互联网环境下企业关键消费者选取比例优化策略研究

Optimization of Key Opinion Consumer Selection Strategy for Enterprise in the Internet Environment

摘要: 随着“人 + 内容”为核心的社交营销迅速发展，面向消费者网络的产品推广是企业重点关注的问题之一。学者对其现有研究主要基于传播模型以实现营销效果最大，缺乏可以被用于营销优化的基于消费者网络构建的需求产生模型。为此，本文利用局部平均场(Local Mean Field, LMF)方法构建关键消费者(Key Opinion Consumer, KOC)选取比例决策的非线性优化模型。最后，针对不同消费者购买阈值，结合单位产品利润与营销推广成本进行仿真分析。研究发现：1) 单位营销推广成本与产品利润比越小，企业扩大KOC比例有利于扩大其市场份额和增加收益；2) 单位营销推广成本高于产品利润时，决策者需严格控制KOC数量进行适度营销，继而扩大市场份额。

Abstract: With the rapid development of “people + content” as the core of social marketing, the product promotion for consumer network is one of the key issues that enterprises focus on. Scholars’ existing research on it is mainly based on the diffusion model to achieve the maximum marketing effect. However, it lacks a demand generation model based on consumer network, which can be used for marketing optimization. Thus, a nonlinear optimization model for Key Opinion Consumer (KOC) selection of proportion decision is constructed, using the Local Mean Field (LMF) method. Finally, simulations on different consumer purchase threshold, and combination of unit product profit and marketing cost are performed. The results show as following: 1) the smaller the ratio of unit marketing cost to product profit is, the larger the KOC ratio is, the larger the company’s market share will be and the more revenue it will generate; 2) when the unit marketing cost is higher than the product profit, the decision maker should strictly control the number of KOC for appropriate marketing, and then expand the market share.