網際網路與通信科技蓬勃興起，2015年全球上網人口32億約佔全球人口將近半數，研究指出資料量的產生每兩年增加一倍，其中非結構化（Unstructured）資料更佔了百分之九十。因此，如何透過資料採礦（Data Mining）發掘潛在有用的商情資訊，支援企業的行銷決策，增加企業的競爭優勢，已是現代企業所面臨網路行銷的迫切課題。
本研究試圖從外部多平台的網際網路資料庫角度，探討應用資料採礦於網路行銷之可行性。採用實證探究的方式，運用API（Application Programming Interface）從網際網路多樣性資料庫中自動擷取資料，建立資料倉儲，透過資料採礦技術關聯法則分析挖掘潛在有價值的商情資訊，並結合雲端運算（Cloud Computing）推出跨平台產品服務「雲端廣告（Cloud Business Outlet, CBO）」，發展出一套創新的網路行銷模式，以提供企業於網路行銷之參考使用。
根據本研究結果，以實際企業使用雲端廣告產品之深度訪談結果歸納與分析。說明應用資料採礦於網路行銷模式，可協助企業從網際網路多樣性的海量資料中自動網羅、篩選、發掘潛在客戶，提取商情資訊，買賣雙方得以即時互動。透過雲端運算平台大量、快速、自動撥發有主題性的視覺設計廣告，可增加曝光企業的品牌知名度，亦可經由自然過濾吸引真正有興趣的買家造訪網站，增加新客戶及詢問度來自不同國家（例如：俄國、韓國、印度、美國、加拿大等）；也說明應用資料採礦於網路行銷是一個自動、即時的業務開發過程，可縮短企業尋找客戶的時間，減少人力成本，對於企業的網路行銷有一定程度的助益。

The Internet and communication technology have undergone substantial development. In 2015, the world's online population reached 3.2 billion, representing approximately half of the total global population. Research has indicated that the volume of data produced is doubling every 2 years. Unstructured data alone makes up 90% of online data. Therefore, applying data mining to obtain useful information, support marketing decisions, and increase competitive advantage is crucial for businesses engaging in Internet marketing.
This study investigated the feasibility of applying data mining to Internet marketing from the perspective of external multiplatform databases. The study adopted an empirical exploration approach that entailed employing an application programming interface (API) to automatically collect data from diversified databases to build a data warehouse. Next, data mining technology was applied through association rules to extract valuable data, applying cloud computing to produce a cross-platform product called a “cloud business outlet” (CBO). Through the CBO, an innovative Internet marketing model was devised, serving as a reference for businesses in marketing.
This study conducted in-depth interviews with businesses that used CBO products. The results indicated that the application of data mining on Internet marketing facilitated businesses in automatic filtering, discovering potential customers from big data, extracting useful information, and facilitating timely buyer–seller interactions. By sending thematic advertisements in large volumes rapidly and automatically, businesses achieved increased brand awareness, new customers, and inquiries; this represents an automatic, real-time business development process that reduces time and costs, creating benefits for businesses.

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