This project is an end-to-end price intelligence automation pipeline designed to:
- Extract competitor prices (Amazon & BestBuy) for 4 products
- Compare them against internal company prices
- Detect price gaps and cheapest sellers
- Generate executive-level insights using Generative AI
- Distribute results via Email and Google Sheets
- Perform weekly trend analysis and pricing recommendations
The system is split into TWO AUTOMATED WORKFLOWS:
- Daily Price Monitoring (Operational)
- Weekly Price Pattern Analysis (Strategic)
The goal is fast decision-making, not raw data.
- Playwright: Browser automation for dynamic sites (Amazon JS rendering)
- Python
- Pandas: Data normalization & comparison
- Google Generative AI (GenAI): Analysis & executive summaries
- Google Sheets (Excel equivalent)
- Google Apps Script: Reporting + Email delivery
Daily (cron / scheduler)
Track current competitor prices, detect underpricing/overpricing, and notify management with clear actions.
- PRODUCT INPUT
- Product name
- My company price
- Amazon product URL
- BestBuy product URL
- PRICE EXTRACTION
- Playwright launches a real browser
- Simulates human behavior (JS execution, DOM load)
- Scrapes:
- Amazon price
- BestBuy price
- Handles:
- Dynamic content
- JS-rendered prices
- Delayed page loads
- DATA NORMALIZATION
Raw prices are cleaned and converted to float.
Example structure: { "product_name": name, "amazon_price": amazon_price, "bestbuy_price": bestbuy_price, "my_price": my_price, "diff_amazon": amazon_price - my_price, "diff_bestbuy": bestbuy_price - my_price, "cheapest": min(price_dict, key=price_dict.get) }
- PRICE COMPARISON LOGIC
For each product:
- Compare My Price vs Amazon
- Compare My Price vs BestBuy
- Identify cheapest seller
- Flag overpriced products
- Quantify price gaps
- GENERATIVE AI ANALYSIS (DAILY)
The normalized dataset is sent to Google GenAI.
GenAI outputs:
- Executive Summary (high-level)
- Per-product breakdown:
- Price comparison
- Overpriced status
- Cheapest competitor
- Clear recommended action
Example outcomes:
- Maintain price
- Reduce price
- Urgent price correction
- Marketing advantage opportunity
- REPORT DISTRIBUTION
- Executive summary sent to Company Manager via Email
- Full dataset appended to Google Sheets using Apps Script
- Sheet acts as the historical price database
Weekly (once every 7 days)
Move from daily reactions to strategic pricing decisions using trends.
- DATA FETCH (LAST 7 DAYS)
- Google Apps Script fetches:
- Last 7 days of price data
- All products
- All competitors
- DATA AGGREGATION
Using Pandas:
- Average competitor price per product
- Price volatility
- Frequency of undercutting
- Trend direction (increasing / decreasing)
- GENERATIVE AI ANALYSIS (WEEKLY)
The 7-day dataset is sent to Google GenAI.
GenAI analyzes:
- Competitor pricing patterns
- Repeated underpricing
- Temporary vs consistent discounts
- Risk of price wars
- Margin pressure signals
- WEEKLY STRATEGIC OUTPUT
GenAI generates:
- Weekly Executive Summary
- Product-level insights:
- Stable vs unstable pricing
- Aggressive competitors
- Recommended pricing strategy
- Actionable recommendations:
- Hold price
- Temporary discount
- Permanent price adjustment
- Monitor only
- WEEKLY REPORT DELIVERY
- Strategic report emailed to management
- Summary logged in Google Sheets (weekly tab)
- Enables long-term pricing decisions
- Data first, opinions later
- Automation over manual review
- Executive-friendly output
- No dashboards needed to understand results
- Clear actions, not raw numbers
- Add more competitors
- Add alerting for extreme price gaps
- Integrate margin data
- Slack / WhatsApp notifications
- Predictive pricing with historical trends
A reliable, scalable, and decision-focused pricing intelligence system that:
- Runs daily without supervision
- Thinks weekly like a strategist
- Turns scraped prices into business actions