Marketing Analytics with R: Customer Insights and Forecasting

In today's digital landscape, successful marketing relies on data, not guesswork. Understanding customer behavior, predicting trends, and measuring engagement requires the right analytical toolkit. This text-based course guides you through applying the R programming language to solve real-world marketing challenges. You will learn to parse customer feedback, model purchasing behavior, and extract actionable insights from social media and transaction data. By reading clear explanations and studying practical code examples, you will build a solid foundation in marketing data science. What you'll learn: - Understand foundational marketing metrics and how to structure marketing data in R. - Analyze customer sentiment and extract key themes from product reviews using tidytext. - Perform market basket analysis to discover product associations and purchasing patterns. - Forecast customer lifetime value and churn risk using statistical modeling techniques. - Visualize marketing data and campaign performance using ggplot2. - Apply modern R workflows, including tidy data principles and the native pipe operator, to clean raw marketing datasets. The course begins with core marketing concepts and R basics, gradually advancing to text mining, behavioral segmentation, and predictive modeling. You will work through structured written explanations and step-by-step code walkthroughs. Designed for aspiring marketing analysts, digital marketers, and beginners to R who want to make data-backed strategic decisions, this course requires no prior programming experience. Start reading today to unlock the power of data-driven marketing.