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題名 人工智慧應用於行銷科技之個案分析— 以iKala 為例
A Case Study on the Applications of AI in MarTech作者 林司晴
Lin, Sz-Ching貢獻者 邱奕嘉
Chiu, Yi-Chia
林司晴
Lin, Sz-Ching關鍵詞 行銷科技
人工智慧
商業模式
產品市場適配理論
進入市場理論
MarTech
artificial intelligence
business model
PMF
GTMF日期 2020 上傳時間 2-Mar-2021 14:58:54 (UTC+8) 摘要 行銷科技的落地與應用，只是近10年的新興議題，但這10年間的產品及服務卻有高達5,233%的成長率，總產值甚至突破1210億美元。而從相關文獻和實務場域可發現，導入人工智慧（AI）的行銷活動，其成效相對於其他行銷科技的發展更顯著且被更廣泛的應用。由於行銷科技領域的發展仍屬新穎，故本研究嘗試以商業模式、產品市場適配理論PMF和進入市場理論GTMF作為研究理論，並選擇當今台灣企業中，以AI為核心發展行銷事業的佼佼者iKala做分析，透過訪談創辦人獲得第一手資料以及搜集次級資料，整理並探究兩大問題：（一）以個案公司為例，探討如何以AI建構其行銷科技發展模式？（二）以個案公司為例，分析AI作為行銷科技所帶來的成效與影響為何？但因為iKala為新創公司，在搜集文獻以及訪談過程中，關於AI應用於內部營運的外部資料較少，公司也不便透露，故本文的研究主要聚焦在iKala提供的AI產品分析以及其商業模式的轉變，最終提出6項研究發現並精煉出2大命題：（一）以AI作為行銷科技來優化行銷成效的市場大且機會多，但是企業若要脫穎而出，選對市場和靈活的調整商業模式設計才是致勝關鍵。（二）在劇變的世代中，應當站在巨人的肩膀上，以數據為基礎發展平台事業和創造綜效，同時秉持著以人為本及高層次的價值主張設計商業模式。
The application of marketing technology has become an emerging topic in the past 10 years. The growth rate of MarTech products and services has reached 5,233% and the total output value has exceeded US$121 billion. Based on the relevant literature and practical experience, we can find that utilizing artificial intelligence (AI) is one of the most widely used marketing technologies to improve the effectiveness of marketing activities.In order to further understand the successful factors, I use “Business Model Theory”, “Product Market Fit, and “Go to Market Fit” as the research theory. iKala, a Taiwanese leading company that applies AI to develop marketing business, is chosen as a main company to be studied. Many information has been collected by in-depth interview with iKala co-founder and reading relevant articles. There are two major issues discussed in this thesis:(1) Take the case company as an example and investigate how the company introduces AI into its marketing technology.(2) Take the case company as an example and analyze the effectiveness and impact of AI as a marketing technology.In this study, the information collecting process is challenging. The external information of AI applications in iKala is limited because it is just a start-up company. The internal operations of iKala is also not easily accessible due to the protection of business confidentiality. Therefore, this research focuses on the AI product analysis provided by iKala and the transition of its business model. In the end, six research findings are proposed and two major propositions are refined:(1) Utilizing AI as a marketing technology to optimize the marketing effectiveness is attractive and opens up boundless prospects and opportunities. However, if a company wants to stand out, choosing the right market and adjusting the business model are the key success factors.(2) In the era of drastic change, companies must stand on the shoulders of giants, develop platform businesses and create synergies based on data. In the meanwhile, the company should adhere to people-oriented and high-level value proposition to design business models for improving marketing effectiveness.參考文獻 一、中文文獻1. 阿杰・艾格拉瓦、約書亞‧格恩斯、阿維・高德法布（2018）。AI經濟的策略思維：善用人工智慧的預測威力，做出最佳商業決策（林奕伶譯）。台北市：天下雜誌股份有限公司。（原著出版年：2018年）2. 馬克‧傑佛瑞（2018）。量化行銷時代：貝佐斯與亞馬遜經營團隊都在做，15個關鍵行銷計量指標（高英哲譯）。新北市。大牌出版。（原著出版年：2010年）3. 亞歷山大．奧斯瓦爾德...等人（2012）。獲利世代：自己動手，畫出你的商業模式。台灣：早安財經。（原著出版年：2010年）4. 曾允盈（2019）。找到電商神隊友。看雜誌，第207期，p.32-39。5. 張道宜（2019）。Cheers雜誌，小新創如何打贏「國際賽」？。第221期，p.90-956. 鍾嘉玲（2019）。台灣市場網紅媒合智能推薦平台差異化策略之研究。國立政治大學經營管理碩士學程（EMBA）。7. 行政院（2019）。台灣AI行動計畫—掌握契機，全面啟動產業AI化。