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市場調查報告書

企業虛擬數位助手 (VDA) :人工智能 (AI) 、自然語言處理 (NLP) 、互動式用戶界面 (UI)的有效利用

Virtual Digital Assistants for Enterprise Applications: Virtual Agents, Chatbots and Virtual Assistants for Enterprise Markets Utilizing Artificial Intelligence, Natural Language Processing and Conversational User Interfaces

出版商 Tractica 商品編碼 335100
出版日期 內容資訊 英文 95 Pages; 77 Tables, Charts & Figures
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企業虛擬數位助手 (VDA) :人工智能 (AI) 、自然語言處理 (NLP) 、互動式用戶界面 (UI)的有效利用 Virtual Digital Assistants for Enterprise Applications: Virtual Agents, Chatbots and Virtual Assistants for Enterprise Markets Utilizing Artificial Intelligence, Natural Language Processing and Conversational User Interfaces
出版日期: 2017年12月28日 內容資訊: 英文 95 Pages; 77 Tables, Charts & Figures
簡介

本報告提供企業虛擬數位助手 (VDA) 市場相關調查分析,市場問題點及技術的問題點為焦點,使用案例,主要企業簡介等系統性資訊。

第1章 摘要整理

第2章 市場問題點

  • 範圍和定義
  • 市場概要
  • 推動市場要素
  • 市場障礙
  • 競爭情形
  • 市場趨勢

第3章 使用案例

  • 簡介
  • 客戶服務與行銷
  • 電子商務與銷售
  • 商業應用
  • 自動招聘
  • 醫療
  • 納稅申報和外語教育

第4章 技術的問題點

  • 基礎技術
  • 自然語言處理 (NLP)

第5章 主要企業

  • 簡介
  • Abe AI
  • Alterra.ai
  • Artificial Solutions
  • Babylon Health
  • ChatGrid
  • Clustaar
  • Conversable
  • Converse.AI
  • Creative Virtual
  • CX Company
  • Facebook
  • Flamingo
  • HealthJoy
  • iDAvatars
  • Inbenta Technologies
  • Interactions
  • IPsoft
  • Jacada
  • Julie Desk
  • Kore.ai
  • Klevu
  • LINE
  • LogMeIn
  • Microsoft
  • Mya Systems
  • Next IT
  • Nuance
  • PullString
  • SmartAction
  • Snaps
  • Synthetix
  • Tia
  • Talla
  • Woebot

第6章 市場預測

  • 預測手法
  • 企業VDA軟體的收益
  • 企業VDA用戶的預測
  • 企業VDA軟體的收益:各產業
  • 企業VDA支援服務的收益
  • 企業VDA支援硬體設備的收益
  • 企業VDA有效用戶:各地區、使用案例
  • 建議

第7章 企業名錄

第8章 縮寫、簡稱清單

第9章 目錄

第10章 圖表

第11章 調查範圍,資訊來源,調查手法,註解

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目錄
Product Code: VDA-17

Virtual digital assistants (VDAs) are automated software applications or platforms that assist humans through understanding natural language in written or spoken form, and leverage some form of artificial intelligence (AI) in doing so. Enterprise VDAs are controlled by an enterprise and deployed for interaction with a specific set of systems, using channels the organization typically controls, such as phone/interactive voice response (IVR), website, mobile applications, or kiosks; and channels they do not control, such as messaging applications like Facebook Messenger, LINE, or Telegram, or smart assistants like Amazon's Alexa.

Companies seeking efficiencies and automation for customer support and customer service began experimenting more than 10 years ago with automated applications that leveraged natural language processing (NLP). Most of these applications lived within an enterprise website, delivering smart search for frequently asked questions (FAQs), and then later as pop-up VDAs and avatars with more advanced capabilities. In the last 3 years, significant advances in combining NLP with other forms of AI, primarily machine learning and deep learning, have made enterprise VDAs more intelligent and more useful. This advancement and other market factors have begun to expand the use cases for enterprise VDAs beyond customer service & marketing. Other notable use cases for enterprise VDAs include e-commerce and sales, business applications, healthcare, foreign language tutoring, and tax filing and processing.

This Tractica report examines the market and technology issues surrounding enterprise VDAs and then presents 9-year forecasts for VDAs used in these end markets. The report covers how enterprise VDAs will be used across multiple channels in six key use cases: customer service & marketing, e-commerce & sales, business application, healthcare, foreign language tutoring, and tax filing & processing. The study includes profiles for key industry players throughout the ecosystem. It also presents global market forecasts for enterprise VDAs, segmented by region, covering the period from 2016 through 2025.

Key Questions Addressed:

  • What is the current state of the enterprise virtual digital assistant market and how will it develop over the next decade?
  • What are the key use cases that will drive greater enterprise virtual digital assistant adoption?
  • What are the key drivers of market growth, and the key challenges faced by the industry, in each world region?
  • Who are the key players in the enterprise virtual digital assistant market, what is their competitive positioning, and which ones are poised for greatest success in the years ahead?
  • What is the size of the enterprise virtual digital assistant market opportunity?

Who Needs This Report?

