Case study
AMAZON WHOLESALE PIPELINE —
KEEPA + N8N
A buying-decision pipeline that turns distributor price lists and Keepa exports into ranked Master, Winners, and Review sheets in Google Sheets.
- Attribution
- Techneyx
- Status
- Client delivery
- Role
- Automation Engineer (Techneyx)
Stack: n8n · Node.js · Google Sheets · Jest
Problem
Amazon wholesale buyers were spending too much time manually matching distributor catalogs to Amazon listings and deciding what was worth buying.
What I built
I built a production decision pipeline that takes distributor price files and Keepa bulk CSV exports, then pushes the processed results through staged n8n workflows into Google Sheets. The business logic covers UPC normalization, ASIN expansion, price fallback rules, fee handling, demand signals, and final winner or review classification.
Stack
n8n, Node.js scoring libraries, Google Sheets, Jest, and Keepa bulk CSV exports. This was not a Keepa API integration.
Outcome
The client now works from ranked Master, Winners, and Review sheets instead of raw source dumps — a workflow that's faster to operate and easier to audit. The scoring rules are covered by tests, so the logic can evolve without breaking trust in the output.
Links
Project is not publicly available. Portfolio PDF: /docs/Amazon-Wholesale-Pipeline-Keepa-n8n.pdf
Continue
Back to the wall