2019 智慧企業資訊應用發展國際研討會 台灣，2019/06/29(六) 作者：黃瓊玉
英文姓名：Chiung-Yu Huang 服務單位：黎明技術學院 中文職稱：資訊管理系主任
英文職稱：Chairman of Dept. of Information Management 連絡方式：hcyjoan@gmail.com 0935-874978
2019 智慧企業資訊應用發展國際研討會 台灣，2019/06/29(六) 智慧企業網路行銷技術應用策略之研究-以某公司為例 黃瓊玉 黎明技術學院資訊管理系 hcyjoan@gmail.com 林醫旬 政治大學 EMBA hcyjoan@gmail.com 陳林宏 黎明技術學院機械工程系 hcyjoan@gmail.com 摘要 智慧化時代下，智慧企業的行銷技術亦與傳統不同。智慧企業的行銷技術，著重 網路行銷技術，先找尋消費與其需求所在，藉內容閱讀與瀏覽行為來理解消費者與其需 求後，適時提供所需要的商品服務，以達成銷售目的。因此，首先本研究針對智慧企業 分析，期從掌握智慧企業的特性與概況。其次，對智慧企業網路行銷技術文獻探討， 奠立研究架構與基礎。再者，採個案研究，並進行高階主管深訪與次級資料分析。最 後，提出本研究結論:對智慧企業而言，未來網路行銷技術應用策略是如何進行更有效 的交換-消費者期待完善的整體性套餐，而非單項經個別比較的組合。品牌也將與技術 開發與應用有重要的關聯性。本研究建議：對消費者來說，接收無用訊息也是當網路 垃圾處理；文案企劃與用戶介面應將消費者觀感納入考慮，並對行為紀錄分析。 關鍵詞：智慧企業、網路行銷、技術應用策略 Abstract
With the advent of the era of wisdom, the marketing technology of smart companies is also different from traditional marketing techniques. The marketing technology of smart business focuses on online marketing technology. It first looks for consumption, and where it is needed. After understanding the consumer and its needs through content reading and browsing behavior, it provides the goods/services needed to achieve sales in a timely manner.
First, this study analyzed the smart business to understand characteristics of smart business. Secondly, it conducted literature review on smart business network marketing technology, and lays the foundation for research structure and
implementation steps. Furthermore, case studies were conducted and it was conducted through in-depth interviews with senior executives and secondary data analysis.
2019 智慧企業資訊應用發展國際研討會 台灣，2019/06/29(六) Finally, the conclusion of this study: For smart business, how the future application
strategy of online marketing technology is more effective exchange - consumers expect a complete holistic package instead of a single comparison. The brand will also have an important correlation with technology development and application. The suggestion of this study: For consumers, receiving unwanted messages is also treated as a network waste; while the plan and user interface recommendations take into account the consumer perception and analyze all of their behavior records.
