Year: 2025
Type: article
Abstract: The "Maximized Profits Through Price Optimization" project aims to develop a web-based tool for price optimization in retail. Leveraging historical sales data (retail_price.csv), the application analyses monthly demand trends, explores price-demand relationships, and forecasts future demand using statistical models like Exponential Smoothing and Linear Regression. One key differentiator is its integration of machine learning algorithms for more accurate demand forecasting compared to traditional methods. The objective is to provide retailers with actionable insights into optimal pricing strategies, enhancing profitability and market competitiveness. The tool also supports scenario analysis, allowing retailers to simulate different pricing strategies and their potential impacts on demand and profitability.
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4410097818