Advanced Customer Analytics - Mike Grigsby

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Résumé :
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.

Biographie:
Mike Grigsby has been involved in marketing science for more than 25 years. He was marketing research director at Millward Brown and has held leadership positions at Hewlett-Packard and the Gap. With a wealth of experience at the forefront of marketing science and analytics, he now heads up the strategic retail analysis practice at Targetbase. Mike is also known for academic work, having written articles for academic and trade journals and taught at graduate and undergraduate levels. He is a regular speaker at trade conventions and seminars.

Sommaire:
* Section - 01: Overview; * Section - 02: Regression and Factor Analysis; * Section - 03: Retail; * Section - 04: Retail; * Section - 05: Understanding and estimating demand; * Section - 06: Price elasticity and discounts; * Section - 07: Valuing marketing communications (marcomm); * Section - 08: Forecasting future demand; * Section - 09: Targeting the right customers; * Section - 10: Maximizing the impact of mailing; * Section - 11: The benefits of product bundling; * Section - 12: Estimating time of purchase; * Section - 13: Investigating the time of product purchase; * Section - 14: Increasing customer lifetime value; * Section - 15: Modelling counts (transactions); * Section - 16: Quantifying complexity of customer behaviour; * Section - 17: Designing effective loyalty programmes; * Section - 18: Identifying loyal customers; * Section - 19: Introduction to segmentation; * Section - 20: Tools for successful segmentation; * Section - 21: Drawing insights from segmentation; * Section - 22: Creating targeted messages; * Section - 23: RFM vs. segmentation; * Section - 24: Marketing strategy;