NecessiPick: Data Extraction and AI Data Refinement in Food Retail Comparison

NecessiPick is a system designed to modernize food retail governance in Metro Manila. Utilizing data science and decision-support mechanisms enhances transparency, accountability, and efficiency. NecessiPick employs advanced technologies such as data extraction frameworks and AI algorithms to empower consumer decisions. Traditional price comparison methods like the Department of Trade and Industry’s ‘e-Presyo’ often lack real-time updates and comprehensive product information. NecessiPick addresses this by focusing on specific supermarkets (Puregold, Waltermart, and ShopMetro) and key product categories. Developed using scrum methodology, it integrates Django, MongoDB, Selenium, BeautifulSoup, and OpenAI’s ChatGPT for product descriptions. Its effectiveness in ensuring price transparency is demonstrated through fuzzywuzzy library utilization for product comparison, facilitating informed purchasing decisions. The system ensures consistent and accurate data extraction across diverse website structures and provides valuable visualizations for data-driven decision-making. This study highlights the transformative potential of data-driven approaches in enhancing governance and empowering consumers in the food retail industry.