Web & Marketing Analytics
This course will provide students with the knowledge and skills required to analyze web, social network, social media and other marketing data. This will allow them to generate key insights using various quantitative methods. Initially, focus will be given on how to access and manage structured and unstructured data. Students will learn how to perform text mining so as to extract useful information from text data (e.g. tweets, Facebook, blog posts, movies, TV, restaurant reviews and newspaper articles) and how to use exploratory and supervised machine learning methods (e.g. Naïve Bayes, Neural Networks, K-Means, Rules, Logistic Regression and Decision Trees) so as to perform sentiment analysis, classification, market basket analysis and segmentation. This will allow them to build recommendation systems. Next, emphasis will be given on key aspects of online advertisement, such as pay per click and search engine optimization. Students will learn how to track and report website traffic, to measure the conversion rates and to calculate the ROI in a multi-channel marketing environment. Finally, students will learn to analyze and describe networks, model the evolution of networks, and apply the network analyses in marketing settings (e.g. for customer profiling, targeting, and trend detection).