How we made our supplier matching more accurate
This is a plain record of one improvement round - and what actually made our supplier matching more accurate for buyers.
Where we started
Our matching was fine, but too broad. We were surfacing suppliers across a whole category, instead of the few who clearly made the buyer's exact product type. Buyers got a wider list, but more of it was irrelevant.
What we changed
- Narrowed the match: instead of "suppliers in category X," we filtered to those with a verifiable record in the specific product. Fewer matches, sharper fit.
- Added verification: before surfacing a supplier, we check it exists, makes your product, and is reachable. The list you see is already screened.
- Ranked by response: suppliers who actually respond to your type of request surface first. No more guessing who's real.
What the data said
The share of relevant matches climbed. But the more telling shift was responses - more of the suppliers we surfaced came back. That told us the matching now earned a real reply, not just a browse.
The lesson wasn't "surface more names." It was "surface fewer, sharper fits and verify them." Manual tweaking chased the symptom; the system fixed the cause.
Why self-evolution wins
Every sourcing request feeds its result back. The next round inherits what matched well and drops what didn't - without a human rewriting the rules each week. That's the difference between a directory you browse and a matching system that improves itself.
TokoAI - a find-suppliers system that improves with every request. Every sourcing round feeds back in; the next match is sharper.
Tell us what you want to source