Get Customer Equity: Measurement, Management and Research PDF

By Dominique M. Hanssens, Julian Villanueva

Shopper fairness may also help administration: ·allocate advertising spending for long term profitability, ·understand the relationship among budgets, metrics and fiscal functionality, ·provide a patron targeted procedure for measuring company worth, ·improve the productiveness of CRM structures by means of delivering frameworks, instruments and metrics purchaser fairness stories present versions, deals a typology, and examines the elemental query of even if a patron fairness orientation can positioned a company in a aggressive virtue to different businesses. The authors assessment versions which can elevate buyer fairness via optimizing every one of its drivers - buyer acquisition, buyer retention, and add-on promoting. shopper fairness is necessary interpreting for advertising managers, advertising researchers, students and scholars.

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Extra resources for Customer Equity: Measurement, Management and Research Opportunities (Foundations and Trends in Marketing)

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Between acquisition and retention). Third, these models are generally merely descriptive and do not help in guiding action. Fourth, competitive behavior is usually not included. , cross-effects among consumer segments). The main advantage is that they are relatively easy to implement, if data are available. 2 Customer Migration Model A particularly interesting CLV model is what has been called the Customer Migration Model (Dwyer, 1997). These particular CLV models are better suited for scenarios in which customers follow an always-a-share scenario and where it is difficult to observe whether a customer is alive or not.

All these questions are extremely relevant for the firm, and they emphasize the importance of this area for future modeling work. The most suitable model will depend on the characteristics of the customerfirm relationship. More specifically, it will depend on the following five factors: (a) contractual versus non-contractual relationships. 3. Models to Estimate the Probability of Retention 53 (b) always-a-share versus lost-for-good. , health insurance) the information used to predict switching might be harder to observe because there is no behavioral information other than the premiums paid; (c) frequency of purchases.

This approach, however, underestimates the value generated from customer acquisition and results in underspending. However, their CE specification shown in Eq. 13) can easily be maximized to simultaneously find the optimal level of acquisition and retention spending. It turns out that in their model the optimal level of retention spending per customer is independent of the level of customer acquisition spending even when both retention and acquisition are jointly optimized. This happens in their model because of the following two conditions: (i) the retention response function assumes all customers are equal.

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