大數據應用對於顧客管理與銷售績效影響之研究 —以個案公司為例

Abstract

近年來隨著社群媒體的普及，大數據思維可以運用在大量的歷史資料下，預測出未來潛在的商業機會與價值。因此，本論文以大數據應用於顧客管理對於銷售績效之影響為題，探討企業如何活用大數據分析與模組，建構符合企業本身的商業情境下，擁有最具競爭力的顧客管理策略，以達到創造良好之營收績效為目的。 本研究先確立以「大數據」為主題，並聚焦於「顧客管理與銷售績效分析」的領域擬定研究目的，從蒐集個案公司的背景資料、顧客管理方式與營運模式等，藉由回顧管理學上與顧客管理及大數據分析和應用等相關之文獻理論為參考。個案研究中探討透過導入不同大數據分析模組之應用，包含有傳統的RFM (近期 Recency、頻率Frequency、金額 Monetary) 模組和NPT (下一次購買時機Next Purchase Time)模組，以了解顧客管理方式之不同對於顧客回購率之變化，以做為個案公司或相關產業未來以大數據應用於顧客管理上，對於銷售績效之影響的參考依據。

With the popularity of social media in recent years, the big data cogitation can be used to predict potential business opportunities and value in the future through the application of a large amount of historical data. Therefore, based on the impact on sales performance through the application of big data to customer management, this paper aimed to explore how enterprises use big data analysis and modules to build the best customer management under its own business context in order to create a great performance. This study first established the theme of 'big data' and focused on the areas of 'customer management and sales performance analysis', in which the processes included the collection of case company background information, customer management methods, business and operation models as well as the management literature related to customer relationship management, big data analysis and application literature theory. The case study of this research explored the application of different big data analytic modules by incorporating traditional RFM (Recency, Frequency and Monetary) modules and NPT (Next Purchase Time) modules in order to understand the variation of repeat purchase rate responding to different customer management, which will be able to serve as a reference to case company or related industry in the future for the impact on sales performance through the application of big data on customer management