A live brand intelligence platform that automatically scrapes 10 Logitech products across 12 Amazon global marketplaces, calculates opportunity scores, detects price anomalies, and generates professional PDF reports.
logitech-intelligence-rqvvsmm63hi2ka67c78ok9.streamlit.app
| Feature | Details |
|---|---|
| 🔍 Auto Scraping | 10 products × 12 Amazon markets, runs every 6 hours |
| 📊 Opportunity Scoring | Velocity + Price + Distribution + Content quality |
| 🚨 Real-time Alerts | OOS, price drops >5%, MAP violations, high opportunity |
| 🌍 Global Comparison | Live FX rates across 12 currencies |
| 📈 Price History | Track price trends over time with change indicators |
| 📄 PDF Export | 4-page professional report with executive summary |
| 🌐 Deployed | Live on Streamlit Cloud |
├── dashboard.py # 8-tab Streamlit dashboard
├── scrape.py # Standalone scraper
├── scheduler.py # Auto-scheduler (runs every N hours)
├── alerts.py # Alert detection engine
├── global_comparison.py # Global FX price comparison
├── pdf_export.py # PDF report generator
├── database/
│ └── schema.py # SQLite schema + seed data
├── scrapers/
│ ├── base.py # Base scraper with retry + UA rotation
│ └── all_channels.py # 31 channel scrapers
└── scoring/
└── opportunity_engine.py # Scoring algorithm
# Install dependencies
pip install -r requirements.txt
# Initialize database
python database/schema.py
# Scrape Amazon US
python scrape.py amazon_us
# Launch dashboard
streamlit run dashboard.py# Scrape all Amazon markets every 6 hours
python scheduler.py --interval 6
# Scrape specific channels every 2 hours
python scheduler.py --channels amazon_us amazon_uk amazon_de --interval 2| Tier | Channels |
|---|---|
| Amazon Global | US, UK, DE, CA, JP, FR, IT, ES, MX, AU, IN, SG |
| Tier A | Walmart, Target, Best Buy, eBay, Logitech.com |
| Tier B | Newegg, Costco, B&H Photo, Staples, and 10 more |
Each product-channel combo gets a score (0–100) based on:
- Velocity (30%) — Review count, BSR rank, review growth rate
- Price Competitiveness (25%) — vs MSRP and cross-channel average
- Distribution Gap (25%) — Stock availability and OOS frequency
- Content Quality (20%) — Rating, review volume, deal badges
Download a sample PDF report: sample_report.pdf
- Scraping — Python, Requests, BeautifulSoup
- Database — SQLite with WAL mode
- Dashboard — Streamlit, Plotly
- PDF — ReportLab
- FX Rates — exchangerate-api.com (live, cached 1hr)
- Deploy — Streamlit Cloud
MIT