檢自https://www.ey.gov.tw/Page/5A8A0CB5B41DA11E/a8ec407c-6154-4c14-8f1e-d494ec2dbf23（May 29, 2020）8. Doris Lin（2018）。人工智慧時代，你可以善用的AI行銷工具。檢自https://transbiz.com.tw/ai-人工智慧行銷工具-marketing-tools/（May 24, 2020）9. 高雅欣（2020）。最火熱的AI應用：NLP在含金量最高的2個產業率先發光。檢自https://fc.bnext.com.tw/ai-nlp-contract/（May 24, 2020）10. iKala官方網站，公司簡介。檢自https://ikala.tv/zh-tw/ （May 25, 2020）11. 張道宜（2019）。iKala執行長程世嘉：真正的新創，是先看準弱點，再將優勢化為武器。檢自https://www.cheers.com.tw/article/article.action?id=5095430（May 25, 2020）12. 彭子豪（2020）。疫情延燒 愛卡拉iKala數位行銷火熱。檢自https://money.udn.com/money/story/5640/4404623（May 25, 2020）13. 陳湘庭（2012）。【Meet創業之星】多螢一雲跨裝置K歌平台－iKala。數位時代。檢自https://www.bnext.com.tw/article/23547/BN-ARTICLE-23547（May 27, 2020）14. BBC News（2019），人工智能70年：科幻和現實的交融。檢自https://www.bbc.com/zhongwen/trad/science-48380424。（May 29, 2020）15. 李力昌. (2009). 一篇良好的「文獻回顧」的寫法 (一). https://blog.xuite.net/lichanglee/kuastm/21690495-%E4%B8%80%E7%AF%87%E8%89%AF%E5%A5%BD%E7%9A%84%E3%80%8C%E6%96%87%E7%8D%BB%E5%9B%9E%E9%A1%A7%E3%80%8D%E7%9A%84%E5%AF%AB%E6%B3%95+%28%E4%B8%80%2916. 智策慧編輯小組. (2020). 行銷與行銷科技趨勢與演變 | SWEM｜智策慧｜智創品牌. http://www.swem.com.tw/news/行銷與行銷科技趨勢與演變下/http://www.swem.com.tw/news/%E8%A1%8C%E9%8A%B7%E8%88%87%E8%A1%8C%E9%8A%B7%E7%A7%91%E6%8A%80%E8%B6%A8%E5%8B%A2%E8%88%87%E6%BC%94%E8%AE%8A%E4%B8%8B/17. iKala. (2018). iKala「GCP專門家」獲 Google Cloud Data Analytics 專業認證 ｜ MeetHub. https://meethub.bnext.com.tw/ikala%E3%80%8Cgcp%E5%B0%88%E9%96%80%E5%AE%B6%E3%80%8D%E7%8D%B2-google-cloud-data-analytics-%E5%B0%88%E6%A5%AD%E8%AA%8D%E8%AD%89/18. iKala. (2020). iKala - 以人為本的 AI 科技公司. iKala. https://ikala.tv/zh-tw/19. Jeffery, M. (2018). 量化行銷時代: 貝佐斯與亞馬遜經營團隊都在做,15個關鍵行銷計量指標 = Data-driven marketing: the 15 metrics everyone in marketing should know (初版 ed.). 大牌出版 : 遠足文化事業股份有限公司發行.二、英文文獻1. Marco Iansiti & Karim R. Lakhani (2020). Competing in the Age of AI. Harvard Business Review, Jan/Feb2020, Vol. 98 Issue 1, p60-67.2. Śledzik, Karol. (2013). Schumpeter’s View on Innovation and Entrepreneurship. SSRN Electronic Journal. 10.2139/ssrn.2257783.3. 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Qualitative Research Journal, 9(2), 27-40. https://doi.org/10.3316/QRJ090202712. Scott Brinker (2017). The Grand View of Martech: A Martech Manifesto. Chief Marketing Technologist. https://chiefmartec.com/2017/08/martech-manifesto-grand-view/13. Scott Brinker (2019). 3 trends driving the Second Golden Age of Martech: ecosystems, experts, and (citizen) engineers. Chief Marketing Technologist. https://chiefmartec.com/2019/01/3-trends-next-age-martech-ecosystems-experts-engineers/14. Cannella, J. (2018). Artificial Intelligence In Marketing Honors Thesis. Arizona State University].15. Carolanne, M. (2018). Is Marketing ready for VR / AR in 2018? Smart Insights. https://www.smartinsights.com/digital-marketing-platforms/video-marketing/is-marketing-ready-for-vr-ar-in-2018/16. Conick, H. (2017). What marketers need to know about blockchain. Marketing News, 51(10), 12-14.17. Eisenhardt, K. M. (1989). Building theories from case study research. Academy of management review, 14(4), 532-550.18. Grewal, D., Motyka, S., & Levy, M. (2018). The evolution and future of retailing and retailing education. Journal of Marketing Education, 40(1), 85-93.19. Institute, C. D. T. (2018). Turning AI into concrete value: the successful implementers’ toolkit. Capgemini Worldwide. https://www.capgemini.com/resources/turning-ai-into-concrete-value/20. Marc Andreesen. (2007). EE204 Business Management for Engineers and Computer Scientists. Stanford University. https://web.stanford.edu/class/ee204/ProductMarketFit.html#c121. Mark