Scraped product prices from multiple e-commerce sites in real-time, stored data in a database, and visualized trends with an interactive Dash dashboard.

In this project, I developed an automated system that scrapes real-time product pricing data from multiple e-commerce sites. The collected data—including SKU, product name, price, and URL—is stored in a structured SQLite database with precise timestamped entries. An interactive dashboard built with Dash visualizes price trends over time, enabling efficient analysis and monitoring of market dynamics.

Scraped product pricing data from multiple e-commerce websites with retries for failed requests.

Extracted key information: sku, product name, price, and URL for each product.

Stored the data in an SQLite3 database, organizing it by sku and timestamp.

Price data is regularly updated and trends are visualised in a dashboard for streamlined analysis.

This project provided a dynamic, real-time overview of product price trends across multiple e-commerce platforms. By tracking prices over time, it offers insights into pricing fluctuations, product demand, and market behavior. It helps companies and market analysts monitor trends, make informed pricing decisions and adapt quickly to market changes with making data-driven decisions.

My client recently launched a new product to the market and aimed to build a customer base by offering competitive pricing. To support this, I developed a system that monitors relevant competitors, providing notifications in the event of price changes. This enabled my client to take quick action and stay ahead in the market.