Customer-centric marketing : a pragmatic framework / R Ravi and Baohong Sun

By:

Ravi, R (Ramamoorthi) [autor]

Contributor(s):

Sun, Baohong [author]

Publication details: Cambridge, Massachusetts : The MIT Press, 2016.Description: ix, 136 pages : illustrations ; 23 cmISBN:

9780262529051

Subject(s):

DDC classification:

23 658.812 R197C

Contents:

Preface -- An introduction to customer-centric marketing -- Conceptual framework for customer-centric marketing -- Modeling consumer choice -- Segmenting customers into latent classes based on sensitivity -- Customer lifetime value -- Marketing optimization problem -- Continuous learning and adaptive marketing decisions -- Implications and enablers -- Epilogue -- Notes -- References -- Index.

Summary: "The revolution in big data has enabled a game-changing approach to marketing. The asynchronous and continuous collection of customer data carries rich signals about consumer preferences and consumption patterns. Use of this data can make marketing adaptive, dynamic, and responsive to changes in individual customer behavior. This book introduces state-of-the-art analytic and quantitative methods for customer-centric marketing (CCM). Rather than using a snapshot from the data to plot a single campaign-centric marketing plan, these methods draw on cutting-edge research in optimization and interactive marketing with the goal of maximizing long-term profit from data collected over time. The aim to teach readers to apply optimization tools to derive analytical solutions leading to customized, dynamic, proactive, and real-time marketing decisions. The book develops the CCM framework and illustrates it with four cases that span the life cycle of marketing: pricing, win-back, cross-sales, and customer service allocation. The text walks the reader through real-world examples of applying the framework (supported by spreadsheet models available online), then explains the key concepts: modeling consumer choice; segmenting customers into latent classes based on sensitivity; computing customer lifetime value (CLV); and dynamic optimization. The reader then learns to incorporate the continuous learning of customer preference into an adaptive feedback loop for marketing decisions. The book can be used as a text for MBA students or as a professional reference"--Back cover

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Books	Library and Documentation Division PGRRL	658.812 R197C (Browse shelf(Opens below))	Available		111949

Preface --
An introduction to customer-centric marketing --
Conceptual framework for customer-centric marketing --
Modeling consumer choice --
Segmenting customers into latent classes based on sensitivity --
Customer lifetime value --
Marketing optimization problem --
Continuous learning and adaptive marketing decisions --
Implications and enablers --
Epilogue --
Notes --
References --
Index.

"The revolution in big data has enabled a game-changing approach to marketing. The asynchronous and continuous collection of customer data carries rich signals about consumer preferences and consumption patterns. Use of this data can make marketing adaptive, dynamic, and responsive to changes in individual customer behavior. This book introduces state-of-the-art analytic and quantitative methods for customer-centric marketing (CCM). Rather than using a snapshot from the data to plot a single campaign-centric marketing plan, these methods draw on cutting-edge research in optimization and interactive marketing with the goal of maximizing long-term profit from data collected over time. The aim to teach readers to apply optimization tools to derive analytical solutions leading to customized, dynamic, proactive, and real-time marketing decisions. The book develops the CCM framework and illustrates it with four cases that span the life cycle of marketing: pricing, win-back, cross-sales, and customer service allocation. The text walks the reader through real-world examples of applying the framework (supported by spreadsheet models available online), then explains the key concepts: modeling consumer choice; segmenting customers into latent classes based on sensitivity; computing customer lifetime value (CLV); and dynamic optimization. The reader then learns to incorporate the continuous learning of customer preference into an adaptive feedback loop for marketing decisions. The book can be used as a text for MBA students or as a professional reference"--Back cover

There are no comments on this title.

to post a comment.