An automated competitor intelligence tool built using Selenium WebDriver, NumPy, and Pandas. Designed to extract, clean, and compare pricing data from over 30 online marketplaces, offering insights through visualized financial metrics.
- 🕸️ Built a Selenium-powered scraper to crawl prices across 30+ e-commerce sites
- 🧮 Conducted nation-wide pricing research for a retail client, saving 72+ hours of manual analysis
- 📊 Implemented dynamic financial visualizations for comparing 3+ customizable metrics across competitors
- 💰 Helped drive a +19.9% increase in client annual profits through smarter pricing strategies
| Purpose | Technology |
|---|---|
| Web Scraping | Selenium WebDriver |
| Data Processing | Python, Pandas, NumPy |
| Data Visualization | Matplotlib |
| Automation / Scheduling | Python Scripts |
scrapers/— Selenium scripts for each targeted e-commerce platformdata/— Exported and cleaned.csvfiles for price, brand, and category comparisonsanalyzer.py— Core logic for filtering, grouping, and calculating averages/medianscharts/— Graphical outputs (bar graphs, line charts, trend plots)README.md— Project summary and setup
- Compare any 3 financial metrics (e.g. price, discount rate, shipping cost)
- Visualize patterns in:
- Average brand price over time
- Category-wise price distribution
- Shop-level comparative performance
June – July 2024
Built and delivered as a consulting solution for an e-commerce data intelligence project. Used in-market by one SME client for ROI-backed research.
Kevin Chifamba
📧 [email protected]
🔗 LinkedIn • GitHub