Advanced Ecommerce Analytics

This project focused on analyzing the e-commerce sales data of a production company to uncover trends, performance drivers, and growth opportunities. The dataset included detailed order information such as date, season, marketing channel, campaign or discount usage, product category/subcategory, price, quantity, customer demographics (age, region, income), satisfaction ratings, and more.

I conducted multiple in-depth case studies to answer key business questions and provide actionable insights, including:

Revenue Analysis by region, device type, marketing channel, and customer segment

Customer Behavior: average spending and satisfaction by age group, customer lifetime value segmented by acquisition source and device used.

Campaign Performance: revenue generated, satisfaction rate, and return rate per campaign.

Product Insights: identifying top revenue-generating categories/subcategories and those with the highest sales volume.

Discount Impact: effect of discounts on sales volume, return rates, and revenue.

Seasonality Analysis: how sales and revenue vary across seasons.

Return Revenue Analysis by region, city, and campaign.

Key Insights:

Upper Egypt generated the highest revenue, driven mainly by electronics purchases — the top revenue category.

Alexandria had the lowest revenue, partly due to lower mobile usage compared to other regions.

First-time customers contributed the highest profit and lifetime value, primarily due to clothing purchases promoted heavily in marketing campaigns.

Customers aged 25-40 had the highest spending (mainly on electronics), while those aged 60+ had the highest satisfaction (mainly purchasing travel services).

Travel ranked highest in satisfaction rate, explaining the strong positive feedback from older customers.

These findings provided valuable guidance on customer targeting, marketing strategy, and product focus to boost overall revenue.