By V. Kumar

ISBN-10: 1119993202

ISBN-13: 9781119993209

Statistical tools in consumer dating Management specializes in the quantitative and modeling features of purchaser administration concepts that result in destiny company profitability, with emphasis on constructing an figuring out of shopper dating administration (CRM) types because the guiding notion for ecocnomic consumer administration. to appreciate and discover the functioning of CRM types, this publication lines the administration concepts all through a customer’s tenure with an organization. in addition, the booklet explores intimately CRM versions for shopper acquisition, shopper retention, shopper acquisition and retention, client churn, and buyer win back.

Statistical equipment in consumer dating Management:

  • Provides an outline of a CRM process, introducing key suggestions and metrics had to comprehend and enforce those models.
  • Focuses on 5 CRM versions: shopper acquisition, buyer retention, shopper churn, and consumer win again with helping case studies.
  • Explores each one version intimately, from investigating the necessity for CRM versions to the way forward for the models.
  • Presents versions and ideas that span around the introductory, complicated, and professional levels.

Academics and practitioners curious about the realm of CRM in addition to teachers of utilized statistics and quantitative advertising classes will make the most of this e-book.

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2008) Managing Customer for Profit, Prentice Hall, Upper Saddle River, NJ. 3. , and Thearling, K. (2000) Building Data Mining Applications for CRM, McGraw-Hill, New York. 4. Bianco, A. (2004) The vanishing mass market. com (accessed July 12, 2004). 5. Farrell, G. (2010) Kraft boosted by Cadbury purchase. com (accessed August 6, 2010). 6. , and Bhalla, G. (2010) Rethinking marketing. Harvard Business Review, Reprint R1001F. 7. Kurczweski, N. (2011) Tata Nano seeks footing as world’s cheapest car.

Thus, the effect of WOM referral on switching was obtained by subtracting the switching probability of a customer who had not received WOM ðx ¼ 0Þ from that of a customer who had received WOM ðx ¼ 1Þ. To answer the second question, the authors only included the sample of prospects who had received WOM referral in the modeling procedure and also used a logit model to estimate whether switching behavior is a function of WOM referral resource characteristics, source expertise and similarity. which were included as independent variables, conditioning on receiving WOM referral: probðy ¼ 1jx ¼ 1Þ ¼ expða Á zÞ 1 þ expða Á zÞ ð3:13Þ where z indicated the two independent variables, source expertise and source similarity.

1, include:  How likely is it that the prospects will respond to our acquisition promotion?  How many new customers can we acquire in this campaign?  How many orders will each of our newly acquired customers place? Statistical Methods in Customer Relationship Management, First Edition. V. Kumar and J. Andrew Petersen. Ó 2012 John Wiley & Sons, Ltd. Published 2012 by John Wiley & Sons, Ltd. 1 Issues addressed in customer acquisition models (LTV, Lifetime Value; CE, Customer Equity).  How do the marketing variables, such as shipping fee, word-of-mouth referral, and promotion depth, influence prospects’ response behavior?

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Statistical Methods in Customer Relationship Management by V. Kumar

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