Supermarket-Sales-Analysis

Demo

Dashboard (Consumer Behaviour): https://public.tableau.com/views/yangon-supermarket-analysis/Dashboard1?:language=en-GB&:display_count=n&:origin=viz_share_link

Dashboard (Region Comparison): https://public.tableau.com/shared/6SPZK4C3N?:display_count=n&:origin=viz_share_link

Notebook: https://www.kaggle.com/code/vikram92/eda-for-supermarket-sales-memberships

Introduction

An analysis is done on three supermarkets located at 'Mandalay', 'Naypyitaw' and 'Yangon' (Myanmar). Sales are analyzed in following ways

• Region wise sales
• Weekday-wise sales of members vs non-members
• Weekday-wise sales of males vs females
• Sales volume: members vs non-members
• Sales volume: males vs females
• Weekday-wise sales distribution: members vs non-members
• Weekday-wise sales distribution: males vs females

Following product insights are obtained

• most profitable items
• item sales vs price
• item ratings
• Product-wise sales distribution: members vs non-members
• Product-wise sales distribution: males vs females

Customer preferences are determined by following

• Total customers vs memberships for males and females
• Sales by payment methods: members vs non-members
• Sales by payment methods: males vs females

Thus, a comprehensive analysis is obtained for the supermarket sales.

Dataset

The dataset was obtained from Kaggle (Link: https://www.kaggle.com/datasets/aungpyaeap/supermarket-sales). This consists of the historical sales of 3 different cities 'Mandalay', 'Naypyitaw' and 'Yangon' (Myanmar).

Problem Statement

Numerous economic events and global challenges impose pressure in pricing and increase competition. Besides, with maturing online market, future trading will acutely challenge prices. Furthermore, multi-channel sales and promotions demand supermarkets to capture broader market. Therefore, managing the supermarket business is very challenging and less rewarding.

Regardless of the adverse situation, a supermarket is required to sustain the demands of a pool of customers. With this accomplishment; a supermarket easily maintains consistent sales.

Therefore, a comprehensive supermarket analysis is vital to reveal the vital insights of supermarket business.

Goal

An acclaimed supermarket consistently attracts large customers. Therefore; an exhaustive analysis is performed, to improve sales, item selection and customer experience. Several aspects of sales, products and customer preferences are analyzed. The subsequent insights; aid to consistently attract a pool of customers, and thus; provide consistent revenues.

System Environment

Directory Structure

├── data                                           # Data files    
|  ├── data.csv                                    # Supermarket dataset 
├── notebooks                                      # Main project files
|  ├── dashboard.ipynb                             # Notebook for creating dashboard
|  ├── eda-for-supermarket.ipynb                   # Notebook for EDA
├── visualizations                                 # Analysis visualizations
|  ├── 01-monthly-sales.png                        # Monthly sales distribution od Supermarket
|  ├── 02-monthly-sales.png                        # Region-wise monthly sales
|  ├── 03-region-comparison.png                    # Performance comparison of regions
|  ├── 05-product-sales-vs-rating.png              # Product sales vs price vs margin
|  ├── 06-segment-wise-sales-.png                  # Sales comparison: members vs non-members & males vs females
|  ├── 07-daywise-sales.png                        # Weekday-wise Supermarket sales 
|  ├── 08-daywise-members-sale.png                 # Weekday-wise Supermarket sales: members vs non-members
|  ├── 09-daywise-gender-sales.png                 # Weekday-wise Supermarket sales: males vs females
|  ├── 10-category-wise-total-sales.png            # Sales contribution: members vs non-members & males vs females
|  ├── 11-product-wise-categorical-sales.png       # Product-wise sales contribution: members vs non-members & males vs females
|  ├── 12-payment-method-preferences.png           # Payment preferences: members vs non-members & males vs females
├── LICENSE                                        # License
├── README.md                                      # Repository description
├── requirements.txt                               # Required libraries

Installing Dependencies

Foremost running the project, installing the dependencies is essential.

• Ensure Python 3.8.8 or later is installed in the system.
• All required libraries are listed in "requirements.txt". These are easily installed; by running the following command in project directory

pip install -r requirements.txt

Run Project

The notebooks are provided in notebooks section. These run easily with Jupyter Notebook or Google Colab