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| 研究生： |
陳佩蓉 Chen, Pei-Rong |
|---|---|
| 論文名稱： |
數據分析如何實現精準行銷? -以T公司為例 How Does Data-Driven Analysis Achieve Precision Marketing? - A Case Study of T Company |
| 指導教授： |
張元杰
Chang, Yuan-Chieh |
| 口試委員: |
謝英哲
Hsieh, Ying-Che 張公一 Zhang, Gong-Yi 黃瓊誼 Hwang, Chiung-Yi |
| 學位類別： |
碩士 Master |
| 系所名稱： |
科技管理學院 - 科技管理研究所 Institute of Technology Management |
| 論文出版年： | 2019 |
| 畢業學年度： | 107 |
| 語文別： | 英文 |
| 論文頁數： | 47 |
| 中文關鍵詞： | 精準行銷 、RFM模型 、集群分析 、資料探勘 |
| 外文關鍵詞： | precision marketing, RFM model, cluster analysis, data mining |
| 相關次數： | 點閱：1 下載：0 |
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本研究旨在探討數據分析如何實現精準行銷，對企業而言，蒐集客戶數據的能力已不再是問題，然而，大多數企業仍無法善用這些累積的數據，進而挖掘顧客的需求。過去研究已經證實，透過數據分析，能夠從消費者的購買行為獲取顧客偏好，使行銷更有效率，並提升企業的表現。本研究採用RFM(近度，頻率，消費金額)模型作為顧客價值分析方法，蒐集T公司在2018年間的顧客消費紀錄，共有8090筆交易資料與4192會員。研究結果顯示，RFM模型能有效將會員依據其消費特徵，聚集成五個不同的集群，進一步的訪談結果也得出消費者的真正需求。本研究的結論是，RFM模型能對顧客進行詳細分類，進一步的訪談結果能了解消費者在特徵表現上的差異，有助於精準行銷的實現。
This study aims to investigate that how data-driven analysis achieves precision marketing. The capability of collecting customer data is no longer a problem to firms, however, most of firms are not able to make the best of the accumulated data to dig out customers’ needs. Previous studies have proven that data-driven marketing is an efficient way to capture the customers’ preferences from purchasing behaviors, resulting in increasing firms’ performances. By adopting RFM (recency, frequency, monetary) model as an effective means of customer value analysis, this study collects 8,090 transaction data and 4,192 members of T Company in 2018. The results show that the RFM model clusters members into five various clusters with specific characteristics of customers’ needs which aligned with the results of interviews. This study concludes that RFM model is useful to classify customers in detail and further interviews are helpful to achieve precision marketing. The managerial implications for achieving precision marketing are suggested.
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