Introduction
# Price Tracker
## Overview
Track product prices across multiple e-commerce platforms to identify arbitrage opportunities, profit margins, and optimal buying/selling windows. This skill enables automated price monitoring, historical tracking, and revenue-focused decision making.
## Core Capabilities
### 1. Product Discovery & Monitoring
**Search and Track Products:** - Search products by keyword across Amazon, eBay, Walmart, Best Buy - Add products to monitoring lists - Set target price thresholds - Configure alert frequency (hourly, daily, weekly)
**Example Request:** "Monitor iPhone 15 Pro prices across Amazon and eBay. Alert me if the price drops below $800 or if eBay listing is $150+ cheaper than Amazon."
### 2. Arbitrage Analysis
**Cross-Platform Comparison:** - Compare identical product prices across platforms - Calculate profit margins after fees and shipping - Identify flip-worthy opportunities (20%+ margin after costs) - Factor in platform fees, shipping costs, and taxes
**Fee Structure Reference:** - Amazon: ~15% referral fee - eBay: ~13% final value fee + listing fees - Walmart: ~8-15% referral fee
**Example Request:** "Find Nintendo Switch bundles where eBay price is 20%+ higher than Amazon, accounting for all fees and shipping costs."
### 3. Historical Price Tracking
**Price History:** - Track price changes over time (30, 60, 90 days) - Identify seasonal pricing patterns - Detect price manipulation or flash sales - Export historical data for analysis
**Example Request:** "Show me the price history for AirPods Pro 2 over the last 60 days. Identify the best buying window."
### 4. Automated Alerts
**Alert Configuration:** - Price drop alerts (below threshold) - Arbitrage opportunity alerts (margin threshold) - Competitor price alerts (when competitor lowers price) - Bulk product monitoring
**Example Request:** "Set up alerts for all Sony TV models. Alert me if any model drops below $400 or has 25%+ arbitrage margin."
## Quick Start
### Track a Single Product
```python # Use scripts/track_product.py python3 scripts/track_product.py \ --product "Apple iPhone 15 Pro 256GB" \ --platforms amazon,ebay \ --alert-below 800 \ --alert-margin 0.20 ```
### Bulk Monitor Products from CSV
```python # Use scripts/bulk_monitor.py python3 scripts/bulk_monitor.py \ --csv products.csv \ --margin-threshold 0.25 \ --alert-frequency daily ```
### Price Comparison Report
```python # Use scripts/compare_prices.py python3 scripts/compare_prices.py \ --keyword "Sony WH-1000XM5" \ --platforms amazon,ebay,walmart,bestbuy \ --report markdown ```
## Workflow
### Arbitrage Opportunity Discovery
1. **Search** for products in high-demand categories (electronics, gaming, home goods) 2. **Compare** prices across all platforms using `compare_prices.py` 3. **Calculate** net profit after fees/shipping/taxes 4. **Filter** opportunities with 20%+ margin 5. **Verify** product condition and seller reliability 6. **Execute** or set monitoring for price drops
### Price Drop Monitoring
1. **Identify** target products (wishlist, seasonally discounted items) 2. **Set** alert thresholds using `track_product.py` 3. **Monitor** historical patterns to predict optimal buy windows 4. **Act** when price drops below threshold 5. **Repeat** for seasonal shopping events (Prime Day, Black Friday)
## Scripts
### `track_product.py` Track a single product across platforms with configurable alerts.
**Parameters:** - `--product`: Product name/keyword - `--platforms`: Comma-separated platforms (amazon,ebay,walmart,bestbuy) - `--alert-below`: Alert when price drops below this amount - `--alert-margin`: Alert when arbitrage margin exceeds this fraction (e.g., 0.20 = 20%) - `--frequency`: Check frequency (hourly,daily,weekly) - `--output`: Output format (json,csv,markdown)
**Example:** ```bash python3 scripts/track_product.py \ --product "Samsung Galaxy S24 Ultra 256GB" \ --platforms amazon,ebay,walmart \ --alert-below 900 \ --alert-margin 0.25 \ --frequency daily \ --output markdown ```
### `compare_prices.py` Compare prices for a product across all platforms.
**Parameters:** - `--keyword`: Product search keyword - `--platforms`: Comma-separated platforms (default: all) - `--report`: Report format (markdown,json,csv) - `--sort-by`: Sort by price, margin, or rating - `--min-rating`: Minimum seller rating
**Example:** ```bash python3 scripts/compare_prices.py \ --keyword "PlayStation 5 Slim" \ --platforms amazon,ebay,walmart,bestbuy \ --report markdown \ --sort-by margin \ --min-rating 4.5 ```
### `bulk_monitor.py` Monitor multiple products from a CSV file.
**CSV Format:** ```csv product,platforms,alert_below,alert_margin "Apple MacBook Air M3 256GB",amazon,ebay,walmart,899,0.20 "Sony PlayStation 5",amazon,ebay,399,0.25 "Dyson V15 Detect",amazon,walmart,bestbuy,500,0.18 ```
**Parameters:** - `--csv`: Path to CSV file - `--margin-threshold`: Minimum margin to report - `--alert-frequency`: Frequency of alerts - `--output`: Output file for alerts
**Example:** ```bash python3 scripts/bulk_monitor.py \ --csv products.csv \ --margin-threshold 0.20 \ --alert-frequency daily \ --output alerts.txt ```
### `price_history.py` Retrieve and analyze historical price data.
**Parameters:** - `--product`: Product name/keyword - `--days`: Number of days of history (default: 30) - `--platform`: Specific platform (optional) - `--output`: Output format (markdown,json,csv) - `--trend-analysis`: Include trend analysis and predictions
**Example:** ```bash python3 scripts/price_history.py \ --product "AirPods Pro 2" \ --days 60 \ --trend-analysis \ --output markdown ```
## Best Practices
### Arbitrage Profit Calculation
Always calculate net profit: ``` Net Profit = (Sell Price - Buy Price) - Platform Fees - Shipping Costs - Payment Processing Fees - Taxes ```
**Recommended minimum margin:** 20-25% to account for: - Unexpected shipping delays - Returns/refunds - Market price fluctuations - Time value of money
### Risk Mitigation
1. **Verify seller reliability** - Check ratings and reviews 2. **Check product condition** - New, refurbished, or used 3. **Factor in return windows** - Platforms have different policies 4. **Monitor price stability** - Volatile prices increase risk 5. **Stay within limits** - Don't over-leverage on single opportunities
### Seasonal Patterns
- **Q4 (Oct-Dec):** Holiday sales, best for electronics - **January:** Post-holiday clearance - **Prime Day (July):** Amazon-specific deals - **Black Friday/Cyber Monday:** Cross-platform discounts - **Back-to-School (Aug-Sep):** Laptops, tablets, accessories
## Automation Integration
### Set Up Cron Jobs for Automated Monitoring
```bash # Check prices every 6 hours 0 */6 * * * /path/to/price-tracker/scripts/bulk_monitor.py --csv products.csv --output alerts.txt
# Daily arbitrage scan 0 9 * * * /path/to/price-tracker/scripts/compare_prices.py --keyword "high-demand-products" --report markdown >> /path/to/reports.txt ```
### Integration with Notifications
Combine with notification systems (email, Discord, Telegram) to receive real-time alerts when opportunities are detected.
## Limitations
- Platform API rate limits may affect search frequency - Real-time prices may have slight delays - Some platforms restrict scraping (comply with ToS) - Seller inventory changes rapidly
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**Revenue first. Track smart. Flip fast.**