3k users, 0 revenue: a Google Sheets add-on postmortem 3k users, 0 revenue: a Google Sheets add-on postmortem<br>Jun 14, 2026<br>Two years ago, I launched an add-on for Google Sheets that made it easy to forecast<br>time series data. I called it ForecastSheets (brilliant name right?!).<br>Three thousand people have used it, yet I never earned a penny. So, time to make a story out of it!

Background

It all started when I was helping a potential cofounder with another business idea: providing<br>data analytics services to SME pharmaceutical companies. He handed me a time series dataset of<br>drug prices and asked if I could build some forecasts. I said<br>“sure, it should be straightforward!”; I remember<br>it being so with Excel,<br>and, even though I didn’t<br>have a Microsoft Office subscription anymore, I assumed that would be the case with Google Sheets.

I was wrong: Google Sheets can only do<br>linear regression and<br>exponential curves. So, I had to<br>do a crash course in forecasting and homebrew something in Python. It was a hassle, but I was focusing<br>on other things so I left it at that.

About a year later, I was in search of another idea, and I came across stories of people<br>making good money off of add-ons on the<br>Google Workspace Marketplace.<br>I remembered the problem I suffered through, so I got stuck in.

Probably the most famous fortune story in this space<br>Development

Step one was deciding which, of the many, prediction models I should use. SARIMA is the most<br>popular, so I began with it; and I quickly discovered how difficult it is to make it accurate<br>without frequent fine-tuning. I then checked what Excel ran under the hood: Holt-Winters.<br>That one performed superbly across various scenarios, and so became my chioce.

Next, I had to establish how to actually build a Google Sheets add-on. Turns out, there are<br>two types:

Workspace add-ons: latest version that’s recommended by Google

Editor add-ons: more customizable and commonly encountered

I picked Editor add-ons, so I could use other add-ons as reference points.

Building the add-on was quite easy. The React/TypeScript UI triggers a Google Apps Script, which<br>fetches the data from the spreadsheet. The script passes that to a Django API server<br>that generates the forecasts, which is inserted back into the spreadsheet.

Slightly harder was going through all the configuration and form-filling bureaucracy to get<br>it published. After a couple of rejections for valid reasons, it went live!

Marketing

I kept this simple:

Picked a dot-com brand name that includes relevant keywords - hence it being called ForecastSheets.

Built a basic landing page that explains what it is, as if it was a<br>short blog post. It had<br>none of the fancy styling that you see even on indie hacker sites these days.

Wrote a brief guide on what people<br>would often search for - seasonal forecasting in Google Sheets.

Optimised the wording on the<br>Google Workspace Marketplace listing.

Recorded a 2-minute YouTube video, again targeting what people<br>would search for.

The results speak for themselves: top of Google and YouTube search results, and third-ranked on the<br>Google Marketplace (first two being irrelevant).

Traction

As I spoiled in the opening paragraph, the add-on ended up reaching three thousand<br>downloads. Which sounds like an incredible feat!

Proof that the number is real<br>The usage logs painted a stark contrast:

Most people tried it once, then gave up;<br>those that didn’t, only used the tool once every 6 months.

A couple of users with commercial potential: an ops/strategy/analytics person<br>from Bolt the mobility company, and the customer service quality<br>department in CNT Ecuador, a public telecoms provider.

Few outreaches from the contact form as well. None of them asked for new features which<br>I could release as part of a premium package.

Retrospection

In hindsight, the problem just wasn’t painful enough.<br>People don’t run these kind of forecasts often.<br>And, if they want to do it, they’d only have to pay $10 for Excel.

The fact that I wasn’t in the data analytics field<br>made things worse. I couldn’t pivot to another use case.

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