進入新網路時代，包括搜尋引擎、社群網站、線上購物等等都會遇到龐大數據資料的挑戰，在網路上購物不僅可以享受到實體書店所沒有的便利功能，且價格又比傳統實體商店還要更便宜。海量資料的重要性不在於資料大小或數量多寡，而是如何運用客戶的資料在軟硬體中找出線索、趨勢，經過演算法分析後提出預測，成為企業推展行銷活動的重要議題。 本研究以Amazon網路書店與博客來網路書店為個案研究，並以UCCT模式進行分析，並依結論提出四點建議：一、「整合數據」以解決大數據的問題；二、加強分享社群與網路書店對消費者的關聯性；三、建立資料庫行銷系統，開發推薦功能；四、因應新個資法，避免侵害隱私權。 In the new era of the Internet, including search engines, social networking sites, online shopping, and so will face a huge challenging data, and shopping on the Internet can not only enjoy the convenience features but the price also getting cheaper than the traditional physical store. Importance of the mass of information is not limited to the amount of data size or the numbers, but can also focus on how to use customer information to find clues, trends via hardware and software, to forecast after the analysis of algorithms, and to promot business marketing activities. In this study, by adopting Amazon online bookstore and Books online bookstore to a case study, and using UCCT model to analysis both bookstores, and puts forward four proposals in accordance with the conclusions: First, integrate big data to solve the problem of big data; Second, strengthen social sharing consumer groups and Internet bookstores relevance; Third, create a database marketing system and develop a recommendation mechanism; four, avoid infringement of privacy in response to the new Personal Information Protection Act.
