In the ever-evolving landscape of the retail industry, supermarkets play a pivotal role in meeting the daily needs of consumers. With the advent of technology and the availability of large volumes of data, supermarkets are now in a unique position to optimize their operations and enhance the shopping experience. Exploratory Data Analysis (EDA) is a powerful approach that can provide valuable insights into supermarket sales data.

In this EDA project, we will delve into the world of QuickMart sales data between Janaury - March of 2019 to uncover patterns, trends, and opportunities that can drive informed decision-making and contribute to the supermarket's growth and success.

• Customer Demographics: What is the gender distribution among customers, and does it impact the choice of product line?

• Branch Performance: How do sales and customer types differ across the three branches of the business?

• Product Line Analysis: Which product line generates the highest total sales and gross income?

• Pricing Strategy: Are there any correlations between unit price, quantity, and customer ratings? Can this information be used to adjust pricing strategies?

• Payment Methods: What are the preferred payment methods among customers, and do they vary by branch?

• Time Analysis: Are there specific months, times of the day or days of the week when sales tend to peak or dip??

• Customer Loyalty: Do certain customer types tend to generate more sales, and are they more satisfied with their shopping experience?

• City Comparison: Are there significant differences in Quantity sold, customer ratings, or product preferences between cities??

Click HERE to view the analysis.