以RFM模型分析電商會員受網紅影響之再購意願

Abstract

電子商務市場自1995年Amazon開展，不僅僅使用者逐年發展，躍進成長曲線一直以陡幅上升，近年更受到新冠肺炎影響下，讓全球企業加速數位轉型，零售業也邁向電子商務高佔比推進，各家企業與品牌均致力於提升電子商務市場流量轉化之數位工具與技術，期望能精準掌握數位用戶動態與軌跡。當消費者動向引入電商平台後，即需要進行已消費會員維護，進而引導形成再次購買行為以降低廣告成本的逐步投入。會員維護除了包含售中與售後服務外，消費行為數據分析亦是重要環節之一，尤其是品牌業者要有效掌握與降低數位廣告花費轉以會員再購推廣為主之前提，即需要精準掌握已消費會員的購物行為與軌跡。 品牌與零售業者除了主動行銷之外，依靠網紅行銷對消費者具有一定影響力，本論文詳細回顧台灣數位用戶行為與數位行銷網紅的分類與發展，再以某美髮、美容零售產業品牌之電商消費會員軌跡為數據基礎，運用RFM模型為研究方法，不同於過往僅將RFM針對消費會員進行三維度分析下，本研究進一步將象限細化與軌跡來源歸屬進一步區分，分析會員受網紅自媒體行銷導引進入消費，與受品牌經營電商引入消費之差異，透過了解不同歸屬來源會員之RFM差異，亦利用趨勢圖解釋出各自屬性，且進一步以會員二次以上消費數據推導出電商消費會員對於網紅自媒體的依賴度以及行為預測。最後針對現今電子商務平台工具進行整理，進一步分析在留客機制上亦需要搭配適切之電商平台工具。

The development of the e-commerce market was started by Amazon in 1995. With a steep growth curve, the number of e-commerce users has soared over the years. Furthermore, COVID-19 has accelerated enterprise digital transformation and spurred retailers to increase their shares of e-commerce sales on a worldwide basis since 2020. Concurrently, for a better grasp of user activity and the path to purchase, algorithms are being gradually optimized for digital tools and technologies, thereby meeting the needs of converting traffic into sales for e-commerce businesses. After understanding consumer behavior trends and driving consumers to shop on e-commerce platforms, brands and retailers then have to retain their members with purchase history to encourage repeat purchases to reduce the gradually rising advertising costs. On top of services during and after sales, data analysis of shopping behavior is also pivotal to member retention. Having a solid grasp of consumer behavior and the path to purchase apparently has become one of the most critical issues faced by marketers. If brands would like to effectively control and cut the spending on digital advertising and rely mainly on repeat purchases and promotions made by existing members who have purchase history, a sound grasp of their shopping behavior and path to purchase is a prerequisite. Nevertheless, with the improvement of digital technologies, it is learned via third-party tracking tools that in the world of digital media, influencer marketing has a certain impact on consumers. In light of the foregoing, the present study first reviewed the categorization and development of influencers against the background of digital marketing and digital user behavior in Taiwan. Then based on the data of customers’ journey to purchase on online stores of certain hair and beauty retailers, the study used the recency, frequency, and monetary value (RFM) model of membership marketing as the research method and framework. Compared with previous studies in which marketers only used the three dimensions of RFM to analyze members with purchase history, this study further refined the quadrants for a more detailed data analysis and distinguished source attributions of the path to purchase. Certain members’ purchases are driven by influencer marketing and self-media, while some are attracted by brands’ e-commerce campaigns. Regarding the different driving forces, this study explored the RFM differences of members with different source attributions and used run charts to present each attribute. Moreover, from data analysis of the members’ online repeat purchases, the study deduced the members’ reliance on influencers and self-media and predicted the member’s behavior under the impact of influencers and self-media. This study also organized tools of existing e-commerce platforms and further analyzed the appropriate e-commerce platform tools needed for the customer retention mechanism.