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e-commerce-analytics

You can access my notebook from the link : https://www.kaggle.com/code/cansusary/e-commerce-analytics .

🛍️ E-Commerce Dataset Analysis

📚 Project Overview

This project dives deep into an e-commerce dataset to uncover valuable insights about sales, customer behavior, and performance metrics. By employing exploratory data analysis (EDA), data visualization, and key performance indicator (KPI) calculations, this analysis provides a comprehensive understanding of e-commerce operations.

🎯 1. Purpose and Objectives

Objective: To analyze e-commerce data and derive actionable insights.

Key Goals:

-Identify top-performing products and revenue trends.

-Understand customer behavior and lifetime value.

-Evaluate sales distribution across different regions and times.

📊 2. Dataset and Features

This dataset contains key features, including transaction details, customer information, and product descriptions: InvoiceNo, StockCode, Description, Quantity, InvoiceDate, UnitPrice, CustomerID, Country.

🔍 3. Exploratory Data Analysis (EDA)

Key steps taken in this analysis include:

  • Loading and Understanding the Dataset: Ensured a clear understanding of data structures and types.
  • Handling Missing Values: Removed and imputed missing data for a clean dataset.
  • Data Formatting: Standardized column formats for consistency.
  • Negative Quantity Filtering: Removed invalid transactions to improve accuracy.

🛠️ 4. Feature Engineering

Revenue Calculation: Revenue = Quantity × UnitPrice.

Order Date Extraction: Extracted year, month, day, and hour from InvoiceDate.

📈 5. Data Visualization

6. Key Performance Indicators (KPIs)

💰 Total Revenue: Aggregated revenue across all transactions.

📆 Monthly Revenue Growth: Tracked growth trends over time.

🎁 Best-Selling Products: Identified high-performing items.

🛒 Average Order Value (AOV): Revenue divided by the total number of orders.

👤 Customer Lifetime Value (CLV): Estimated the total revenue generated by customers.

I am passionate about learning and growing through collaboration and would love to hear your thoughts! Feel free to comment, ask questions, or provide feedback on this project. 🌟

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