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Home/The SaaS Podcast/Episode 456
Product-Led Growth: From Internal Mistake to 7-Figure SaaS
PLG & Growth·Sergiy Korolov, Mailtrap

Product-Led Growth: From Internal Mistake to 7-Figure SaaS

Introduction

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In 2011, Sergiy Korolov's team accidentally sent 20,000 test billing emails to real customers. The chaos was immediate - customers confused about whether they'd been charged. So they built a small internal tool to prevent it from happening again. When they shared it with the Ruby on Rails community, something unexpected happened. Developers loved it. Mailtrap spread purely through word of mouth, eventually attracting more than 200,000 users - all with zero marketing spend. This is the product-led growth playbook in action.

Sergiy Korolov is the co-CEO of Railsware, a product studio that helps companies design, build, and scale successful software products, and the co-founder of Mailtrap, an email testing and delivery platform trusted by developers worldwide. Back in 2011, Sergiy's team made a massive mistake. They accidentally sent 20,000 test billing emails from their staging environment straight to real customers. The chaos was immediate. Customers were confused and upset, wondering if they'd actually been charged or not. To make sure it never happened again, they built a small internal tool to stop test emails from reaching real inboxes. When they shared it with the Ruby on Rails community, something unexpected happened. Developers loved it, and Mailtrap spread purely through word of mouth, eventually attracting more than 200,000 users. For the next five years, Mailtrap stayed free. It was a side project until 2016, when Sergiy finally decided to turn it into a real business. Instead of guessing, his team ran over 100 customer interviews and dug into usage data to guide pricing and product decisions. It took another four years to reach $1 million in ARR. Growth was slow and steady, not the overnight success story people imagine. And just as things started to pick up, a new challenge appeared. Customers wanted Mailtrap to handle production email sending too. That meant turning a product built to avoid sending emails into one that had to deliver them flawlessly. It was a risky move. The shift created a whole new set of problems, from dealing with spam attacks and deliverability issues to fighting brand confusion about what Mailtrap actually did. Suddenly, a product known for blocking emails had to prove it could deliver them reliably. Sergiy and his team spent months rebuilding their infrastructure, tightening security, and designing tools that gave developers more visibility and control. It wasn't glamorous work, but it paid off. Mailtrap evolved into a trusted, full-stack email platform used by teams around the world. Today, Mailtrap generates seven-figure ARR with a 40-person team and more than 100,000 monthly active users.

This episode is part of our PLG & Growth series.

Key Insight

Mailtrap grew to 200,000 users over five years with zero marketing spend by solving a painful developer problem and sharing the solution with the Ruby on Rails community. They monetized only after running 100+ customer interviews and analyzing product usage data to guide pricing decisions.

Key Ideas

  • Build for yourself first: Mailtrap was born from their own 20,000-email disaster, solving a problem they experienced directly
  • Let the community spread your product: zero marketing for 5 years, purely word-of-mouth through developer forums
  • Mandatory signup surveys don't hurt conversion: adding required questions had no impact on activation rates but provided critical segmentation data
  • Run 100+ customer interviews before pricing: data-driven pricing decisions led to sustainable monetization
  • Use "fake door" tests: they validated email campaigns demand with a menu item that led to a Typeform survey, receiving 300 responses without building anything

Key Lessons

  • 🎯 Product-led growth starts with your own pain: Mailtrap was born from their own 20,000-email disaster. Building tools that solve problems you experience directly creates authentic product-market fit that resonates with similar users.
  • 🚀 Community distribution beats paid marketing for developer tools: By actively participating in the Ruby on Rails community before launching, Sergiy's team had built trust that made developers want to share Mailtrap with their peers.
  • 📊 Mandatory signup surveys reveal who actually converts: Adding required questions about intent and role had zero impact on activation but let Mailtrap filter analytics by cohort - showing marketing which segments drive revenue, not just signups.
  • 🛠️ Use fake door tests to validate features before building: Instead of building email campaigns, they added a menu item leading to a survey and got 300 responses in weeks - validating demand without writing code.
  • 💰 Run 100+ customer interviews before setting prices: Sergiy's team interviewed users across segments and combined qualitative insights with product analytics to identify which features correlated with willingness to pay.
  • 🔄 Product expansion creates brand confusion you must actively fight: When Mailtrap added email sending, users who associated the brand with blocking emails needed convincing - requiring months of repositioning and trust-building.

