SaaS Entrepreneurship

I Built a $1M AI App [No Code]

Starter Story 16 min #23
I Built a $1M AI App [No Code]

This is the breakdown of how David Bressler went from working a full-time job to building an AI app valued at over $1M in just over 1 year.


Summary

  • David Bressler

    • Built an AI spreadsheet and data app originally called Excel Formula Bot and later called Formula Bot.
    • Started the product while working a full-time job and helping prepare for the birth of his youngest child.
    • Used a six-week window to build something around a problem he personally understood.
    • Had no coding background and learned most of what he needed from Bubble documentation and YouTube.
  • Formula Bot

    • Helps people work faster and smarter with data.
    • Includes AI inside Excel and Google Sheets.
    • Offers formula generators that translate text into spreadsheet formulas.
    • Includes a data analyzer where users can upload data and ask for answers, analysis, charts, and modeling in natural language.
    • Grew to roughly 750,000 users in about a year and a half.
    • Reached about 5,000 paying users for unlimited access.
    • Reached about $226,000 in monthly recurring revenue.
  • Origin And MVP

    • Got the idea after repeatedly helping junior analysts with Excel questions at work.
    • Asked OpenAI for name ideas and found the Excel Formula Bot domain available.
    • Searched online for similar tools and could not find the same product.
    • Built the MVP in Bubble because coding it would have taken too long and hiring someone was too expensive for an unproven idea.
    • Launched the first version as a no-code app in a couple of weeks.
    • Later moved from fully no-code to about 5% to 10% coded as the product hit no-code limitations.
  • Launch And Early Users

    • First showed the tool to people at his full-time job, who were surprised it had only taken weeks to build.
    • Posted it on the Excel subreddit with a simple title and link.
    • Became the top post of the day, then the top post of the week.
    • Posted it on the Internet Is Beautiful subreddit after a commenter suggested it.
    • Got around 10,000 upvotes, thousands of comments, and heavy traffic from that post.
  • Early Monetization

    • Quickly spent about $5,000 on OpenAI API costs after the viral launch.
    • Added a Stripe donation link and made a few thousand dollars back.
    • Tested ads and sponsorships, including an ESPN Excel competition ad.
    • Found ads were not worth the hassle as a long-term model.
    • Added logins and a paywall a few months later.
  • Product Evolution

    • Started as an Excel formula generator and expanded into additional generators.
    • Initially struggled to explain a broader vision to venture capitalists beyond more generators.
    • Talked with coworkers who worked with data and spreadsheets.
    • Learned from users who emailed Excel files and asked for help beyond formula generation.
    • Offered to help those users on calls in exchange for feedback about the product.
    • Used those calls to shift the product toward an all-in-one platform for data analytics work.
  • Competition And Positioning

    • Saw many similar Excel formula generator sites appear within weeks.
    • Faced competitors that copied the product, interface, and naming.
    • Realized a simple input-output generator would become a race to the bottom.
    • Heard from Microsoft about building an Excel add-on, then worried Microsoft could turn the idea into a built-in Office feature.
    • Recognized ChatGPT as a churn driver because it offered free unlimited usage.
    • Initially competed on convenience and customization inside spreadsheets.
      • Users could generate formulas without leaving Excel.
      • Users could set language preferences for spoken language and Excel language.
    • Shifted the long-term vision toward features that could not be easily replicated by ChatGPT or Microsoft.
  • Lessons And Advice

    • Started by solving his own problem.
    • Used no-code because it let him move quickly without outside funding or a developer.
    • Turned customer support requests into product research calls.
    • Learned that viral usage can create urgent infrastructure costs before monetization is ready.
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