How to Grow a SaaS Company to $100M ARR

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Clate Mask is the co-founder and CEO of Infusionsoft, which makes sales and marketing automation software exclusively for small businesses.

Infusionsoft combines CRM, email automation and e-commerce capabilities into one product. It helps small businesses capture more leads, improve conversion rates and generate more sales.

The company was founded in 2001 and has raised over $125 million to date. Infusionsoft has over 125,000 users and so far has processed $3.4 billion of payments for its customers.

Clate is also the author of Conquer the Chaos: How to Grow a Successful Small Business Without Going Crazy', a New York Times bestseller which focuses on balancing personal and work life, will becoming successful as a budding entrepreneur.

This episode is a story about a guy who always wanted to be an entrepreneur. But he decided to go to law school and got an MBA instead. Then, with $100,000 in debt, he finally decided that to take the leap and become an entrepreneur.

He described the first 3 years of working on his business as a 'nightmare'. He was getting deeper into debt every month. But he was determined to make his business work, yet he also had his wife and 4 kids to think about. Eventually, his wife had enough and told him that he needed to find a job.

But he had a surprising conversation the next day and decided (with his wife’s support) that he was going to continue working on his business for a little longer. And his determination paid off.

Today, his company employs 675 people and does over $100 million in annual recurring revenue.

He’s a great guy and very transparent. He shares his story and how he got through those first three ‘nightmare’ years. We explore how he got his first 1000 customers and started to get traction. And we discuss how he’s building a product-driven culture and how he thinks about competition.

This episode is part of our PLG & Growth series.

Book Recommendations

The Power of Positive Thinking

by Dr. Norman Vincent Peale

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Bilal Aijazi is the co-founder of Polly, an engagement platform that brings polls, surveys, and feedback workflows into the tools teams already use like Slack, Teams, and Zoom. In 2015, Bilal was working at a consumer messaging company, watching apps like WeChat evolve from simple chat tools into full-blown platforms. He figured the same shift would happen at work. So he and his co-founder Samir started experimenting with simple solutions to collect feedback. Their first attempt was an email-based tool, but engagement was terrible. People just treated it like another survey to avoid. Then Slack opened their API. And Bilal noticed people on Twitter asking for Slack polls. So the founders quickly ported their product over, becoming one of the very first Slack apps ever built. But the installation process was clunky. Five manual steps that required copying and pasting tokens between different screens. Yet 80% of people still completed the setup. So they were clearly providing something people wanted. Then one day someone posted Polly on Product Hunt and they went viral overnight. They were getting thousands of new signups every month and struggling to keep the servers running. Yet they had zero revenue. Their first paying customer spent $8 a month for a fantasy football league. Then came the real challenge of building a freemium SaaS: figuring out who would actually pay. Most users just wanted to do something casual with polls like pick lunch spots. But through hundreds of conversations, they found where the real money was. They focused on company all-hands, sales kickoffs, and other high-stakes meetings where feedback actually mattered. Just when things clicked, Slack threw a spanner in the works. Polly had built a workflow feature for automating feedback. They were signing five-figure deals. Six months later, Slack launched their own solution. The founders had to make a choice. Stay on Slack and hope for the best, or take a massive risk and rebuild everything for multiple platforms. They expanded to Teams, Zoom, Google Meet, and embedded directly into presentations. Rebuilding their entire infrastructure was a huge undertaking, but they had no choice. Today, Polly serves millions of monthly active users and generates multiple seven figures in ARR with just 20 people.

Ryan Wang, Assembled

SaaS Pricing Trap: Usage-Based Models Need Minimums to Survive

Ryan Wang is the co-founder and CEO of Assembled, an AI platform for customer support that helps companies manage both human and AI agents more efficiently. In 2016, Ryan was a machine learning engineer at Stripe. He and his co-founders spent two years building before launching in 2020—the same day WHO declared COVID a global pandemic. Their momentum vanished. About a quarter of demos didn't show up. Their SaaS pricing model—usage-based with no minimums—meant customers could scale to zero without leaving. It took 8 months to earn their first dollar of revenue. In 2016, Ryan was a machine learning engineer at Stripe. He and his future co-founder Brian built ML tools to automate support tickets, but they realized the real problem wasn't automation—it was workforce management. That became the spark for Assembled. The three co-founders spent two years building before they launched in 2020. They lined up a TechCrunch story, hit the front page of Hacker News, and then their launch landed the same day the World Health Organization declared COVID a global pandemic. Momentum vanished. About a quarter of demos didn't show up. It took them eight months to earn their first dollar of revenue. The SaaS pricing trap: When they finally got customers, they had usage-based pricing with no minimums. Customers could scale usage to zero. When usage flatlined during the pandemic, the team blamed themselves before realizing customers weren't leaving because of the product—they were just cutting costs. How Ryan fixed the SaaS pricing problem: 1. Shifted focus from chasing growth to serving customers who were getting value 2. Met customers in person, sat with support leaders, and built what actually mattered 3. Added pricing minimums to prevent revenue from dropping to zero 4. Built sticky features that justified the investment That hands-on approach worked for about 10 customers. Then it broke at 50. Onboarding took weeks. Some features worked in demos but failed in production. So they rebuilt onboarding to get it down to days and cleaned up the product so it could scale. Eventually they grew from their early customers to dozens more and reached 8-figure ARR.

David Shim, Read AI

Product-Led Growth to 8-Figure ARR with $0 Ad Spend

David Shim is the co-founder and CEO of Read AI, a meeting intelligence platform that helps teams capture, analyze, and act on insights from their meetings. David Shim had already built and sold a company for $200 million to Snapchat when he spotted his next opportunity: a reflection in someone's glasses during a Zoom call. During the pandemic, David noticed a fellow meeting participant's glasses reflecting ESPN.com - they were both distracted on the same call. That moment sparked a question: could AI measure meeting engagement in real-time? After cold-emailing Zoom founder Eric Yuan to validate the idea (Eric confirmed Zoom wasn't building it), David raised $10 million and launched Read AI on the Zoom App Store. The initial product showed engagement analytics - sentiment scores, attention metrics, who was distracted. Users thought it was cool. But cool doesn't pay the bills. Monthly retention sat at just 5%. Users would try the product, see their meeting scores, and never come back. David had built a dashboard when he should have built a decision-making tool. The breakthrough came when OpenAI released ChatGPT. David's team combined their proprietary engagement analytics with LLM-powered summaries, creating what they call the "narration layer" - capturing not just what was said, but how people reacted. Tone, emotions, head nods, who looked away. The transcript tells you the words; the narration layer tells you the truth. Retention climbed: 5% to 10%, then 30%, 40%, 50%, and finally 81%. Today Read AI adds 12 million accounts per year with zero ad spend. Every meeting report shared is a viral loop - all participants receive the notes, non-users see the value, and accounts multiply. Product-led growth at its purest.

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