中文摘要
本研究基於客戶關係管理進行相關的行銷推廣研究，並以美國數據庫行銷研究所亞瑟‧修斯（Arthur Hughes）指出客戶關係管理資料庫中的重要指標：RFM(Recency, Frequency, Monetary)之基礎，來建立個人壽險推廣模式，本論文旨在探討如何利用RFM(Recency, Frequency, Monetary)模型來提高個人壽險產品的銷售效率和客戶價值，RFM模型是一種客戶分析工具，通過對客戶的購買行為進行分析，並依其屬性將客戶分為不同組別，從而了解客戶的價值和行為。
本研究亦選取台灣最大之壽險金控公司來進行研究，並以其個人壽險產品作為研究對象，透過該公司以透過RFM的各項指標值得客戶名單，並依據其指標對客戶來進行分組和特徵深入分析，最終建立了基於RFM 模型的個人壽險推廣模式，提供相對應之解決方案，並有助於提升壽險業的營運績效與方針。
在實際操作方面，本研究提出了幾項關鍵性的結論，為了能提高個人壽險產品的銷售效率，壽險公司根據RFM模型進行客戶的資料分析，並提供客戶名單給予業務人員進行參考，但業務人員根據此名單仍無法迅速理解其應對應的銷售模式，因此本研究再將其名單再次導入本研究之研究模型，並提供更個性化的產品和服務，除了提供業務人員有參考和指導之依據，也提供壽險公司制定更有效的客戶推廣和管理策略，除此之外，可將本研究之研究模型套用至其它相關企業，已提供新的想法與可行與啟示，為其衍生出創新的銷售模式。
關鍵詞:RFM Model、個人壽險推廣、顧客關係管理、金融保險業、行銷推廣策略

Abstract
This study is based on customer relationship management to conduct relevant marketing promotion research. It uses the important indicators in the customer relationship management database pointed out by Arthur Hughes of the American Database Marketing Research Institute: RFM (Recency, Frequency, Monetary) as the foundation to establish a personal life insurance promotion model. The purpose of this thesis is to explore how to use the RFM (Recency, Frequency, Monetary) model to improve the sales efficiency and customer value of personal life insurance products. The RFM model is a customer analysis tool that analyzes the customer purchasing behavior and classifies customers into different groups based on their attributes, thereby understanding customer value and behavior.
This study selected Taiwan's largest life insurance financial holding company for research and used its personal life insurance products as the research object. Through the customer list of the company's RFM indicators, customers were grouped and characterized for in-depth analysis. Ultimately, a personal life insurance promotion model based on the RFM model was established, providing corresponding solutions and helping to improve the operational performance and direction of the life insurance industry.
In terms of practical operations, this study puts forward several key conclusions. To improve the sales efficiency of personal life insurance products, life insurance companies analyze customer data based on the RFM model and provide customer lists for sales staff to refer to. However, sales staff still cannot quickly understand the corresponding sales model based on this list. Therefore, this study re-imported the list into the research model of this study and provided more personalized products and services. In addition to providing a reference and guidance basis for sales staff, it also provides life insurance companies with more effective customer promotion and management strategies. In addition, the research model of this study can be applied to other related enterprises to provide new ideas and feasible inspirations, leading to the derivation of innovative sales models.
