| 摘要: | 隨著數位廣告與網站追蹤技術日益成熟，企業已廣泛應用Google Ads、Facebook Ads 與Google Analytics等數位工具。然而，多數企業在實務操作上仍缺乏完整的顧客歷程觀點與跨平台資料整合能力，難以有效量化廣告成效、網站行為指標與實際諮詢轉換行為之間的關聯性。且過去相關研究多聚焦於單一平台的數據分析，較難以呈現跨平台廣告效益。
本研究以AIDA模型為理論架構，將潛在客戶歷程劃分為「注意、興趣、慾望、行動」四個階段，分析S公司於2018至2023年間實際投放之多平台廣告與網站行為資料。在「注意 → 興趣」階段，Google Ads（整體與搜尋廣告）及Facebook廣告之廣告類型、曝光次數與曝光（頂端）百分比，皆對點擊與互動行為具顯著影響；於「興趣 → 行動」階段，點擊次數、點擊率與留言互動次數可以有效預測Landing Page諮詢行為；在「慾望 → 行動」階段，網頁瀏覽量、跳出率與單次工作階段頁數等網站行為指標，也與網站諮詢行為呈現顯著關聯，而且具轉換預測解釋力。
研究結果顯示AIDA模型可以應用於數位行銷歷程之實證分析，而且本研究成果也擴充AIDA模型在電子商務中，較少被應用於多平台廣告成效與網站行為整合分析的限制，並驗證其在B2B商業模式下的應用成效。本研究也提出S公司在廣告配置、Landing Page導流設計與社群互動優化上的實務建議，以及對媒體平台、廣告代理商與政府教育單位的建議，呼籲提出強化跨平台資料整合、提升數據應用能力與推動數位行銷教育與產學合作，以促進理論與實務之接軌。
;With the rapid advancement of digital advertising and website tracking technologies, companies have enthusiastically adopted digital tools such as Google Ads, Facebook Ads, and Google Analytics. However, even though the promotion effect of these tools has been studied before, they have never been analyzed with cross platform holistic views, which include advertising performance, website behavior indicators and inquiry conversions.
This study adopts the AIDA model as the theoretical framework, dividing customer journey into four stages, namely, Attention, Interest, Desire, and Action to analyze S Company’s advertising performance and website behavior data from 2018 to 2023. This research posited and confirmed that in the "Attention → Interest" stage, advertising type, number of impressions, and top impression rate from Google Ads (including search and display ads) and Facebook Ads significantly influenced click and interaction behaviors. In the "Interest → Action" stage, click numbers, click-through rates, and comment interactions were effective predictors of inquiry behaviors on the landing page. In the "Desire → Action" stage, website behavior indicators such as pageviews, bounce rate, and pages per session were significantly associated with inquiry behaviors.
The results show that the AIDA model can be adopted to study digital marketing processes that involving cross-platform advertising performance and website behavior integration analysis in the e-commerce context. In addition, this study verifies its applicability in B2B business models. With the hypotheses being supported in different AIDA stages, suggestions for S Company regarding advertising configuration, landing page traffic design, and social media interaction optimization were articulated. In addition, this study offers suggestions for media platforms, advertising agencies, and government education units to strengthen cross-platform data integration, enhance data application capabilities, and promote digital marketing education and industry-academia collaboration, thereby bridging the gap between theory and practice. |