Watch the Episode

Chapters

00:00Introduction
00:56The 20,000 Email Disaster (Origin Story)
03:51Building Internal Tools: The "Eat Your Own Dog Food" Strategy
06:11How Mailtrap Spread Through Word of Mouth
08:53Monetizing After 200,000 Free Users
11:35The Decision to Monetize a Free Tool
14:29Pricing Strategy: Using Data and Interviews to Find the Price
16:46The Onboarding Myth: Why Fewer Clicks Didn't Increase Conversions
21:05The Mandatory Signup Survey (That Didn't Kill Growth)
24:45Filtering Marketing by User Intent and Cohort
26:02The "Fake Door" Test: Validating Email Campaigns Before Building
28:30Expanding from Email Testing to Email Sending
31:36The Pivot: Competing with SendGrid and Mailgun
35:47Competing with Giants: Building Better Analytics
39:56AI for Developers: Hype vs. Reality
47:52Lightning Round and Book Recommendation

Episode Q&A

How did Mailtrap grow to 200,000 users with zero marketing spend?

Sergiy's team shared the tool with the Ruby on Rails community where they were already active contributors, and developers spread it through word of mouth because it solved a painful problem they all faced.

Why did Mailtrap stay free for five years before monetizing?

The team treated it as a side project while focusing on their consultancy business, only deciding to monetize when they saw user feature requests growing consistently and realized the product could sustain a real business.

How did Sergiy Korolov use mandatory signup surveys without hurting conversion?

They added required questions about user intent, role, and marketing channel during signup and saw zero change in activation rates - proving that users will answer questions if the survey is quick, clickable, and non-intrusive.

What data did Mailtrap's mandatory signup survey capture?

The survey asked about business vs personal intent, user role (C-level, developer, marketer), and how they discovered Mailtrap - enabling them to filter analytics by cohort and identify which segments actually convert to paid.

How did Mailtrap validate demand for email campaigns before building the feature?

They added an "Email Campaigns" menu item that led to a Typeform survey instead of a feature, received 300 responses in weeks without any incentives, and used the feedback to prioritize their roadmap.

What pricing strategy did Sergiy Korolov use for Mailtrap?

They ran over 100 customer interviews across different segments (small companies, enterprises, individuals) and combined that with product analytics to identify which features correlated with paid conversion.

How did Mailtrap transition from email testing to email sending?

Customer demand pushed them to add production sending capabilities, but this required building spam protection, deliverability infrastructure, and overcoming brand confusion from users who associated Mailtrap with blocking emails.

What was the biggest challenge when Mailtrap started competing with SendGrid and Mailgun?

The brand perception problem - millions of users knew Mailtrap as a tool that blocks emails from reaching inboxes, so convincing them it could reliably deliver production emails required significant repositioning.

How long did it take Mailtrap to reach $1M ARR after monetizing?

Four years of slow, steady growth from 2016 to 2020 - not an overnight success, but a methodical PLG approach that prioritized product quality and user trust over aggressive sales.

Book Recommendations

The Power of Now

by Eckhart Tolle

A New Earth

by Eckhart Tolle

Links

  • Mailtrap: Website | LinkedIn | X
  • Sergiy Korolov: LinkedIn | X
  • Omer Khan: LinkedIn | X

More on PLG & Growth

Freemium SaaS: From $8/Month to 7-Figure ARR - Bilal Aijazi

Bilal Aijazi, Polly

Freemium SaaS: From $8/Month to 7-Figure ARR

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.

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

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.

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

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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