Keywords: RFM model, Personal life insurance promotion, CRM, Financial insurance industry, Promotional marketing strategy
 

中文摘要 I
ABSTRACT II
誌謝 IV
目錄 V
圖目錄 VI
第壹章 緒論 1
第一節 研究背景 1
第二節 研究動機及目的 1
第三節 研究論文架構及流程 5
第貮章 文獻探討 8
第一節：國內外壽險的現況 8
（一）國內文獻探討 8
（二）國外文獻探討 12
第二節：壽險的行銷模式 15
第三節：保險業運用RFM 17
第叁章 研究方法 19
第一節 個案資料收集與變數定義 20
第二節 研究架構 24
第肆章 資料分析與資料探討 26
第一節資料分析 27
第伍章 結論與建議 30
第一節 研究結論 30
第二節 研究建議 34
參考文獻 37
中文文獻 37
英文文獻 39

 
圖目錄
圖1本研究之研究論文架 7
圖2人口結構(資料來源國家發展委員會) 10
圖 3 傳統模式 銷售架構圖 19
圖4個案公司現行模式銷售架構圖 20
圖5個案公司數據分析八大面向 21
圖6 本研究之銷售架構圖 24
圖 7 本研究之RFM模型 24
圖 8 個案導入本研究RFM模型 26

參考文獻
中文文獻
(1)江宗翰. (2020). 我國網路保險行銷之研究.
(2)呂慧貞. (2019). 自費特殊醫療材料之台灣病患決策因素研究.
(3)宋畹玖. (2012). 台灣人口高齡化及少子化趨勢探討長期看護保險之發展. 嶺東通識教育研究學刊, 4(4), 51-62.
(4)林俊廷. (2019). 論我國問題保險業之退場處理機制.
(5)邱琮富. (2019). 負利率政策對日本保險業之影響.
(6)高子媛. (2020). 新冠肺炎下匯率與利率風險對於人壽保險安定基金風險保費之研究.
(7)梁景洋, & 韓幸紋. (2020). 從人口老化及薪資停滯角度探討全民健保財務及保費負擔世代分配問題. 臺灣經濟預測與政策, 51(1), 57-110.
(8)陳麗文. (2019). 產險公司在金控體系下共同行銷策略之探討.
(9)彭金隆, 魏筱昀, & 陳彥志. (2017). 壽險公司銀行保險通路策略會不會受到競爭者行為的影響: 動態競爭觀點之探討. 臺大管理論叢, 27(2S), 149-176.
(10)游雪紅. (2020). 台灣保險業產業趨勢與展望-改變才有新契機迎向保險新格局.
(11)黃正吉, & 吳天方. (2020). 探討台灣人口高齡化與健保支付的關聯性. 嶺東通識教育研究學刊, 8(3), 37-54.
(12)黃政雄. (2020). 保險經紀人公司全通路行銷策略之研究: National Taiwan Normal University (Taiwan).
(13)黃追. (2022). 以風險管理觀點看 [防疫保單之亂]. 會計研究月刊(440), 48-53.
(14)黃銘鴻. (2019). 人壽保險公司之財務槓桿與清償風險分析.
(15)趙尉妘. (2022). 醫療機構引入醫療器材經營策略之探討-以某醫學中心之調制中頻電刺激器應用於自費減重塑身為例.
(16)劉宜君, 陳敦源, 林昭吟, & 王光旭. (2020). 全民健保財務收支連動機制之研究: 問題建構途徑. 臺灣社會福利學刊, 16(1), 53-90.
(17)蕭惠斐. (2019). 保經代公司銷售壽險商品之研究.
(18)賴冠仲. (2017). 資本適足率與財務績效指標關聯性之探討-以台灣壽險業為例.
(19)簡鈺潔. (2022). IFRS 17 導入對台灣壽險公司的影響分析.
 
英文文獻
(1)Abdurazzokov, S. O., & Jabborov, O. N. (2022). ASSESSMENT OF FINANCIAL STABILITY OF INSURANCE COMPANIES. Paper presented at the INTERNATIONAL CONFERENCES.
(2)Agyei, J., Sun, S., Abrokwah, E., Penney, E. K., & Ofori-Boafo, R. (2020). Influence of trust on customer engagement: Empirical evidence from the insurance industry in Ghana. SAGE Open, 10(1), 2158244019899104.
(3)Al Omari, R., Alkhawaldeh, R. S., & Jaber, J. J. (2023). Artificial Neural Network for Classifying Financial Performance in Jordanian Insurance Sector. Economies, 11(4), 106.
