运筹与管理 ›› 2019, Vol. 28 ›› Issue (4): 109-117.DOI: 10.12005/orms.2019.0086

• 应用研究 • 上一篇    下一篇

第三方数据平台精准营销收费模式研究

李新明   

  1. 西安交通大学 管理学院,过程控制与效率工程教育部重点实验室,陕西 西安 710049
  • 收稿日期:2017-03-22 出版日期:2019-04-25
  • 作者简介:李新明 (1984-),男,陕西西安人,博士后,研究方向:信息产品定价,IT经济学。
  • 基金资助:
    国家自然科学基金重大研究计划培育项目 (91546119);国家自然科学基金海外及港澳学者合作研究基金项目(71628205);中国博士后科学基金(2016M602785)

Study on the Charging Model for Precision Marketing of Third-party Data Platform

LI Xin-ming   

  1. The key Lab of Education for Process Control & Efficiency, School of Management, Xi’an Jiaotong University, Xi’an 710049, China
  • Received:2017-03-22 Online:2019-04-25

摘要: 第三方数据平台通过大数据分析技术为商家提供精准营销服务,本文研究了两个竞争商家通过同一个数据平台进行精准营销时,平台收费模式(费率佣金与按销量收费)对商家竞争以及平台与商家利润的影响。研究发现:1)费率佣金模式的绩效依赖于费率参数,在精准度高的情况下,它不能最大化平台与商家的利润。2)与费率佣金相比,按销量收费模式显著提高了商家的利润,并且平台与商家的利润都随费用参数的增加而增加。3)从收费模式选择的角度,精准度越高,按销量收费模式的优势越明显;费率佣金模式适用于垄断情况,而按销量收费模式更适用于竞争情况。4)费率佣金与按销量收费的结合可以实现平台与商家的共赢。研究结论为大数据驱动下的精准营销收费模式选择,以及“大数据平台”的盈利模式创新提供了理论参考。

关键词: 数据平台, 精准营销, 大数据驱动, CPS

Abstract: Through big data analysis technology , the third-party data platform provides firms with precision marketing service. This paper studies the effects of the platform’s revenue model (the commission model and charging according to the sale volume model) on firms’ competition, platform’s profit and firms’ profits. The findings are as follows. First, the performance of the commission model depends on the commission rate; when the targeting precision is high, the commission model cannot maximize the profits of platform and firms. Second, compared to the commission model, charging according to the sale volume model enhances firms’ profits; and both platform’s and firms’ profits increase with fee parameter. Third, from the charging model selection perspective, the higher the targeting precision is, the more advantage of charging the sale volume model has; the commission model is suitable for monopoly situation while charging according to which the sale volume model works well in competing situation. Fourth, combining the commission model, charging according to the sale volume model can realize the win-win situation for both platform and firms. All these findings provide theoretic references not only for charging model selection of precision marketing driven by big data, but also for the revenue model innovation of “big data platform”.

Key words: data platform, precision marketing, big data-driven, CPS

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