Conducting market segmentation analysis and committing to a long-term market segmentation strategy is a complex and challenging journey for any organisation. This course guides you through the entire process of market segmentation analysis and offers a ten-step process that makes customer segmentation efficient and organised.
This course begins with the decision to conduct market segmentation analysis and continues through to the final stages of evaluating the success of the strategy and monitoring the market for possible changes. We also cover segmentation variables such as geographic segmentation, psychographic segmentation, behavioural segmentation, and demographic segmentation.
In this course, we will explore how to leverage statistical concepts into the organisation's segmentation strategy, such as the hierarchical clustering and partitioning methods, exploratory data analysis, biclustering, mixture models, and regression models.
The concepts and skills you will gain in this course are relevant in a wide range of contexts in both the for- and not-for-profit sectors.
This course enables you to conduct customer segmentation analysis. You can replicate the calculations and visualisations demonstrated in the customer segmentation modelsby downloading the data and the R code. R is a free open-source statistical computing environment, and is widely acknowledged as the universal language of computational statistics.
This course is based on and taught by the authors of the book Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful. You will have full access to this valuable resource when you enrol in this course.