(4)Angelevska-Najdeska244, K. (2018). IDENTIFICATION OF COMPETITIVE ADVANTAGES-CONDITION FOR A SUCCESSFUL APPEARANCE OF INSURANCE COMPANIES IN THE INSURANCE MARKET. Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture, 640.
(5)Badat, F., Ocampo, D. G., & Yong, J. (2021). Redefining insurance supervision for the new normal. International Association of Insurance Supervisors, Financial Stability Institute.
(6)Baecke, P., & Bocca, L. (2017). The value of vehicle telematics data in insurance risk selection processes. Decision Support Systems, 98, 69-79.
(7)Barua, S. (2020). Understanding Coronanomics: The economic implications of the coronavirus (COVID-19) pandemic. Available at SSRN 3566477.
(8)Binder, S., & Mußhoff, J. (2017). Global Insurance Industry Insights. An in-depth perspective McKinsey Global Insurance Pools—.
(9)Christy, A. J., Umamakeswari, A., Priyatharsini, L., & Neyaa, A. (2021). RFM ranking–An effective approach to customer segmentation. Journal of King Saud University-Computer and Information Sciences, 33(10), 1251-1257.
(10)Cruz, M. C. G. P. (2019). Evaluation of the technical provisions of insurance contracts under IFRS 17. Universidade de Lisboa (Portugal),
(11)Cvitanović, P. L. (2021). The analysis of digital marketing tactics of selected insurance companies in Croatia. EFZG working paper series, 2021(03), 1-21.
(12)Dhaene, J., Godecharle, E., Antonio, K., Denuit, M., & Hanbali, H. (2017). Lifelong health insurance covers with surrender values: updating mechanisms in the presence of medical inflation. ASTIN Bulletin: The Journal of The IAA, 47(3), 803-836.
(13)Ericson, R., & Doyle, A. (2004). Catastrophe risk, insurance and terrorism. Economy and society, 33(2), 135-173.
(14)Fachmi, M., Modding, B., Kamase, J., & Damis, H. (2020). The Mediating Role of Satisfaction: Life Insurance Customers’ Perspective (Service Quality, Trust and Image Toward Loyalty). International Journal of Multicultural and Multireligious Understanding, 7(6), 156-170.
(15)Foley-Fisher, N., Narajabad, B., & Verani, S. (2020). Self-fulfilling runs: Evidence from the us life insurance industry. Journal of Political Economy, 128(9), 3520-3569.
(16)Gachoki, J. M., Kinyua, J. M., & Kariuki, S. N. (2022). Diversification Strategies And Performance Of Insurance Companies In Kenya. Journal of Positive School Psychology, 6(11), 2667-2678.
(17)Gunawardhane, H., Wijesinghe, M., & Kavinda, D. (2022). The impact of Company-specific and Macro-economic factors on Company Performance: Evidence from Insurance Sector in Sri Lanka. Vidyodaya Journal of Management, 8(I).
(18)Kim, J.-M., Bae, J., Son, S., Son, K., & Yum, S.-G. (2021). Development of model to predict natural disaster-induced financial losses for construction projects using deep learning techniques. Sustainability, 13(9), 5304.
(19)Kumar, S. J., & Philip, A. O. (2022). Achieving Market Segmentation from B2B Insurance Client Data Using RFM & K-Means Algorithm. Paper presented at the 2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES).
(20)Kumar, V., Lahiri, A., & Dogan, O. B. (2018). A strategic framework for a profitable business model in the sharing economy. Industrial Marketing Management, 69, 147-160.
(21)Lanfranchi, D., & Grassi, L. (2021). Translating technological innovation into efficiency: the case of US public P&C insurance companies. Eurasian Business Review, 11(4), 565-585.
(22)Liu, Y., Peng, J., & Yu, Z. (2018). Big data platform architecture under the background of financial technology: In the insurance industry as an example. Paper presented at the Proceedings of the 2018 international conference on big data engineering and technology.
(23)Mall, S. (2017). Contribution of Insurance on economic growth in India: An Econometric approach.
