Customer Sales Analysis

📊 Project Overview

This project analyzes customer sales data to uncover key insights about revenue trends, regional performance, and product category success. The goal is to support strategic decision-making for marketing and operations.

🛠 Tools Used

• Excel (data cleaning, calculations)
• Power BI (dashboard and data visualization)
• SQL (customer segmentation and revenue queries)

🗂 Dataset Description

The dataset includes 12 months of sales data from a fictional retail business. Key fields include:

• Customer ID
• Region
• Sales Amount
• Product Category
• Purchase Date

🔍 Methodology

1. Cleaned and transformed the data in Excel (removed nulls, standardized columns).
2. Loaded the dataset into Power BI for advanced visualization.
3. Created calculated columns (monthly revenue, quarter-over-quarter growth).
4. Used SQL queries to identify top revenue-generating customers.
5. Designed visual dashboards to represent regional trends and product performance.

📈 Visuals

Total sales amount grouped by region.

Total sales by different product categories.

Line chart showing sales performance over time.

💡 Insights & Recommendations

• Central region contributes 35% of total revenue—consider increased investment.
• Electronics and Furniture are top categories—promote these during campaigns.
• Low-revenue regions could benefit from localized marketing strategies.
• A loyalty program for high-spending customers can improve retention.

📁 Files Included

• sales_data.csv: Cleaned dataset used for analysis
• dashboard.pbix: Power BI file with final dashboard
• visuals/: Folder with screenshots of visualizations
• analysis.sql: SQL scripts for data queries

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👩‍💻 Created by: Solape Olojede 📅 Date: April 2025