Generative AI for Customer Experience: From Basics to Advanced Applications
暫譯: 生成式人工智慧在客戶體驗中的應用:從基礎到進階應用
Vemula, Anand
- 出版商: Independently Published
- 出版日期: 2024-07-23
- 售價: $680
- 貴賓價: 9.5 折 $646
- 語言: 英文
- 頁數: 38
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798333906380
- ISBN-13: 9798333906380
-
相關分類:
人工智慧
海外代購書籍(需單獨結帳)
商品描述
"Generative AI for Customer Experience: From Basics to Advanced Applications" delves into the transformative potential of Generative AI in enhancing customer interactions and satisfaction. The book begins with a comprehensive introduction to Generative AI, explaining its fundamentals, key technologies, and algorithms. It highlights how technologies like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models such as GPT-3 and GPT-4 have revolutionized content creation, offering new avenues for personalized customer engagement.
The evolution of customer experience is traced from traditional methods, emphasizing face-to-face interactions and manual feedback collection, to the digital transformation era, where data analytics and automation tools began to play a crucial role. The book illustrates how AI has further advanced customer experience by enabling unprecedented levels of personalization and efficiency. It showcases how AI-powered chatbots, virtual assistants, and machine learning algorithms analyze vast amounts of data to predict customer needs and preferences, making interactions more seamless and engaging.
Key use cases of Generative AI in customer experience are explored in detail, including personalized recommendations, chatbots and virtual assistants, customer sentiment analysis, and predictive customer insights. Real-world case studies from various industries, such as retail, finance, healthcare, and hospitality, demonstrate the practical applications and benefits of Generative AI.
The book provides a step-by-step guide to implementing Generative AI in customer experience, covering the identification of customer pain points, data collection and management, selecting the right AI models, and integrating them with existing systems. It also addresses ethical considerations and challenges, such as data privacy, bias, fairness, transparency, and trust.
Measuring the impact of Generative AI on customer experience is another critical aspect covered, with discussions on key performance indicators (KPIs), customer satisfaction metrics, and return on investment (ROI) analysis. The book concludes with insights into future trends and innovations, offering predictions for the next decade and highlighting emerging technologies that will shape the future of customer experience.
商品描述(中文翻譯)
《生成式人工智慧在客戶體驗中的應用:從基礎到進階應用》深入探討了生成式人工智慧在提升客戶互動和滿意度方面的變革潛力。本書首先提供了生成式人工智慧的全面介紹,解釋其基本概念、關鍵技術和演算法。它強調了生成對抗網路(Generative Adversarial Networks, GANs)、變分自編碼器(Variational Autoencoders, VAEs)以及基於變壓器的模型如 GPT-3 和 GPT-4 如何徹底改變內容創作,為個性化客戶互動提供了新的途徑。
客戶體驗的演變從傳統方法追溯,強調面對面互動和手動反饋收集,轉向數位轉型時代,數據分析和自動化工具開始發揮關鍵作用。本書說明了人工智慧如何進一步提升客戶體驗,使個性化和效率達到前所未有的水平。它展示了人工智慧驅動的聊天機器人、虛擬助手和機器學習演算法如何分析大量數據,以預測客戶需求和偏好,使互動變得更加流暢和引人入勝。
本書詳細探討了生成式人工智慧在客戶體驗中的關鍵應用案例,包括個性化推薦、聊天機器人和虛擬助手、客戶情感分析以及預測性客戶洞察。來自零售、金融、醫療保健和酒店等各行各業的實際案例研究展示了生成式人工智慧的實際應用和好處。
本書提供了實施生成式人工智慧於客戶體驗的逐步指南,涵蓋了識別客戶痛點、數據收集和管理、選擇合適的人工智慧模型以及與現有系統的整合。它還討論了倫理考量和挑戰,如數據隱私、偏見、公平性、透明度和信任。
衡量生成式人工智慧對客戶體驗影響的另一個關鍵方面是關鍵績效指標(KPIs)、客戶滿意度指標和投資回報率(ROI)分析的討論。本書最後提供了對未來趨勢和創新的見解,預測未來十年的發展,並強調將塑造客戶體驗未來的新興技術。