Skip to content

Performed an advanced Excel-based exploratory data analysis (EDA) of an E-Commerce sales dataset to create an interactive dashboard for uncovering key business insights.

Notifications You must be signed in to change notification settings

SwethaJoseph/Sales-EDA-Project

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 

Repository files navigation

Sales-EDA-Project

Overview

This project involves an exploratory data analysis (EDA) of an E-Commerce Sales dataset using advanced Excel techniques. The primary objective is to create an interactive sales dashboard to analyze sales trends, profitability, and performance metrics across various product categories and regions for the year 2015 and uncover insights that support decision-making for business operations.

Key Features

  • Data Cleaning and Preparation: Comprehensive cleaning and formatting of the dataset to ensure accuracy in analysis.
  • Sales and Profit Analysis: Identification of key sales and profit trends, including peak periods and correlations.
  • Regional Performance: Detailed analysis of regional sales and profit distributions, highlighting top and bottom-performing regions.
  • Product Performance: Insights into the best and worst-performing products across different regions.
  • Customer Segment Analysis: Evaluation of customer segments, identifying dominant segments in sales and profit contributions.
  • Statistical Analysis: Application of statistical measures to understand the variability and distribution of sales and profit data.

Dataset Description

The dataset consists of 51,290 records from the year 2015, detailing sales information across various product categories. Key attributes include:

  • Order ID, Order Date, Ship Date, Ship Mode
  • Product Category, Product Name, Sales, Quantity, Discount, Profit
  • Shipping Cost, Order Priority, Customer ID, Customer Name
  • City, State, Country, Region, and Months

Analysis Summary

  • Sales & Profit Trends: Identified December as the peak month for both sales and profit, with lower performance in February.
  • Regional Profit Analysis: Fashion was the top-performing category across most regions, with varying performance for other categories like Electronics and Home & Furniture.
  • Product Performance: Fashion products, especially Apple Laptop, Tyre, and T-shirts, led in sales across multiple regions.
  • Customer Segment Insights: The Consumer segment accounted for the majority of sales and profit, indicating a strong focus on individual consumers.
  • Global Sales & Profit Distribution: The United States dominated with the highest sales and profit, followed by a sharp drop-off in other countries.
  • Statistical Findings: Both sales and profits displayed considerable variability, indicating diverse performance across products and regions.

Conclusion & Recommendations

  • Focus on Targeted Marketing: Enhance marketing strategies in underperforming regions and product categories.
  • Supply Chain Optimization: Improve supply chain efficiency to meet demand in high-performing regions.
  • Customer Engagement: Continue focusing on the Consumer segment while exploring growth opportunities in Corporate and Home Office segments.
  • Product Strategy: Tailor product offerings to match specific regional demands and consumer preferences.

Tools Used

  • Microsoft Excel: For data cleaning, preparation, and analysis.
  • Pivot Tables & Charts: To create interactive dashboards and visualizations.
  • Statistical Functions: For in-depth analysis of sales and profit data.

How to Use

  • Open the Excel File: Load the Sales EDA Project.xlsx file in Microsoft Excel.
  • Explore the Data: Review the data cleaning, preparation steps, and analysis within the Excel sheets.
  • Interact with Dashboards: Use the Pivot Tables and Charts to filter and explore different aspects of the data.

About

Performed an advanced Excel-based exploratory data analysis (EDA) of an E-Commerce sales dataset to create an interactive dashboard for uncovering key business insights.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published