What drives growth and profitability in e-commerce? This project analyzes customer behaviour and product performance to uncover revenue drivers and support smarter commercial decisions.

View the full project code on Github →

Key Insights

• Revenue growth is strongly supported by repeat customers
• High-volume products show lower profitability margins
• Certain categories outperform in both revenue and margin
• Discounting impacts revenue positively but reduces margin

Business Impact

• Identified opportunities to improve pricing strategy
• Highlighted high-value customer segments for targeting
• Provided actionable recommendations for revenue and margin optimization

Overview

This project demonstrates an end-to-end business intelligence workflow for a fashion e-commerce company.

The objective was to analyze product performance, customer behavior, and revenue drivers to support strategic decision-making.

A synthetic dataset was created using Python and analyzed in Power BI to deliver a decision-ready dashboard.

The case links customer behaviour and product performance to commercial decision-making.

Dashboard summarizes key commercial KPIs, including revenue, AOV, customer base, and repeat rate.

Business Objective

How can we evaluate product performance across revenue, profitability, and volume to identify:

• High-performing products worth scaling
• High-volume but low-margin products requiring pricing review
• Underperforming products needing strategic action
• Category-level growth opportunities

Analytical approach

The dataset simulates a mid-sized fashion e-commerce company:

• 45,000 orders
• 8,000 unique customers
• 2.68 M€ total revenue
• 92.89% repeat rate

Approach:

• Generated a structured synthetic dataset using Python
• Stored and queried data using SQL (SQLite)
• Aggregated performance metrics (revenue, margin, AOV)
• Modeled data in Power BI using a star schema
• Built interactive dashboards with KPI-focused visuals

Key questions

• Is revenue growing sustainably?
• What drives repeat purchases?
• Are discounts improving revenue or eroding margin?
• Which customer segments generate the most value?
• Is customer retention stable?

Recommendations

Based on the analysis:

• Increase marketing investment in high-margin women´s products.
• Review pricing strategy for high-volume, low-margin items.
• Develop targeted campaigns to grow niche high-margin products.
• Continue leveraging strong repeat customer behavior for retention-driven growth.