Supermarket Sales Analysis

Project Overview

This project involves analyzing supermarket sales data from 2021 to derive actionable insights and improve business operations. The analysis includes data cleaning, visualization, and the creation of an interactive dashboard using Excel.

Objective

The primary objective is to clean and analyze the dataset to uncover trends, patterns, and insights that can aid decision-making. This includes creating visualizations and an interactive dashboard to present the findings effectively.

Dataset Description

The dataset was sourced from a supermarket's sales records for the year 2021. It includes various attributes such as:

• Invoice ID
• Branch
• City
• Customer type
• Gender
• Product line
• Unit price
• Quantity
• Tax
• Total
• Date
• Time
• Payment method
• Cost of goods sold (COGS)
• Gross margin percentage
• Gross income
• Rating

Project Files

The repository contains the following files:

• Super Market Sales 2021 Dashboard.xlsx: Excel file containing the original data, cleaned data, various analyses, and the interactive dashboard.
• Super Market Sales 2021 Dashboard.png: Image of the final dashboard.
• Super Market Sales 2021 Dashboard_Report.pdf: Detailed report of the project, including data cleaning, analysis, visualizations, and insights.

Data Cleaning Process

• Removed duplicates to ensure data integrity.
• Handled missing values appropriately to avoid skewing the analysis.
• Corrected inconsistencies in data entry for accurate analysis.

Data Analysis

Excel was used for data cleaning, analysis, and visualization. Pivot tables and formulas were utilized for in-depth analysis. Key findings include:

• Sales distribution across different branches and cities.
• Customer purchasing behavior based on type and gender.
• Performance of various product lines in terms of sales and customer ratings.
• Trends in sales over time.

Data Visualization

The visualizations created include:

• Sale Trend Over Time
• Sales by Product Line
• Payment Method Distribution
• Customer Rating Distribution
• Product Line Trends
• Ratings vs. Sales

Interactive Dashboard

The dashboard integrates various visualizations to provide a comprehensive view of the data. Interactive elements allow users to filter and drill down into specific aspects of the data.

Insights and Recommendations

• Branch A in Yangon has the highest sales.
• Female customers tend to have higher average ratings.
• E-wallet is the most popular payment method.
• Recommendations include focusing marketing efforts on high-performing branches and product lines, improving customer service based on feedback from ratings, and expanding payment options.

Conclusion

The analysis provided valuable insights into sales performance, customer behavior, and product line success. The visualizations and dashboard effectively present these insights, making it easier to understand and act upon them.

Future Work or Suggestions

• Conduct further analysis to understand the factors influencing customer ratings.
• Explore additional data sources to gain a more holistic view of sales performance.
• Regularly update the dashboard with new data to monitor trends over time.

How to Use

1. Open the Super Market Sales 2021 Dashboard.xlsx file in Excel.
2. Explore the various sheets to understand the data and analysis.
3. Use the interactive dashboard to filter and view specific data insights.

Acknowledgements

• Special thanks to the team members who contributed to data collection and analysis.
• Thanks to the supermarket for providing the data.

Contact

For any questions or feedback, please contact fizapathan2102@gmail.com.

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