Strategic Analysis of Northwind Sales Data

Project Overview
This project provides a detailed, data-driven analysis of Northwind sales data to uncover customer behavior, product performance, order trends, and employee contributions. The goal is to generate actionable insights that support business strategy and decision-making.

Key Objectives

• Analyze customer segmentation and order behavior.
• Evaluate product performance and identify slow movers.
• Examine order trends and seasonality patterns.
• Assess employee performance metrics.
• Generate actionable insights to inform business strategy.

SQL Skills & Techniques Demonstrated

• Data querying, aggregation, and filtering.
• RFM (Recency, Frequency, Monetary) analysis for customer segmentation.
• Ranking and percentiles for order and customer value analysis.
• Joins across multiple tables (Orders, Order Details, Products, Employees, Customers).
• Grouping and categorizing data for actionable insights.
• Views creation to simplify complex queries.

Analysis Highlights

1. Customer Segmentation

• Grouped customers based on RFM metrics and average order value.
• Identified key customer segments: Champions, Potential Loyalists, and At Risk.

2. Product Performance Analysis

• Ranked top revenue-generating and high-frequency products.
• Highlighted slow movers for strategic inventory decisions.

3. Order Analysis

• Examined seasonality by month and day of the week.
• Categorized orders into Small, Medium, and Large based on total quantity.

4. Employee Performance Evaluation

• Evaluated employees based on total revenue, order volume, and average order value.

Project Structure

• SQL_Code/ – Contains all SQL scripts used for analysis.
• Presentation/ – Project presentation summarizing key findings and insights.
• Dataset – The analysis was performed on the Northwind sample database, available in SQLite (e.g., via SQLiteOnline).

Usage

• Clone the repository and open the SQL scripts in any SQLite environment.
• Run the scripts on the Northwind database to explore customer, product, order, and employee analyses.
• Review queries to understand RFM segmentation, product performance evaluation, and operational insights.

Learning Outcomes

• Hands-on experience with SQL for real-world business data analysis.
• Practical understanding of customer segmentation, product performance evaluation, and operational insights.
• Ability to convert raw sales data into actionable business recommendations.