I Found a Product Idea Hiding Inside a Google Autocomplete Suggestion. Here's the Full Case Study.
Most indie hacker case studies start with "I had a problem, so I built a solution." Mine didn't start that way. Mine started with a autocomplete dropdown that made zero sense to me at first glance — and turned into one of the more satisfying small builds I've shipped.
I'm sharing the full process here: the research, the validation, the build, and what happened after launch. No inflated numbers, no "I made $10k in a weekend" nonsense. Just an honest walkthrough for other devs who like turning small, weird ideas into working products.
Step 1: Noticing the Signal
I was doing routine keyword research for a text utility site when I typed "sorry" into a search tool out of curiosity. The autocomplete and related-searches data showed something odd: write sorry 100 times as a real, recurring, high-frequency query. Not a fluke — consistent month over month.
Before you go further here is output example of tool -
I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺 I am really sorry 🥺
That's usually the point where most people scroll past and move on. I didn't, because a repeating pattern like that is a signal, not noise. Real people were typing that exact phrase into Google with real intent behind it.
Step 2: Figuring Out the Actual Intent
Search volume alone doesn't tell you what to build. I had to figure out what someone typing "sorry 100 times" actually wanted as an end result. A few possibilities:
- They wanted to read about the phrase (informational intent)
- They wanted a pre-written block of "sorry" repeated, ready to copy (transactional intent)
- They wanted a meme or joke image
I checked what was already ranking. Almost everything was either a bare-bones repeater tool with poor UX, or low-effort content pages with no actual usable output. That told me the intent was clearly transactional — people wanted the text itself, generated instantly, not an article about apologies. And nobody had built a genuinely good tool for it.
That's validation. Not survey data, not a landing page test — just a clear, unmet, repeating demand with weak existing competition.
Step 3: Scoping the MVP Ruthlessly
It would've been easy to over-scope this. Add accounts, add a "save your history" feature, add social sharing, add a dozen preset categories. I didn't. The entire point of someone searching "sorry 1000 times" is urgency — they want output fast, not a feature tour.
So the MVP became intentionally minimal:
- A text input, plus a few ready-made presets for common cases
- A count selector — 100, 1,000, 10,000
- A generate button
- Copy button
- Download as .txt button
That's it. No sign-up wall, no unnecessary steps between the search query and the result.
Step 4: Building and Shipping Fast
Because the scope was so tight, the build itself only took a few focused sessions. Plain HTML, CSS, and JavaScript — no framework overhead needed for something this contained. I kept performance in mind from the start, since generating up to 10,000 repetitions needed to feel instant, not sluggish, or the entire value proposition falls apart.
I didn't wait for a "perfect" version. I shipped the minimal version, watched how real users interacted with it, and iterated afterward based on actual usage rather than my own assumptions.
Step 5: What I Learned Post-Launch
A few things surprised me once real traffic started coming in:
People use presets more than I expected. I assumed most users would type their own text, but a large chunk of users click straight into a preset and generate immediately. Reducing typing effort mattered more than I predicted.
The download button gets used more on mobile. Copy-paste on mobile keyboards is clunky when the block of text is huge, so a lot of mobile users prefer downloading the .txt file over trying to copy 10,000 lines by hand.
"Sorry 100 times copy and paste" style intent dominates. Almost everyone wants the output ready to paste somewhere immediately — a group chat, a text message, a caption — not a file to keep. Copy usage outpaces downloads by a wide margin.
The Bigger Lesson for Other Indie Dev's
You don't need a groundbreaking idea to build something worth shipping. You need a real, repeating signal of demand, a clear-eyed read on what people actually want when they search that phrase, and the discipline to build only what solves that specific need — nothing more.
This entire project started because I refused to scroll past a weird, oddly specific search query. If you're doing keyword or market research for your own side project, don't dismiss the strange, hyper-specific queries. Sometimes those are exactly the ones nobody has bothered to build a good solution for yet.
If you want to see the finished result of this whole process, it's a live tool now — simple enough that you can generate something like sorry 10,000 times output in under ten seconds without writing a single line of code yourself.
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