Project Overview
This project focuses on analyzing marketing campaign performance and return on investment using data from multiple marketing channels. The main purpose of the project is to understand how different campaigns performed, which channels generated better results, where the marketing budget was used effectively, and how campaign decisions can be improved through data analysis.
In this project, I worked with realistic marketing data that represents common sources used in real-world digital marketing, such as paid ads, website traffic, email marketing, campaign engagement, leads, customers, and revenue. The project goes beyond basic metrics like impressions and clicks and connects campaign activity with actual business outcomes such as qualified leads, customer conversions, revenue generation, ROAS, ROI, and cost efficiency.
The analysis includes data cleaning, preparation, KPI calculation, campaign comparison, channel-level performance analysis, and business recommendation development. I used Excel for organizing, cleaning, and building analysis sheets, SQL for querying campaign and business performance, and Python for data analysis, calculations, and visualization. The final output helps identify which campaigns performed well, which channels delivered stronger returns, and which areas need budget optimization.
This project demonstrates how marketing analytics can support better business decisions. Instead of only reporting what happened in a campaign, the project explains why the results matter and how a business can use the insights to reduce wasted ad spend, improve lead quality, increase revenue, and make smarter marketing decisions in the future.
