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From Side Hustle to $8K MRR: Notion2Sheets Case Study

6/11/2024
Notion2Sheets
Leandro Zubreski
Notion2Sheets
notion2sheets.com
Buenos Aires, ArgentinaFounded 2021
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Monthly Revenue
$8,400
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Founders
Leandro Zubreski
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Employees
1
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Business Description

Notion2Sheets is a micro-SaaS that syncs Notion databases with Google Sheets, enabling automatic updates, formula use, and charting by bridging two leading productivity tools. Born from direct user feedback, it now serves tens of thousands of users.
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Executive Summary

Notion2Sheets began as a rapid two-week MVP by Argentinian freelancer Leandro Zubreski, filling a critical gap between Notion and Google Sheets. By bootstrapping user research in Reddit and Facebook groups and leveraging strategic Product Hunt and Hacker News launches, the plugin hit 50 users in 10 days, scaled to 40K installs, and reached $8.4K MRR. This case study explores each step and practical tips for founders to replicate this growth.
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Case Study Content

How Notion2Sheets Bridged a Major Productivity Gap

Notion soared in popularity as a workspace organizer, but many users hit a wall once they needed advanced spreadsheet features. In May 2021, software developerLeandro Zubreskirecognized this pain point and turned it into a micro-SaaS opportunity. By tapping into the newly released Notion API, he built a minimum viable product (MVP) that syncs Notion databases with Google Sheets, unlocking formulas, charts, and pivot tables for structured Notion data.

Rapid MVP & User Discovery

Leandro spent his first week researching in Notion communities on Reddit and Facebook, noting frustrations around manual exports and limited analytics. Drawing on past experience with the Google Sheets API, he coded the core workflow in two weeks and launched on the Google Workspace Marketplace. Early adopters reported bugs, but their feedback directed crucial fixes and feature priorities.

Community-Driven Growth

Rather than paid ads, Leandro engaged directly in niche forums. He shared demos on Reddit, posted screenshots in Facebook groups, and answered every question. Moderators tolerated self-promo thanks to the fresh Notion API excitement. This organic approach secured 50 users within ten days of launch.

Iterating Pricing and Features

A generous free tier offered three workspaces and three databases, plus hourly updates. While it drove installs, it capped revenue. Leandro adjusted limits iteratively—optimizing the balance of value and paid tiers. This process was—and still is—data-driven, using user behavior to refine subscription levels and add-on options.

Leveraging Product Hunt & Hacker News

A coordinated Product Hunt launch with a Notion insider, plus a front-page Hacker News post, refined the landing page copy and visuals. The buzz delivered new sign-ups and press mentions, and extended the tool’s credibility beyond the Notion world—even when direct sales from HN remained modest.

Scaling to $8.4K MRR

Fast forward to December 2023: Notion2Sheets crossed 40,000 installs and 400 paying users, yielding $8,400 MRR. The secret? Ongoing user research, community engagement, and carefully tuned pricing. Its position as a top result on the Marketplace continues to drive organic leads, while the blog educates and converts new prospects.

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Key Takeaways

  • 1Leverage direct user research in niche communities to pinpoint product-market fit beyond guesses.
  • 2Build an MVP quickly—Notion2Sheets went live in just two weeks using the Notion and Google Sheets APIs.
  • 3Use generous free plans to attract early adopters, then refine limits based on real usage and feedback.
  • 4Amplify launches via Product Hunt and Hacker News to boost credibility and landing-page polish.
  • 5Prioritize community engagement—answer questions, post demos, collect bug reports in Reddit and Facebook.
  • 6Optimize pricing iteratively, balancing free value with paid upgrades to sustainably grow MRR.
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Key Facts

Users Acquired in 10 Days
50 users
Total Installs
40,000+
Paid Subscribers
400+
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Tools & Technologies Used

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How to Replicate This Success

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Disclaimer: Some data in these case studies may be inaccurate or out of date. In certain cases, AI-generated content is used.