Marketing Analytics for Big Data surveys several topics within the new and emerging field of big data. Marketing analytics itself (e.g., profiling, segmentation) is not new. Yet big data has brought about several new techniques, new applications, and new types of data that are all becoming increasingly important for product and marketing managers, analysts and others to understand and apply. The aim of the course is to give students a broad overview of several areas rather than an in-depth presentation
of any one particular technique, application or data type (which could easily occupy an entire course or more). We will cover some of the math and calculations of the models. We will not be estimating these models on large datasets, or coding in R or Python.
At the end of the course, students should be able to:
- Describe several different ways big data on customers has allowed researchers and managers to study customers.
- Evaluate and critique a selection of models used for predicting customer behavior and informing business decisions.
- Calculate outcomes for a handful of cases, communicating clearly the results and implications
The course comprises 6 topics:
- Introduction to big data: new data, models, and societal impact
- Experimentation with A/B testing, multivariate testing and multi-armed bandits
- Customer journey analytics & multichannel attribution
- Dynamic targeting: recommender systems
- Sentiment analysis, opinion and text mining
- Network analytics, social contagion