Sales Resource Optimization Based on Customer Lifetime Value (CLV): A Data-Driven Dynamic Decision Model

Xiangmin Li

doi:10.70393/6a6374616d.333335

Authors

Xiangmin Li Ym Trading Limited

DOI:

https://doi.org/10.70393/6a6374616d.333335

ARK:

https://n2t.net/ark:/40704/JCTAM.v2n6a07

Disciplines:

Statistical Analysis

Subjects:

Data Mining

References:

14

Keywords:

Customer Lifetime Value (CLV), Dynamic Resource Allocation, Data-Driven Decisions, Sales Optimization

Abstract

This study proposes a framework for a dynamic decision-making model based on Customer Lifetime Value (CLV) to optimize sales resources. This model prioritizes profitability as a benchmark for customer performance, serving as a guide for effective resource allocation and improvement. The paper presents a data-driven approach that combines real-time data and dynamic analysis of customer behavior for resource allocation and adjustment. This method analyzes enterprise data and customer behavior to inform decisions that maximize resource utilization and enhance sales performance. The core idea is to prioritize high-value customers and allocate more resources accordingly. Furthermore, by categorizing customers into different CLV groups, more informed and targeted decisions are made for each customer group. Ultimately, this improves customer retention, thereby enhancing the enterprise's long-term attractiveness and strategic model.

Author Biography

Xiangmin Li, Ym Trading Limited

Ym Trading Limited, Denver, CO 80202, USA.

References

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