Industry: Retail · Services: Data Analytics, Power BI
The need
In retail, pricing decisions cannot be made independently of the prices on competitors’ shelves. But tracking competitor prices by hand in scattered spreadsheets was time-consuming and made it hard to access up-to-date information at the moment of decision.
The solution
We developed Python-based data collection processes that regularly gather product and price information from competitor websites. The collected data is stored centrally in SQL Server, products are matched to the company’s own product records, and the results are fed into Power BI reports.
- Automated, scheduled data collection with Python
- Historical price archive in SQL Server
- Product matching and price gap calculation
- Price positioning, gap analysis and change tracking in Power BI
The result
Manual tracking turned into a single report that updates itself every day. The pricing team can now monitor competitor prices on one screen, together with their history of changes.
Technologies: Python, Selenium, SQL Server, Power BI