Overview

Staying competitive in e-commerce means knowing what your competitors are charging — and knowing it every single day. Manually checking product prices across multiple websites is time-consuming, inconsistent, and simply not scalable when you’re tracking dozens or hundreds of products.

The Price Tracking System automates this process entirely. It scrapes competitor product pages on a daily schedule, stores every price point in a structured database, and surfaces the data through a clean web dashboard with historical trend charts and price change alerts. With this system, you always have an accurate and up-to-date view of the competitive pricing landscape without lifting a finger.

How It Works

The system uses a Python-based web scraper configured with a list of target product URLs and competitor websites. Every day, the scraper visits each page, extracts the current price, and stores it alongside a timestamp in the database. The Django dashboard then displays this data as interactive trend charts, comparison tables, and alert notifications whenever a significant price change is detected.

Key Features

  • Fully automated daily scraping — runs on a schedule and collects prices from all configured target pages without any manual intervention
  • Price history database — every price change is recorded with a timestamp, building a comprehensive historical dataset that grows more valuable over time
  • Trend visualization — interactive charts display price movements over custom date ranges, making it easy to spot patterns and seasonal trends
  • Price change alerts — the system automatically flags significant price drops or increases, so you can react quickly to market changes
  • Multi-product, multi-competitor tracking — monitor as many products and competitor websites as needed from a single dashboard
  • Clean comparison dashboard — side-by-side price comparisons across competitors for any selected product or category
  • Data export — price history data can be exported to CSV for further analysis in Excel, Google Sheets, or business intelligence tools

Tech Stack

  • Python for automated web scraping and data extraction
  • Django for the backend application, data management, and dashboard
  • PostgreSQL for structured price history storage
  • Chart.js for interactive trend visualization on the frontend
  • Celery + Cron for daily scrape job scheduling

Use Cases

  • E-commerce sellers monitoring competitor prices to adjust their own pricing strategy dynamically
  • Purchasing teams tracking supplier or wholesale prices over time to identify the best time to buy
  • Market researchers collecting pricing data across industries for reports or analysis
  • Product managers monitoring how a product’s market price evolves after launch

Demo

A live demo is available to explore the dashboard, sample price history data, and trend charts.

Live demo: pricetracking.etuannv.com
Username: viewer | Password: etuannv2019demo

👉 Need a custom price tracker built for your market or industry? Contact me to discuss your project.

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