000			02746 a2200241 4500
999			_c153575 _d153575
003			LDD
005			20191016114829.0
008			191016b ||||| |||| 00| 0 eng d
020			_a9780262529051
040			_cIGNOU Library
082			_223 _a658.812 R197C
100			_aRavi, R _eautor _q(Ramamoorthi) _98785
245			_aCustomer-centric marketing : _ba pragmatic framework / _cR Ravi and Baohong Sun
260			_aCambridge, Massachusetts : _bThe MIT Press, _c2016.
300			_aix, 136 pages : _billustrations ; _c23 cm
505			_aPreface -- 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.
520			_a "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
650			_aRelationship marketing. _98786
650			_aCustomer relations. _92390
650			_aMarketing _xManagement. _98787
700			_aSun, Baohong _eauthor _98788
942			_2ddc _cBK