In this presentation, we delve into the integration of advanced data analytics and machine learning to optimize marketing efficiency and drive revenue growth for web retailers. By leveraging Python-based predictive models and Tableau for data visualization, I will offer a comprehensive workflow and visualization that transforms raw data into valuable revenue forecasts. This session begins with the creation of a synthetic dataset using Python notebooks, ensuring you can practice without needing access to proprietary data. If participants prefer to use their own data, such as from Google Analytics, they can skip the dummy data generation step and proceed directly to analysis.

By the end of this presentation, participants will have a clear methodology for creating and analyzing web traffic data with Python, optimizing feature selection for predictive models, and visualizing results in Tableau to inform strategic marketing decisions. Whether you are a small business new to Python or a large company with big data and cloud computing technology, this session offers practical insights and sophisticated techniques to enhance your data-driven marketing efforts.

Agenda

TUG intro and Speaker intro (5 mins)

"Driving Revenue Growth through Python-Based Predictive Models and Tableau" (60 mins)

Q&A (5 mins)