I scraped 3,000 ecommerce listings and realized most AI product research advice is BS

Scraped ~3k ergonomic desk accessory listings because I wanted to see if AI product research is actually useful or just more LinkedIn slop.

Turns out the interesting part wasn't the prompts.

It was getting clean data in the first place.

Most "AI product research" content is basically:

"ask ChatGPT what to sell"

which feels kinda useless tbh.

What actually worked for me:

1. scrape a stupid amount of listings

2. dump everything into CSV

3. feed it into Claude

4. look for repeated signals instead of magic answers

The funny part is how insanely repetitive most listings are.

Every seller says:

* ergonomic

* premium

* adjustable

* space-saving

Meanwhile reviews are screaming:

* this thing wobbles

* setup took 40 mins

* scratched my desk

* cable management sucks

Whole market is LARPing as premium while customers just want stable products that don't annoy them lol.

Biggest realization:

AI is cracked at processing huge amounts of repetitive info.

Humans are still better at deciding whether the pattern actually matters.

The workflow that ended up working looked more like:

human = asks good questions

AI = pattern machine

tools = keep structured data flowing

Honestly feels like product research is slowly turning into dataset analysis.

Kinda weird to watch in real time.