Supermarket Sales Project

The Project utilizes R for data exploration, visualization, and statistical summarization to derive actionable business insights. The dataset, containing supermarket sales records, was cleaned and processed using tidyverse, lubridate, and ggplot2. Key metrics such as total sales, transaction count, average customer rating, and units sold were computed. Visualizations, including bar charts, histograms, and time-series plots, revealed sales trends, product line performance, customer demographics, and seasonal variations. The findings highlighted high-performing product categories, customer behavior patterns, and the impact of membership programs on sales. Recommendations include optimizing inventory, refining marketing strategies, and enhancing loyalty programs to drive revenue growth and customer satisfaction.