Advanced Customer Analytics provides a clear guide to the specific analytical challenges faced by the retail sector. The book covers the nature and scale of data obtained in transactions, relative proximity to the consumer and the need to monitor customer behaviour across multiple channels. The book advocates a category management approach, taking into account the need to understand the consumer mindset through elasticity modelling and discount strategies, as well as targeted marketing and loyalty design.
A practical, no-nonsense approach to complex scenarios is taken throughout, breaking down tasks into easily digestible steps. The use of a fictional retail analyst 'Scott' helps to provide accessible examples of practice. Advanced Customer Analytics does not skirt around the complexities of this subject but offers conceptual support to steer retail marketers towards making the right choices for analysing their data. Online resources include a selection of datasets to support specific chapters.
<i>Advanced Customer Analytics</i> provides a great introduction into the main analytical tools marketing managers should be familiar with these days. Starting from regression analysis the book gradually covers more sophisticated methods including time series models, survival analysis, TOBIT models and structural equation models. What makes this book special is the easy to understand way in which these methods are explained and applied to problems marketing managers face every day. This makes this book great for practitioners as well as for readers interested in learning applied statistics. I strongly recommend this book to anyone interested in data-based marketing decision making.