CUSTOMER VALUATION THEORY & FIRM VALUE

Augmented Customer Value through the Wheel of

Fortune Strategies

Once a firm has used CLV to determine directly contributed customer value, it can then use that information to implement value-maximizing strategies. This added impact of customer value corresponds to the depth of the contribution. Using CLV, firms can effectively select for profitable customers, manage loyalty and profitability among the customer base simultaneously, and optimize the allocation of resources, among other managerially value-generating actions. In this regard, the Wheel of Fortune Strategies have been developed to aid firms in addressing marketing issues with greater confidence (Kumar (2008), (2013)). This set of strategies answers the following questions:

With which customers should the firms interact through inexpensive channels like the Internet or the touch tone phone, and which customer to let go? When resources were reallocated based on the optimal mix and frequency of communication channels, a business-to-business (B2B) company realized 100% more revenue and 83% more profits across all their four customer segments (Venkatesan and Kumar 2004).
Should the firm encourage or discourage product return behavior, and how should it manage this process? Petersen and Kumar (2009) found that the ideal level of product returns should be one that maximizes firm profit. For a B2C catalog retailer, they found that the optimal percentage of product returns that maximized profitability was 13%. Further, Petersen and Kumar (2015) addressed the aspects of perceived risk and optimal resource allocation into the product returns process for a B2C catalog retailer and found that the firm was able to generate approximately $300,000 more in profits compared to next-best available resource allocation strategy
Having ensured that the customer is transacting with the firm, what kind of sales and service resources should the firm allocate to conduct future business with that customer? Kumar and Venkatesan (2005) identified the drivers of profitable multi-channel shopping behavior and found that adding one more channel resulted in an average net gain of about 80% in profits.

How do firms leverage the CLV metric to drive their stock price and provide more value to their stakeholders? By linking CLV-based actions to a firm’s stock price, B2B and B2C firms have reported significant increases of about 35% and 57% in their stock prices, better prediction of stock price movements, and superior performance with respect to the stock market index and rival firms (Krasnikov, Alexander, Satish Jayachandran, and V. Kumar (2009); Kumarand Shah 2009).

References
Krasnikov, Alexander, Satish Jayachandran, and V. Kumar (2009), “The impact of customer relationship management implementation on cost and profit efficiencies: evidence from the US commercial banking industry,” Journal of Marketing, 73 (6), 61-76.
Kumar, V. (2008), Managing Customers for Profit: Strategies to Increase Profits and Build Loyalty. Upper Saddle River, NJ: Wharton School Publishing.
Kumar, V. (2013), Profitable Customer Engagement: Concept, Metrics, and Strategies. New Delhi, India: Sage Publications.
Kumar, V., Morris George, and Joseph Pancras (2008), “Cross-buying in retailing: Drivers and consequences,” Journal of Retailing, 84 (1), 15-27.
Kumar, V., M. Luo, and V. R. Rao (2018), “Linking an individual’s brand value to the CLV: An integrated approach,” Working Paper, Georgia State University, Atlanta, GA.
Kumar, V., J Andrew Petersen, and Robert P Leone (2013), “Defining, measuring, and managing business reference value,” Journal of Marketing, 77 (1), 68-86.
Kumar, V., J Andrew Petersen, and Robert P Leone (2010), “Driving profitability by encouraging customer referrals: who, when, and how,” Journal of Marketing, 74 (5), 1-17.
Kumar, V., J Andrew Petersen, and Robert P Leone (2007), “How valuable is word of mouth?,” Harvard Business Review, 85 (10), 139-46.
Kumar, V., and Denish Shah (2009), “Expanding the Role of Marketing: From Customer Equity to Market Capitalization,” Journal of Marketing, 73 (6), 119.
Kumar, V., and Rajkumar Venkatesan (2005), “Who are the Multichannel Shoppers and How do they Perform? : Correlates of Multichannel Shopping Behavior,” Journal of Interactive Marketing, 19 (2), 44-62.
Kumar, V., Rajkumar Venkatesan, and Werner Reinartz (2006), “Knowing What to Sell, When, and to Whom,” Harvard Business Review, 84 (3), 131-7, 50.
Petersen, J Andrew, and V. Kumar (2009), “Are product returns a necessary evil? Antecedents and consequences,” Journal of Marketing, 73 (3), 35-51.
Petersen, J Andrew, and V. Kumar (2015), “Perceived Risk, Product Returns, and Optimal Resource Allocation: Evidence from a Field Experiment,” Journal of Marketing Research, 52 (2), 268-85.
Ramani, Girish, and V. Kumar (2008), “Interaction orientation and firm performance,” Journal of Marketing, 72 (1), 27-45.
Reinartz, Werner J., and V. Kumar (2002), “The Mismanagement of Customer Loyalty,” Harvard Business Review, 80 (7), 86-94.
Reinartz, Werner J., and V. Kumar (2000), “On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing,” Journal of Marketing, 64 (4), 17-35.
Reinartz, Werner, Jacquelyn S Thomas, and V. Kumar (2005), “Balancing acquisition and retention resources to maximize customer profitability,” Journal of Marketing, 69 (1), 63-79.
Shah, Denish, V. Kumar, Yingge Qu, and Sylia Chen (2012), “Unprofitable cross-buying: evidence from consumer and business markets,” Journal of Marketing, 76 (3), 78-95.
Venkatesan, R., and V. Kumar (2004), “A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy,” Journal of Marketing, 68 (4), 106.