I did a week of market research in an afternoon — from my terminal

Every project I start eventually runs into the same uncomfortable moment. I'm excited, the demo works, and then a quiet voice asks: am I the only person who actually needs this?

For Spoken Kitchen — my app that turns an elderly relative's cooking ramble into a bilingual recipe book — that question really mattered. If there's already a StoryWorth-for-recipes with translation built in, I'd rather find out on day one than after I've spent three months building it.

The honest answer to that question is market research: who else is here, what do they charge, how do they talk about themselves, who's the customer, and where's the gap. Normally that's a week of open tabs, half-finished spreadsheets, and pricing pages that won't load. This time I did the whole thing in an afternoon, entirely from my terminal, using the Nimble CLI.

I'm not going to walk through every finding here — I published all of it. The full research, every script, and the raw data live in this repo, and the results are deployed as an interactive page here. This post is about what the process was actually like, and what I walked away believing.

The mental shift that made it click

The thing that unlocked this for me wasn't a feature. It was reframing the whole project as one simple mapping: a business question becomes a command.

"Who are all the players?" is a search sweep. "What do they charge?" is pulling pricing pages. "How do they position?" is grabbing competitor homepages and reading them next to how real buyers describe the problem. "Who's the customer?" is reading the actual threads where people are asking for this. Once I stopped treating research as vibes and started treating each question as a thing I could run, the afternoon basically structured itself.

Every phase ended up being a small shell script that called nimble and dumped raw JSON to a folder. By the end I had a directory I could re-run, not a memory of tabs I'd closed.

What surprised me

It found competitors I didn't know to look for. I went in with a shortlist I was pretty confident about. The discovery sweep surfaced two voice-to-recipe products that weren't on it at all. That's the part that actually mattered — anyone can confirm what they already suspect, but having the search widen on me, catch the things I'd have missed, is the whole reason to do research instead of just guessing.

It was live, not a training snapshot. I was reading pricing and Father's-Day homepage copy that was current to that day. For competitive work this is the difference between real and theater — last year's pricing tells you nothing.

The customer was already telling me what to build. The most useful stuff wasn't the competitor pages, it was the buyer-side searches. People are already translating family recipes by hand, copy-pasting them into translators, scrambling to save a grandparent's handwriting after a funeral. The need is clearly real and clearly nobody's productized it well. You can't get that from a competitor's marketing — you get it from listening to where people are already struggling.

The part that was genuinely annoying

It wasn't all clean. A few of the pricing pages render their numbers in JavaScript, so pulling the page gave me everything except the prices, and I had to fall back to reading them out of search snippets. There were a couple of flags that turned out to be enterprise-only and just 403'd at me until I figured that out. And the CLI wants the API key in the environment, not in a .env file, which cost me a confused ten minutes.

I'm including the friction on purpose. The pitch for tools like this is always frictionless, and it mostly was — but the honest version is that I still spent a little time reading errors and adjusting. The difference is those were ten-minute detours, not the days that scraping each site by hand would've cost.

What I actually walked away with

I came in asking whether I was the only one who needed this. I left with the opposite of a vibe — a priced, positioned, customer-named picture of the market, and a clear empty space where Spoken Kitchen fits. The specifics are all in the repo and the results page if you want to see the charts.

But the bigger takeaway is about the shape of the work. Market research used to be a thing you scheduled a week for and dreaded. Turning it into a folder of scripts changed it from a chore into something I'll just do now — early, often, and again whenever the market moves. That's the real unlock. Not that it was faster, but that it got cheap enough to become a habit.

And the answer to the question? No, I'm not the only one who needs this. I might just be the first one building it.

If you want to reproduce it or poke at the data, everything's open: the research repo has the scripts and raw JSON, and the deployed page has the findings.