Restaurant Feasibility Study and Behavioural based Restaurant Recommendation

This research paper harnesses spatial analysis and data science to revolutionize restaurant setup and user recommendation strategies within the online food ordering domain, focusing on the 5% of users contributing rating. By aggregating user rating data and spatial information, the methodology conducts in depth exploratory data analysis of unwilling distribution pattern and spatial co-relation among user demographic, locations and rating. Employing special tool, it map restaurant location identify underserved or competitive areas and applies clustering algorithm to understand localized user preferences. Behavioral pattern analysis segment users, develop predictive models, and construct recommendation engine, a bling personalize restaurant suggestions. Business recommendation encompass optimal restaurant placements, targeted marketing strategies, and operational optimization based on identify user’s preference. Rigorous model evaluation ensure accuracy, with iterative refinement for continuous enhancement empowering restaurant owner with data driven insights per strategic decision making and offering tailored dining recommendations to users.