(24)Müller, B., Johnson, L., & Kreuer, D. (2017). Maladaptive outcomes of climate insurance in agriculture. Global Environmental Change, 46, 23-33.
(25)Nguyen, H. T., Nguyen, H., Nguyen, N. D., & Phan, A. C. (2018). Determinants of customer satisfaction and loyalty in Vietnamese life-insurance setting. Sustainability, 10(4), 1151.
(26)Ostrowska, M. (2021). Transparency in Insurance Regulation and Supervisory Law of Poland. Transparency in Insurance Regulation and Supervisory Law: A Comparative Analysis, 213-230.
(27)Owolabi, A., Oloyede, F., Iriyemi, A., & Akinola, A. (2017). The impact of risk management on the profitability of insurance companies in Nigeria. International Journal of Marketing and Technology, 7(6), 1-26.
(28)Ozili, P. K., & Arun, T. (2023). Spillover of COVID-19: impact on the Global Economy. In Managing Inflation and Supply Chain Disruptions in the Global Economy (pp. 41-61): IGI Global.
(29)Ozyuksel, S., & Gezgin, M. (2020). Turkish Insurance Companies Risk Management Strategies and Structures: A Survey Study. International Journal of Economics and Finance, 12(8), 1-12.
(30)Peng, J.-L., Jeng, V., Wang, J. L., & Chen, Y.-C. (2017). The impact of bancassurance on efficiency and profitability of banks: Evidence from the banking industry in Taiwan. Journal of Banking & Finance, 80, 1-13.
(31)Preda, A., Popescu, M., & Drigă, I. (2021). The impact of covid-19 on global insurance market. Paper presented at the MATEC Web of Conferences.
(32)Revzon, O. A., Pochekutov, M. P., & Barabanov, A. E. (2021). Digital Insurance as an Industry in the Digital Economy. In Socio-economic Systems: Paradigms for the Future (pp. 757-765): Springer.
(33)Sheshasaayee, A., & Logeshwari, L. (2018). Implementation of clustering technique based RFM analysis for customer behaviour in online transactions. Paper presented at the 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI).
(34)Tahmoorespur, A., Behname, M., Hooshmand, M., & Tahsili, H. (2021). Investigation of the Relationship Between Life Insurance Growth and Economic Growth in Selected Countries of MENA Region. Journal Of Economics and Regional Development, 28(21), 239-268.
(35)Talesh, S. A. (2018). Data breach, privacy, and cyber insurance: How insurance companies act as “compliance managers” for businesses. Law & Social Inquiry, 43(2), 417-440.
(36)Turgaeva, A. A., Kashirskaya, L. V., Zurnadzhyants, Y. A., Latysheva, O. A., Pustokhina, I. V., & Sevbitov, A. V. (2020). Assessment of the financial security of insurance companies in the organization of internal control. Entrepreneurship and Sustainability Issues, 7(3), 2243.
(37)Ungur, C. (2017). Socio-economic valences of insurance. Revista Economia Contemporană, 2(2), 112-118.
(38)Wang, Q. (2021). The Impact of insurtech on Chinese insurance industry. Procedia Computer Science, 187, 30-35.
(39)Wang, Y., Zhang, D., Wang, X., & Fu, Q. (2020). How does COVID-19 affect China’s insurance market? Emerging Markets Finance and Trade, 56(10), 2350-2362.
(40)Wen, C., Gao, K., & Xiao, Y. (2021). Data-Driven Market Segmentation in Insurance Industry and Other Related Sectors. Journal of Finance and Accounting, 9(6), 268-272.
(41)Yuvaraj, M., & Rajendiran, G. (2020). A Relationship Between Service Quality and Customer Satisfaction in Life Insurance Sector. EasyChair Preprint.
(42)Zong, Y., & Xing, H. (2021). Customer stratification theory and value evaluation—analysis based on improved RFM model. Journal of Intelligent & Fuzzy Systems, 40(3), 4155-4167.