Leslie, M. H. (2017). Leslie’s Compass: A Framework For Go-To-Market Strategy.https://firstround.com/review/leslies-compass-a-framework-for-go-to-market-strategy/22. Scholz, J., & Duffy, K. (2018). We ARe at home: How augmented reality reshapes mobile marketing and consumer-brand relationships. Journal of Retailing and Consumer Services, 44, 11-23.23. Shah, D., & Shay, E. (2018). How and Why Artificial Intelligence, Mixed Reality and Blockchain Technologies Will Change Marketing We Know Today. Handbook of Advances in Marketing in an Era of Disruptions: Essays in Honour of Jagdish N. Sheth, 377.24. Yin, R. K. (2018). Case study research and applications: design and methods (Sixth edition ed.). SAGE.25. Everett, Cath. (2018). ‘Using Artificial Intelligence to Add Insight for Clever Customer26. Service: Developers Are Adding Layers of Intelligence to Customer Analytics Applications to Improve Sellers’ Interactions with Buyers’. Computer Weekly, March, 17–21.27. Kuester, S., Konya-Baumbach, E., & Schuhmacher, M. C. (2018). Get the show on the road: Go-to-market strategies for e-innovations of start-ups. Journal of Business Research, 83, 65-81. https://doi.org/10.1016/j.jbusres.2017.09.03728. McNeill, R. (2005). Go-to-Market Frontier: Global Account Management (GAM). Journal of Global Business and Technology, 1(1), 12-31.29. Schuhmacher, M. C., Kuester, S., & Hultink, E. J. (2018). Appetizer or Main Course: Early Market vs. Majority Market Go-to-Market Strategies for Radical Innovations. Journal of Product Innovation Management, 35(1), 106-124. https://doi.org/10.1111/jpim.1237930. Zott, C., & Amit, R. (2008). The fit between product market strategy and business model: implications for firm performance. Strategic Management Journal, 29(1), 1-26. https://doi.org/10.1002/smj.642 描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
107363071資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107363071 資料類型 thesis dc.contributor.advisor 邱奕嘉 zh_TW dc.contributor.advisor Chiu, Yi-Chia en_US dc.contributor.author (Authors) 林司晴 zh_TW dc.contributor.author (Authors) Lin, Sz-Ching en_US dc.creator (作者) 林司晴 zh_TW dc.creator (作者) Lin, Sz-Ching en_US dc.date (日期) 2020 en_US dc.date.accessioned 2-Mar-2021 14:58:54 (UTC+8) - dc.date.available 2-Mar-2021 14:58:54 (UTC+8) - dc.date.issued (上傳時間) 2-Mar-2021 14:58:54 (UTC+8) - dc.identifier (Other Identifiers) G0107363071 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/134211 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 企業管理研究所(MBA學位學程) zh_TW dc.description (描述) 107363071 zh_TW dc.description.abstract (摘要) 行銷科技的落地與應用，只是近10年的新興議題，但這10年間的產品及服務卻有高達5,233%的成長率，總產值甚至突破1210億美元。而從相關文獻和實務場域可發現，導入人工智慧（AI）的行銷活動，其成效相對於其他行銷科技的發展更顯著且被更廣泛的應用。由於行銷科技領域的發展仍屬新穎，故本研究嘗試以商業模式、產品市場適配理論PMF和進入市場理論GTMF作為研究理論，並選擇當今台灣企業中，以AI為核心發展行銷事業的佼佼者iKala做分析，透過訪談創辦人獲得第一手資料以及搜集次級資料，整理並探究兩大問題：（一）以個案公司為例，探討如何以AI建構其行銷科技發展模式？（二）以個案公司為例，分析AI作為行銷科技所帶來的成效與影響為何？但因為iKala為新創公司，在搜集文獻以及訪談過程中，關於AI應用於內部營運的外部資料較少，公司也不便透露，故本文的研究主要聚焦在iKala提供的AI產品分析以及其商業模式的轉變，最終提出6項研究發現並精煉出2大命題：（一）以AI作為行銷科技來優化行銷成效的市場大且機會多，但是企業若要脫穎而出，選對市場和靈活的調整商業模式設計才是致勝關鍵。（二）在劇變的世代中，應當站在巨人的肩膀上，以數據為基礎發展平台事業和創造綜效，同時秉持著以人為本及高層次的價值主張設計商業模式。 