E-COMMERCE / DATA
Competitive intelligence & data collection system
Automated ASIN monitoring across competitor storefronts with shared team database.
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Keepa API
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Processing
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SQLite DB
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Google Sheets
INDUSTRY
E-Commerce / Data
DURATION
3 months
TEAM
2 engineers
OVERVIEW
An e-commerce company needed to systematically monitor competitor storefronts and discover new product opportunities across Amazon. Manual research was slow and missed opportunities.
THE CHALLENGE
- —Competitor monitoring was entirely manual — team spent hours browsing Amazon storefronts
- —No systematic way to discover new brands entering the market
- —Two separate teams needed to share data without duplicating work
- —Data was scattered in personal spreadsheets with no single source of truth
- —Needed to track 1,000+ ASINs across multiple seller storefronts
THE SOLUTION
- —Built automated ASIN collection system that monitors competitor storefronts via Keepa API
- —Developed shared SQLite database (WAL mode) on cloud storage for multi-team access
- —Implemented deduplication logic using composite keys (seller + marketplace ID)
- —Created standardized 10-column output format synced to Google Sheets for team analysis
- —Built analytics layer with brand-level aggregation and research scoring
TECH STACK
PythonGoogle ColabKeepa APISQLiteGoogle Sheets APIService Account Auth
RESULTS
BRAND DISCOVERY SPEED
Days → minutes
MONITORED ASINS
0 → 1,000+ tracked
TEAM COLLABORATION
Separate spreadsheets → shared real-time DB
DATA DUPLICATION
Eliminated via automated dedup
NEW SKU IDENTIFICATION
3-5x increase in viable discoveries/month