | TeleportGravity | — | open sourceSaaS+5 | ThreatLocker | 1h 09m 12s | ||
| 4/16/26 | SaaS onboardinggaming psychology+4 | Karel Papik | Product FruitsKPMG+2 | Czech RepublicPrague | SaaSonboarding+8 | ThreatLocker | 55m 02s | ||
| 4/9/26 | product-market fitB2B SaaS+4 | Girish Redekar | RecruiterBoxSprinto | — | product-market fitB2B+5 | ThreatLockerCODE | 54m 07s | ||
| 4/2/26 | bootstrapped SaaS growthAI in business+4 | Sylvestre Dupont | ParseurChatGPT | — | bootstrapped SaaSAI-powered parsing+6 | GearheartCODE | 43m 07s | ||
| 3/26/26 | vertical SaaSflat pricing+4 | Hewitt Tomlin | TeamBuildrNFL | — | vertical SaaSflat pricing+7 | GearheartCODE | 49m 55s | ||
| 3/19/26 | SaaS product-market fitentrepreneurship+4 | Sarah Ahmad | StableDoorDash+6 | — | SaaSproduct-market fit+5 | ThreatLockerCODE | 39m 29s | ||
| 3/12/26 | SaaS distributionpartnerships+4 | Zhong Xu | DeliverectUber Eats+2 | — | SaaSdistribution channel+6 | GearheartCODE | 50m 24s | ||
| 3/5/26 | bootstrapped SaaScustomer acquisition+3 | Joel Griffith | BrowserlessGoogle Cloud | — | bootstrapped SaaScustomer acquisition+5 | ThreatLockerCODE | 49m 44s | ||
| 2/26/26 | enterprise salesB2B sales+4 | Vineet Jain | EgnyteBox+2 | US | enterprise salesEgnyte+5 | ThreatLockerCODE | 51m 00s | ||
| 2/19/26 | product-market fitSaaS growth+3 | Adam Markowitz | DrataPortfolium+1 | — | product-market fitSaaS+5 | ThreatLockerCODE | 1h 01m 51s | ||
| 2/12/26 | 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 02m 20s | ||||||
| 2/5/26 | 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 | 50m 42s | ||||||
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About the show, platforms, and key insights.
Distribution & Reach
About the show, platforms, and key insights.
Omer Khan is an independent podcast creator known for his extensive experience in coaching SaaS founders and his deep understanding of the business landscape. Having interviewed over 500 founders and guided more than 150 through significant revenue milestones, he brings a wealth of practical knowledge to his audience. The SaaS Podcast is unique in its focus on real-world experiences from SaaS founders, covering essential topics such as product-market fit, customer acquisition, scaling to $1M+ ARR, and navigating challenges like pricing and churn, all framed within the context of AI's impact on the industry. The weekly episodes feature firsthand insights, making it a valuable resource for entrepreneurs at various stages of their journey. Listeners primarily consist of SaaS entrepreneurs and business enthusiasts seeking actionable strategies and growth insights. The podcast offers them proven methodologies and inspiration, fostering a community of over 5,000 founders engaged in the SaaS Club, thereby enhancing their understanding of the complexities of scaling a business.
Find them online
Audience
professionals, adults
Key insights
What the show covers
- interviews with SaaS founders
- scaling to $1M+ ARR
- navigating pricing and sales
- coaching on revenue milestones
Audience interests
- SaaS business strategies
- product-market fit insights
- customer acquisition techniques
- AI in SaaS growth
Platform reach
- available on major platforms
- targeting SaaS founders
- growing listener community
- no specific platforms listed
Publishing consistency
- weekly episodes released
- active for 11 years
- 479 total episodes
- consistent publishing schedule
Chart history for The SaaS Podcast - AI, Growth & Product-Market Fit for SaaS Founders
Peaked at #39 in India, currently #39 in India.
| Market | Genre | Peak | Current | Trend |
|---|---|---|---|---|
| India | — | #39 | #39 | — |
| ID | — | #78 | #78 | — |
| SG | — | #79 | #79 | — |
| KE | — | #96 | #96 | — |
| CH | — | #109 | #109 | — |
| BE | — | #123 | #123 | — |
| Denmark | — | #129 | #129 | — |
| Germany | — | #144 | #144 | — |
| AT | — | #144 | #144 | — |
| United Kingdom | — | #160 | #160 | — |
| PH | — | #162 | #162 | — |
| South Africa | — | #163 | #163 | — |
| Netherlands | — | #165 | #165 | — |
| GR | — | #169 | #169 | — |
| PT | — | #178 | #178 | — |
| VN | — | #180 | #180 | — |
| Mexico | — | #182 | #182 | — |
| Finland | — | #188 | #188 | — |
Chart Positions
18 placements across 18 markets.
Chart Positions
18 placements across 18 markets.