zh_TW dc.description.abstract (摘要) The application of marketing technology has become an emerging topic in the past 10 years. The growth rate of MarTech products and services has reached 5,233% and the total output value has exceeded US$121 billion. Based on the relevant literature and practical experience, we can find that utilizing artificial intelligence (AI) is one of the most widely used marketing technologies to improve the effectiveness of marketing activities.In order to further understand the successful factors, I use “Business Model Theory”, “Product Market Fit, and “Go to Market Fit” as the research theory. iKala, a Taiwanese leading company that applies AI to develop marketing business, is chosen as a main company to be studied. Many information has been collected by in-depth interview with iKala co-founder and reading relevant articles. There are two major issues discussed in this thesis:(1) Take the case company as an example and investigate how the company introduces AI into its marketing technology.(2) Take the case company as an example and analyze the effectiveness and impact of AI as a marketing technology.In this study, the information collecting process is challenging. The external information of AI applications in iKala is limited because it is just a start-up company. The internal operations of iKala is also not easily accessible due to the protection of business confidentiality. Therefore, this research focuses on the AI product analysis provided by iKala and the transition of its business model. In the end, six research findings are proposed and two major propositions are refined:(1) Utilizing AI as a marketing technology to optimize the marketing effectiveness is attractive and opens up boundless prospects and opportunities. However, if a company wants to stand out, choosing the right market and adjusting the business model are the key success factors.(2) In the era of drastic change, companies must stand on the shoulders of giants, develop platform businesses and create synergies based on data. In the meanwhile, the company should adhere to people-oriented and high-level value proposition to design business models for improving marketing effectiveness. en_US dc.description.tableofcontents 目次摘要 I目次 IV圖次 VI表次 VIII第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的與問題 7第二章 文獻探討 8第一節 行銷科技 8一、行銷科技定義 8二、行銷科技的演變 10第二節 產品市場適配理論（Product Market Fit） 17第三節 進入市場適配理論（Go-to-Market Fit） 20第四節 商業模式 32第三章 研究方法 37第一節 研究方法 37第二節 研究架構與流程 39第四章 個案公司介紹—愛卡拉互動媒體股份有限公司（iKala） 41第一節 公司使命與願景 41第二節 公司發展階段 41第三節 主要服務 51第五章 個案分析與討論 57第一節 第一階段iKala的商業模式分析 57第二節 第二階段iKala的PMF模型分析 61第三節 第三階段iKala的GTMF模型分析 66第六章 結論與建議 72第一節 研究發現與命題 72第二節 研究結論 75第三節 研究限制 77第四節 研究建議 77附錄 78參考文獻 80 zh_TW dc.format.extent 6928391 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107363071 en_US dc.subject (關鍵詞) 行銷科技 zh_TW dc.subject (關鍵詞) 人工智慧 zh_TW dc.subject (關鍵詞) 商業模式 zh_TW dc.subject (關鍵詞) 產品市場適配理論 zh_TW dc.subject (關鍵詞) 進入市場理論 zh_TW dc.subject (關鍵詞) MarTech en_US dc.subject (關鍵詞) artificial intelligence en_US dc.subject (關鍵詞) business model en_US dc.subject (關鍵詞) PMF en_US dc.subject (關鍵詞) GTMF en_US dc.title (題名) 人工智慧應用於行銷科技之個案分析— 以iKala 為例 zh_TW dc.title (題名) A Case Study on the Applications of AI in MarTech en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文文獻1. 阿杰・艾格拉瓦、約書亞‧格恩斯、阿維・高德法布（2018）。AI經濟的策略思維：善用人工智慧的預測威力，做出最佳商業決策（林奕伶譯）。台北市：天下雜誌股份有限公司。（原著出版年：2018年）2. 馬克‧傑佛瑞（2018）。量化行銷時代：貝佐斯與亞馬遜經營團隊都在做，15個關鍵行銷計量指標（高英哲譯）。新北市。大牌出版。（原著出版年：2010年）3. 亞歷山大．奧斯瓦爾德...等人（2012）。獲利世代：自己動手，畫出你的商業模式。台灣：早安財經。（原著出版年：2010年）4. 曾允盈（2019）。找到電商神隊友。看雜誌，第207期，p.32-39。5. 張道宜（2019）。Cheers雜誌，小新創如何打贏「國際賽」？。第221期，p.90-956. 鍾嘉玲（2019）。台灣市場網紅媒合智能推薦平台差異化策略之研究。國立政治大學經營管理碩士學程（EMBA）。7. 行政院（2019）。台灣AI行動計畫—掌握契機，全面啟動產業AI化。檢自https://www.ey.gov.tw/Page/5A8A0CB5B41DA11E/a8ec407c-6154-4c14-8f1e-d494ec2dbf23（May 29, 2020）8. 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