ABSTRACT
This chapter explores how companies analyse and use customer-related data. We define analytical CRM as the process through which companies transform customer-related data into actionable insight for either strategic or tactical purposes. Analysis of customer-related data supports Strategic CRM by answering questions like “who are our most valuable customers?” and operational CRM by answering questions like “what offer should we next make to the customer?” Analytical CRM supports strategic and tactical decision-making by sales, marketing, and service teams throughout the customer journey. CRM analytics are commissioned and delivered to users in three ways: through standard reports, online analytical processing (OLAP), or data mining. Analytical methods for structured data – the type of data that typically exists in relational databases – are mature. Analytics for unstructured data are becoming more widely adopted. Textual analysis is the most widely deployed form of unstructured data analytics. Analytics for Big Data are still evolving. Big Data are characterised by their volume, velocity, and variety. These attributes make analysis challenging. Data mining technologies work in several ways: by describing and visualising, classifying, estimating, predicting, affinity grouping and clustering.
