Customer value maximization
In today's world, Customer value maximization has become a topic of great relevance and interest to a wide sector of society. With the advancement of technology and globalization, Customer value maximization has taken a leading role in different areas, from politics to popular culture. Knowing more about Customer value maximization is essential to understand the challenges and opportunities that currently arise. In this article, we will explore different aspects related to Customer value maximization, from its history to its impact on contemporary society.
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Customer value maximization (CVM) is a real-time service model that, proponents say, goes beyond basic customer relationship management (CRM) capabilities, identifying and capturing maximum potential from prospective and existing customers.[1]
Customer-centricity
The CVM framework evaluates current methods and effectiveness, makes changes where required, and sets up a measurement system that helps in evaluating effectiveness. The CVM framework operates as a continuous process in a closed loop.[2]
The CVM framework is closely related to the idea of customer-lifetime-value.
One of the strategies to maximize the value that each customer generates is to split customers into defined segments, a process called client segmentation.
Marketing challenges
Marketing challenges can be predominantly dissected into four categories:
- Lifecycle challenges include driving usage of a product/service, new client acquisition, enabling cross-sell, up-sell, client retention, activation, usage, churn prevention, etc.[3]
- Segment-based challenges Companies will reach out to each customer in a different way to suit their needs, especially when the company has multiple products/product variants. They need to reach out in a focused manner to independent segments that require varying strategies.[4]
- Channel-based challenges Most companies adopt a multi-channel strategy in order to take their products or services to their customers. Each channel (store, online, mobile, etc.) needs to be tackled differently to ensure maximization of results. The increasing number of touch-points that each customer faces, has led marketers to grow increasingly reliant on machine-learning and AI models when calculating CVM models.[5]
- Function-based challenges When companies invest in marketing programs, they look for methods that help them evaluate and track how they work and measure ROI. Systems to manage their programs, maximize results and optimize spends are all that companies keep looking for.[6]
Features
- Growth in value[7]
See also
- Brand engagement
- Business case
- Business model
- Cross-selling
- Customer centricity
- Customer data integration
- Customer Data Platform
- Customer experience
- Customer experience transformation
- Customer intelligence
- Customer relationship management (CRM)
- Guided selling
- Loyalty marketing
- Online lead generation
- Real-time marketing
- Relationship marketing
- Sales force management system
- Selling technique
- Strategic management
- Supplier relationship management
- Support automation
- Trigger-based marketing
- Up-selling
- Value-added selling
References
- ^ Superior customer value/ Buch. CRC. 2012. ISBN 9781439861288. OCLC 799019107.
- ^ Art., Weinstein; Art., Weinstein (2004). Superior customer value in the new economy concepts and cases. CRC Press. ISBN 0203501497. OCLC 300310255.
- ^ "Exploit the Product Life Cycle". Harvard Business Review. Retrieved 2017-05-16.
- ^ "Market Segmentation in B2B Markets | B2B Segmentation". B2B International. Retrieved 2017-05-16.
- ^ "Four Essential Analyses for a Successful FMCG Brand Online Performance". ciValue. 2020-12-17. Retrieved 2021-03-15.
- ^ "7 Big Problems in the Marketing Industry". www.ama.org. April 2016. Retrieved 2017-05-16.
- ^ Anna, Fiorentino (December 2010). "Driving Intelligent Growth with Customer Value Maximization". Archived from the original on 19 February 2015.
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