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Analyzes 450K+ e-commerce sessions to quantify marketing channel ROI, connecting acquisition traffic to conversion, refunds, and profit using Python (pandas, matplotlib).

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Marketing-Channel-ROI-Analysis

Connecting Marketing Acquisition to Real Profitability

This project analyzes how different marketing channels perform across the full e-commerce funnel from website sessions to orders, refunds, and profit using Python-only analytics.

🔍 Overview

Using real-world e-commerce data, this analysis attributes customer orders back to their originating marketing sessions and evaluates each channel based on conversion, revenue, refunds, and profit.

Rather than stopping at conversion rates, the project focuses on refund-adjusted profitability, answering the question:

Which marketing channels actually drive profitable growth?

🚀 Key Features

Marketing Channel Attribution using UTM parameters & referrers

End-to-End Funnel Metrics

Sessions → Orders → Revenue → Refunds → Profit

Monthly & Device-Level Performance Analysis

Refund-Adjusted Gross Profit Modeling

Automated KPI Tables & Visualizations

Fully reproducible Python-only workflow

🧮 Metrics Calculated

Sessions

Orders

Conversion Rate (CVR)

Revenue

Cost of Goods Sold

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Analyzes 450K+ e-commerce sessions to quantify marketing channel ROI, connecting acquisition traffic to conversion, refunds, and profit using Python (pandas, matplotlib).

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