Customer Analytics

Course Description & Learning Outcomes

This course is part of the Data Science and Graduate Certificate in Customer Analytics Practice Series offered by NUS-ISS. It is the first course in a series of three courses for the Graduate Certificate in Customer Analytics. Candidates interested in Stackable Certificate Programme in Data Science must complete two Fundamental Certificates before registering for this certificate as this is a certificate at specialist level. At the end of the course, participants will be able to: - Understand the customer management life-cycle and the infrastructure to manage it. - Apply dimension reduction techniques (PCA/Factor analysis) to identify core dimensions/factors based on various customer characteristic/ behaviour/product holding variables to arrive at efficient solution for decision making. This method also helps to manage large number of variables for other analytics techniques like prediction etc. - Develop multivariate customer segmentation using all types of variables/features or factors to design and execute marketing strategies profitably. For example, the most profitable customer segment might receive special treatment than other customer segments. - Apply customer profiling so that customer segments are better understood, behaviourally (e.g. how much they spend per month, how long have they been buying from the business) and touchpoints they access for appropriate strategy formulation for targeted marketing for deepening relationship. - RFM analysis both for segmentation and other customer development strategies.