Social Media and Web Analytics

Taught at:

• Tilburg, Spring 2021
• Tilburg, Spring 2022
• Tilburg, Spring 2023
• Tilburg, Spring 2024

Motivation

Across the globe, consumers spend over 6 hours per day on the internet, spending over $US7.5 trillion annually on digital commerce sites and spending roughly 1/3 of their time on social media websites (See Statista and Pew Research, 2019, Social Media Fact Sheet. ). The goal of this course is to develop an analytics toolkit to analyze the data coming from digital markets and social media to deliver managerially relevant business recommendations. The course content will be unashamedly analytics heavy - utilizing modern statistical and mathematical modelling techniques. Our approach will be to introduce these techniques in a practical manner, with a focus on deep concepts and intuition but there will be mathematical formulae when needed. By the conclusion of the class you will be able to deliver data-driven answers to the following questions (among many others):

• Is my online marketing effective? How can I make it even better?
• Should I respond to consumer reviews on social media? If so, which ones?
• Does what is written on social media sites influence demand for my product?
• Are there fake reviews on my website/platform? How can I detect them?

The course is split into four substantive modules:

1. Reseach Design for Causality: provides the basic framework for thinking about the design and analysis of empirical research in digital markets and social media
2. Casual Inference: provides the statistical toolkit to analyze data and interpret findings from field experiments and observational data
3. Text Analytics: provides the statistical toolkit to analyze text using statistical and numerical techniques
4. Special Topics: introduces additional tools based on preferences of the student cohort

During these modules we will focus on learning and then leveraging an analytics toolkit as well as extracting insights from recent academic literature. This course provides students with the background needed to begin working in a marketing analytics position within a corporation, a consulting firm, or a marketing research firm. By the end of the course, you will be able to walk into any company and help make data-driven marketing decisions.