Customer value management
Customer value management (CVM) is a strategic business discipline that combines marketing, data analytics, and finance to optimize the value of a customer base. Unlike general brand marketing, CVM focuses on the measurement and management of the economic value created by individual customers over their entire relationship with a firm.[1] It is closely associated with the calculation of customer lifetime value (CLV) and the use of predictive modeling to determine resource allocation for customer acquisition, retention, and development.[2]
While historically rooted in relationship marketing, CVM is distinguished by its reliance on quantitative metrics to balance the value delivered to the customer against the value derived by the company.[3] It is most prevalent in subscription-based industries, such as telecommunications, financial services, and SaaS, where recurring revenue streams rely on long-term retention.[4]
Theoretical foundation
CVM is grounded in the concept that not all customers possess equal economic value to a firm. Academic literature posits that marketing resources should be allocated differentially based on a customer's potential contribution to profit.[5]
Customer Lifetime Value (CLV)
The central metric in CVM is Customer Lifetime Value (CLV or LTV), which is the net present value of the future cash flows attributed to the customer relationship. CVM strategies utilize CLV to determine the upper limit of spending feasible for acquiring a new customer (Customer Acquisition Cost or CAC) or retaining an existing one.[6]
The Value Exchange
Scholars such as Philip Kotler and V. Kumar describe CVM as managing a "dual value" equation:
- Value to the Customer: The benefits a customer receives (product quality, service, brand prestige) relative to the cost (price, effort).
- Value to the Firm: The profit the company generates from the customer (margin, loyalty, referrals).
Effective CVM seeks to align these two factors, ensuring that high-value customers receive commensurate service levels to prevent churn.[7]
Core processes
CVM is typically operationalized through the customer lifecycle, a framework that segments customers based on their stage of relationship with the brand.
Acquisition
In the CVM context, acquisition focuses on "quality over quantity." Instead of maximizing the raw number of new customers, practitioners use predictive analytics to target prospects who are likely to have a high CLV. This involves analyzing look-alike audiences and optimizing pricing strategies to attract profitable segments.[8]
Retention and churn prevention
Retention involves activities designed to extend the duration of the customer relationship. CVM relies heavily on churn prediction models, which analyze behavioral signals (e.g., declining usage, complaints, contract expiration dates) to identify customers at risk of leaving. Interventions, such as proactive discounts or service calls, are prioritized for high-value customers.[9]
Value development (Cross-sell and Up-sell)
Value development aims to increase the Average Revenue Per User (ARPU). This includes:
- Up-selling: Encouraging customers to move to a higher tier of service.
- Cross-selling: Offering complementary products.
- Next Best Action (NBA): Using machine learning to determine the specific offer or interaction most likely to succeed for a specific individual at a specific time.[4]
CVM vs. CRM
While often used interchangeably, Customer Value Management and Customer relationship management (CRM) are distinct concepts in management theory.
- CRM typically refers to the operational systems (software) and workflows used to record customer data and manage interactions. It is the repository of record.[10]
- CVM is the strategic layer that utilizes CRM data to make financial decisions. It focuses on the economic optimization of the relationship rather than the operational handling of the interaction.[11]
Technology and implementation
Implementing CVM requires a technology stack capable of integrating data from disparate sources (billing, web usage, customer support) to form a unified view of the customer.
Key technological components include:
- Data warehouses: For storing historical transaction and behavioral data.
- Predictive analytics: Algorithms used to forecast future behavior, such as propensity to purchase or likelihood to churn.
- Marketing orchestration engines: Tools that automate the delivery of personalized messages across channels (email, SMS, app push notifications).[12]
Industry applications
Telecommunications
The telecommunications industry was an early adopter of CVM due to high market saturation and the high cost of infrastructure. Operators use CVM to manage large subscriber bases, often creating dedicated "CVM Teams" responsible for stabilizing revenue and managing contract renewals.[4]
Financial services
Banks and insurers apply CVM to increase "share of wallet." For example, a bank may use transaction data to identify a customer likely to need a mortgage and present an offer before the customer seeks a competitor.[13]
See also
- Customer lifetime value
- Relationship marketing
- Retention management
- Segmenting-targeting-positioning
References
- ↑ Kotler, Philip (2017). "Customer value management". Journal of Creating Value. doi:10.1177/2394964317706879.
- ↑ Verhoef, Peter C.; van Doorn, Jenny; Dorotic, Matilda (2007). "Customer value management: an overview and research agenda". Marketing: Journal of Research and Management. 3 (2): 105–120. doi:10.15358/0344-1369-2007-JRM-2-105.
- ↑ Kumar, V.; Lemon, K. N.; Parasuraman, A. (2006). "Managing customers for value: an overview and research agenda". Journal of Service Research. 9 (2): 87–94. doi:10.1177/1094670506293558.
- ↑ 4.0 4.1 4.2 Reitenspiess, Martin; Tortosa, José Antonio; de la Herrán, Jesús; Putz, Andreas (2012). "Customer value management: the path to profitable growth in telecom" (PDF). Strategy&. PwC. Retrieved 27 November 2025.
- ↑ Stirling, Mark (2000). "Customer value management". Journal of Targeting, Measurement and Analysis for Marketing. 9 (2): 174–184. doi:10.1057/palgrave.jt.5740013.
- ↑ Estrella-Ramón, Antonia M. (2013). "Customer lifetime value and customer equity". Journal of Business Market Management. 6 (2): 53–80.
- ↑ Verhoef, Peter C.; Lemon, Katherine N. (2013). "Successful customer value management: key lessons and emerging trends". European Management Journal. 31 (1): 1–15. doi:10.1016/j.emj.2012.08.001.
- ↑ Doligalski, Tymoteusz (2015). Internet-Based Customer Value Management: Developing Customer Relationships Online. Management for Professionals. Cham: Springer. doi:10.1007/978-3-319-09855-5. ISBN 978-3-319-09855-5. Search this book on
- ↑ "Customer Value Management Body of Knowledge (CVMBoK)". Exacaster. 2025. Retrieved 27 November 2025.
- ↑ "Customer value management: the basics – CVM v CRM". Customer Value Guy. 4 August 2023. Retrieved 27 November 2025.
- ↑ "Customer value management technology reference architecture". CVMBoK digital. Exacaster. 21 July 2025. Retrieved 27 November 2025.
- ↑ "Customer Value Management (CVM): how technology is transforming loyalty". Altcraft Platform. Altcraft. 2025. Retrieved 27 November 2025.
- ↑ "Customer value management with Efi Koulouridi". McKinsey & Company. 8 March 2023. Retrieved 27 November 2025.
This article "Customer value management" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:Customer value management. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.
