Marketing Data Analytics: Segmentation, Modeling, and Forecasting

Modern marketing relies on data, yet turning raw metrics into actionable strategies can feel overwhelming. This course bridges the gap between marketing strategy and data science, helping you make data-driven decisions with confidence. You will transition from basic reporting to advanced marketing analytics. Through written explanations and practical examples, you will learn how to analyze audience behavior, predict future performance, and scientifically measure the impact of your campaigns using industry-standard analytical methods. What you'll learn: - Understand fundamental marketing analytics terminology and modern data preparation workflows. - Segment target audiences effectively using K-means clustering techniques. - Build marketing mix models to optimize budget allocation across different channels. - Apply linear regression models to forecast sales and plan future marketing campaigns. - Evaluate advertising effectiveness using structured A/B testing and experimental design. - Analyze customer lifetime value and multi-touch attribution using modern data-driven frameworks. The course starts with foundational marketing metrics and data preparation concepts before guiding you through hands-on analytical models. You will read through practical scenarios, study code and data structure examples, and learn to interpret statistical outputs to guide real-world marketing decisions. This course is designed for aspiring marketing analysts, digital marketers, and business professionals looking to build solid analytical skills. No prior programming or advanced statistical background is required. Start developing your data-driven marketing toolkit today.