Collica R.S. Customer Segmentation and Clustering Using SAS Enterprise Miner

Cary: SAS Institute, 2017. — 355 p.There are many points of view on customer segmentation and the potential value that it can yield. Randy Collica’s second edition of Customer Segmentation and Clustering Using SAS Enterprise Miner brings increased clarity to this topic and reveals why customer segmentation is even more important now that we have additional varieties and volumes of customer data from which we can create more value. Randy recognizes that success is highly dependent on your strategy, your data, and the outcomes that you are trying to influence. He is wise on the subject of customer segmentation and includes practical topics over and above those found in the first edition.
In this second edition, Randy covers new areas that reflect the broader adoption of segmentation and clustering methods. We can now apply these methods to richer data that is increasingly available—not only transactional and demographic data, but also textual and social data. Randy shows us how we can more effectively address the growing volumes and complexities of customer data, how we can make sense of that data, and how we can achieve greater insight to better meet customer needs. Segmentation is a journey of visual discoveries. Data visualization is certainly relevant in the discovery phase of analysis as we become more knowledgeable about customer similarities and differences. Then, information visualization helps communicate results in ways that different stakeholders can more easily understand, enabling those stakeholders to better direct their strategies and actions.
The examples that Randy uses are well chosen and easy to follow. The examples that illustrate the mechanics are straightforward, but also rich with wisdom because Randy selects and combines methods that efficiently and effectively get results. The applied examples show you the science as well as the art of methods coming together to meet multiple needs, including categorizing customers, using clusters in predictive models, incorporating new data sources for more descriptive clusters, and preparing the time dimension of data.
Randy’s considerable knowledge and experience shine in this second edition in the way that he tackles large volumes and varieties of data while keeping the goal of business utility and value in view. He shows you how to use segmentation to add measurable value. Read and learn Randy will inspire you to discover the untapped opportunities and value in your customer data.