媒體大數據時代下數據融合對媒體代理商企劃人員的挑戰與因應策略

The challenge and strategies of data fusion in the big data era: The cases of media planners in media agency

陳順吉(Chen Shun-Chi)

指導教授 ： 陳百齡

國立政治大學/傳播學院/傳播學院碩士在職專班/碩士(2021年)

https://doi.org/10.6814/NCCU202101668

摘要

媒體執行往往是行銷策略的核心，費用占比高，被企業端高度重視。媒體代理商的媒體企劃人員，依賴數據進行分析、企劃與效益評估，以持續優化媒體投放效益，藉此與客戶溝通、並贏得信賴。大數據時代來臨，雖可得到更多數據，但媒體環境的改變與消費者媒體接觸模式的改變，導致對數據需求更多，數據不足的情況更明顯，也提高數據取得與整合的難度，讓媒體企劃面臨更大的挑戰。

本研究透過半結構性的質化訪談，與五位在知名媒體代理商企劃總監級以上的資深媒體企劃人員進行深度訪談，並以圖表動態互動的數據融合平台提供受訪者體驗，發現數據生態系、數據斷鏈、私域流量等因素讓媒體企劃人員在數據取得與數據整合都面臨挑戰。媒體代理商在因應方式上，除既有的調研資料庫外，加入網路社群資料庫也成趨勢，部分媒體代理商也提供「自動化報表」等方式以對應新時代下的媒體數據應用，提升與客戶溝通的效率，並自我期許能逐步轉型為客戶的行銷顧問，角色從「數據蒐集者」到「意義生成者」，讓數據發揮更大效益，提升知識價值，以持續深化媒體代理商對客戶的價值。

雖然數據融合模式是媒體企劃在數據應用的理想模式，但現實仍離目標很遠。本研究發現，除數據與技術的阻礙外，人的因素更是一大挑戰，這包含信賴議題，以及對數據融合是否有共同務實的認知。就實踐意涵上，媒體企劃數據融合是「ㄧ個不斷努力對應挑戰、以逐步優化客戶服務的可實踐的動態平衡過程」，並可望因應不同數據應用需求，有限度發展適合自己的媒體企劃數據融合平台。

在落實內容上，可發展結合抽樣數據與大數據的「三層次媒體企劃數據融合架構」，極大化以大數據為基礎、以抽樣調查數據補齊不足的數據來源策略，逐步建構由易到難、由局部到完整的數據融合模式。在此數據融合架構下，可依據使用者需求建構不同的分析模型，並可依據不同帳號設定不同的登入內容與權限，以提升數據分析應用的速度與品質，與強化資安以減少機敏數據外流，增加客戶願意參與的信賴感。值得注意的是，這種建構於數據融合平台的服務需求，可望成為新市場商業模式，背後代表的龐大商機，值得行銷研究領域的重要相關行為者努力。

關鍵字

媒體企劃 ； 媒體數據 ； 數據融合 ； 大數據 ； 抽樣數據 ； 資料庫 ； 媒體代理商 ； 數據斷鏈 ； 數據生態系 ； 私域流量

並列摘要

Media plan with huge budget is often the core of marketing execution and highly valued by the enterprise. Media planners of media agencies rely on data for analysis, planning, and effect evaluation to continuously optimize the effectiveness of media delivery, thereby gaining trust from clients. The era of big data is coming. Although more data can be obtained, changes in the media environment and consumer media contact patterns have led to more data needs and insufficient data, which has also increased the difficulty of data acquisition and integration. Media planners faces greater challenges.

Through semi-structured qualitative interviews, this paper conducted in-depth interviews with five senior media planners who was above the position of media planning director level of well-known media agencies, it also provided interviewees with a interactive data fusion platform of dynamic charts. The study discovers media planners now face challenges in data acquisition and data integration due to the factors such as data ecology, data disconnection, and private traffic. In terms of response the challenges, media agencies not only maintain the existing research databases but also buy social media databases. Some media agencies also provide services such as "automated chart report" to meet clients’ needs and gradually transform into a marketing consultant for clients. Media planners also play roles ranging from "data collector" to "meaning generator", and allowing data to be more effective, enhancing the value of knowledge from the data, and continuing to deepen media agency’s value to clients.

Although data fusion is an ideal model for data applications in media planning, the reality is still far from the goal. This study found that in addition to challenges of data acquisition and technology, the human factors are another major challenges, including the issues of trust and whether there is a common understanding of data fusion between media agencies and clients. In a positive sense, data fusion of media planning is "a practical dynamic balancing process that continuously strives to respond to challenges and gradually optimizes service for clients." It is also possible to develop the suitable data fusion platform for each agency to fit in with different data application needs.

In terms of practice, a "three-level media planning data fusion structure" that combines survey data and big data can be developed to maximize the data source possibility. And from easy to difficult, from partial to complete, it can gradually construct data fusion model. Under this data fusion structure, different analysis models can be constructed according to user needs; different login content and permissions can be set according to different accounts to improve the speed and quality of data analysis applications. From it, media agencies can strengthen information security to reduce the possibility of confidential data outflow. That can increase the trust and willing of clients to participate the data fusion mechanism. It is worth noting that this kind of service demand built on a data fusion platform is expected to become a new market business model, and the huge business opportunities represented behind it are worthy of the efforts of relevant stakeholders among marketing research field.

並列關鍵字

Media planning ； Media buying ； Media data ； Data Fusion ； Big data ； Sampled data ； Marketing database ； Media agency ； Data disconnection ； Data ecosystem ； Private traffic

參考文獻

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