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    題名: 影響App使用者從免費到付費的關鍵因素探討: 以財經App為例
    What Drives App Users from Freemium to Premium: A Case of Financial Service App
    作者: 李玟霖
    Lee, Wen-Lin
    貢獻者: 何乾瑋
    Ho, Chien-Wei
    李玟霖
    Lee, Wen-Lin
    關鍵詞: 免費增值模式
    財經 App
    顧客感知價值
    付費使用者的轉化率
    Freemium model
    financial App
    customer perceived value
    conversion rate of paying users
    日期: 2024
    上傳時間: 2024-07-01 12:43:58 (UTC+8)
    摘要: 隨著數位轉型的快速發展，免費增值模式在各個領域廣泛應用。這種模式吸引了大量使用者，並引導其成為付費會員，進而實現盈利。因此，如何增加使用者的黏著度，進而提升付費會員轉換率，成為免費增值營運模式的關鍵問題。
    本研究以個案公司之財經App為研究對象，有別於以往常用的問卷調查或網路資料搜集方法，利用個案資料庫中的實際使用者行為數據資料，深入探討影響使用者從免費使用者轉變為付費會員的關鍵功能，從而提供精準且具參考價值的分析結果。
    透過機器學習梯度提升決策樹及存活分析，本研究發現「普遍性」、「新內容發現」以及「價格價值」等功能對提升使用者付費轉換率有正向影響。因此，個案公司可以持續優化現有功能，或者規劃相關行銷活動，針對免費會員推廣相關功能，以提高使用率，進而提升付費會員轉換率。相對地，「社會連結」及「個人化功能」則無顯著的正向影響，個案公司可以思考是否優化相關功能，或創造更符合使用者需求的功能，從而提升使用體驗。最後，未來公司可根據分析結果預測有較高機率轉化為付費會員的免費使用者，進行精準行銷的活動規劃。
    With digital transformation advancing rapidly, the freemium model has been widely applied across various industries. This model attracts a large user base, guiding them towards premium subscriptions that lead to profitability. Therefore, increasing user engagement and enhancing the conversion rate to paid membership become a critical issue under the freemium business model.
    This research explores the key features that influence the transition from freemium to premium by studying a case of financial App, which is developed by a leading financial technology company in Taiwan. Different from traditional data collection methods, such as survey research or web data collection, this research extracted real user behavior data from the database in the case company to provide precise and valuable analytical results.
    Using XGBoost techniques in machine learning and survival analysis, this research found that "ubiquity," "the discovery of new content," and "price value" have significant impacts on increasing users’ conversion from freemium to premium. Consequently, the case company can continue optimizing existing features or introduce additional functionalities to enhance the product's value proposition for paid subscriptions. Conversely, "social connectivity" and "personalization features" show no significant impact, indicating a potential reevaluation of these features or the development of new ones that better meet user needs. Finally, the company can use these insights to predict which free users are likely to convert and tailor their marketing strategies accordingly.
    參考文獻: 中文部分
    參考文獻
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    英文部分
    一、 網路和書籍
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    IFPI. (2012). Digital Music Report 2012. International Federation of the Phonographic Industry.
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    Mobile apps in Taiwan - statistics & facts. Statista. (2023). Retrieved from https://www.statista.com/study/164083/mobile-apps-in-taiwan/
    MARIE BEEREN. (2022). Best Mobile Trading Platforms In IBD Best Online Brokers Survey. Retrieved from https://www.investors.com/news/best-mobile- trading-platforms-in-ibd-best-online-brokers-survey/
    OpenView Advisors LLC. (2023). 2023 Product Benchmarks Report. Spotify. (2023). Spotify Reports Third Quarter 2023 Earnings.
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    Vrountas, T. (n.d.). 68 personalization statistics every digital advertiser must keep in mind. Retrieved from https://instapage.com/blog/personalization-statistics/
    二、 文獻參考
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    描述: 碩士
    國立政治大學
    國際經營與貿易學系
    111351038
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0111351038
    資料類型: thesis
    顯示於類別:[國際經營與貿易學系 ] 學位論文

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