  • Customer experience-focused enterprises
  • Customer experience solution providers
  • AI hardware and software providers
  • Application developers
  • Internet service providers
  • Brand marketers and advertisers
  • Investor community

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Overview
  • 1.3. Market Trends
  • 1.4. Market Drivers and Barriers
  • 1.5. Competitive Landscape and Key Industry Players
  • 1.6. Market Forecasts
    • 1.6.1. Enterprise VDA Software Revenue by Use Case
    • 1.6.2. Enterprise VDA Software Revenue by Region
    • 1.6.3. Enterprise VDA Total Revenue by Segment

2. Market Issues

  • 2.1. Scope and Definitions
  • 2.2. Market Overview
  • 2.3. Market Drivers
    • 2.3.1. Consumer Demand for Self Service
    • 2.3.2. Consumer Expectations for Control, Speedy Resolution, and Personal Context
    • 2.3.3. Increased Customer Satisfaction
    • 2.3.4. Shifting App Use/Fatigue
    • 2.3.5. Emergence of One-to-One Marketing
    • 2.3.6. Cost Savings
    • 2.3.7. Better Data Analysis = Better Decision Making
    • 2.3.8. Improved Employee Satisfaction
  • 2.4. Market Barriers
    • 2.4.1. Effectiveness
      • 2.4.1.1. Speech Recognition
      • 2.4.1.2. Understanding Language Context
      • 2.4.1.3. User Context
    • 2.4.2. Automated or Live Agent?
    • 2.4.3. Discoverability-Consumer Awareness
    • 2.4.4. Internal Agreement and Integration
    • 2.4.5. Fear of Failure
  • 2.5. Competitive Landscape
  • 2.6. Market Trends
    • 2.6.1. Facebook's Impact

3. Use Cases

  • 3.1. Introduction
  • 3.2. Customer Service & Marketing
    • 3.2.1. Narrower, Practical Sub-Use Cases
    • 3.2.2. Vertical Market Momentum for Financial Services
      • 3.2.2.1. HDFC Bank
    • 3.2.3. Down-Market Momentum
      • 3.2.3.1. ChatGrid
      • 3.2.3.2. LogMeIn
    • 3.2.4. Hybrid-Live Solutions
      • 3.2.4.1. Creative Virtual
    • 3.2.5. VDAs Using Rules-Based and Machine Learning
      • 3.2.5.1. Inbenta Technologies
    • 3.2.6. Introduction of Deep Learning to Enterprise Virtual Digital Assistants
      • 3.2.6.1. Alterra.ai
    • 3.2.7. Momentum for Messenger Platforms as a Channel, Experimentation with Voice Assistants as a Channel
      • 3.2.7.1. Snaps
  • 3.3. E-Commerce & Sales
    • 3.3.1. Banking and Financial Services
      • 3.3.1.1. Tata Capital
      • 3.3.1.2. Flamingo
    • 3.3.2. LINE
      • 3.3.2.1. Loyalty Programs
      • 3.3.2.2. Selling Financial Services
    • 3.3.3. Retail Sales
      • 3.3.3.1. Conversable
      • 3.3.3.2. Klevu
  • 3.4. Business Applications
    • 3.4.1. Productivity and Collaboration
      • 3.4.1.1. Julie Desk
      • 3.4.1.2. Talla
      • 3.4.1.3. Microsoft
    • 3.4.2. Workflow and Project Management
      • 3.4.2.1. Converse.AI
  • 3.5. Automated Job Recruiting
    • 3.5.1. Mya Systems
  • 3.6. Healthcare
    • 3.6.1. Zocdoc
    • 3.6.2. Babylon Health
    • 3.6.3. HealthJoy
    • 3.6.4. Woebot
    • 3.6.5. Tia
  • 3.7. Tax Filing and Processing Foreign Language Tutoring

4. Technology Issues

  • 4.1. Underlying Technologies
  • 4.2. Natural Language Processing
    • 4.2.1. Legacy Natural Language Processing Gives Way to Hybrid Natural Language Processing
    • 4.2.2. Natural Language Processing Market Drivers
      • 4.2.2.1. User Interface Technology for New Computing Platforms
      • 4.2.2.2. The Failure of Big Data
    • 4.2.3. Natural Language Processing Market Barriers
      • 4.2.3.1. Understanding Context
      • 4.2.3.2. Need for Accurate Data
    • 4.2.4. The Importance of Machine and Deep Learning to Natural Language Processing
    • 4.2.5. Understanding Natural Language: Word Maps and Language Models
    • 4.2.6. Natural Language Generation
    • 4.2.7. Legacy Approaches to Natural Language Processing
      • 4.2.7.1. Rules-Based
      • 4.2.7.2. Statistical Models
    • 4.2.8. Deep Learning
      • 4.2.8.1. Deep Learning in Context
      • 4.2.8.2. What Is Deep Learning?

5. Key Industry Players

  • 5.1. Introduction
  • 5.2. Abe AI
  • 5.3. Alterra.ai
  • 5.4. Artificial Solutions
  • 5.5. Babylon Health
  • 5.6. ChatGrid
  • 5.7. Clustaar
  • 5.8. Conversable
  • 5.9. Converse.AI
  • 5.10. Creative Virtual
  • 5.11. CX Company
  • 5.12. Facebook
  • 5.13. Flamingo
  • 5.14. HealthJoy
  • 5.15. iDAvatars
  • 5.16. Inbenta Technologies
  • 5.17. Interactions
  • 5.18. IPsoft
  • 5.19. Jacada
  • 5.20. Julie Desk
  • 5.21. Kore.ai
  • 5.22. Klevu
  • 5.23. LINE
  • 5.24. LogMeIn
  • 5.25. Microsoft
  • 5.26. Mya Systems
  • 5.27. Next IT
  • 5.28. Nuance
  • 5.29. PullString
  • 5.30. SmartAction
  • 5.31. Snaps
  • 5.32. Synthetix
  • 5.33. Tia
  • 5.34. Talla
  • 5.35. Woebot

6. Market Forecasts

  • 6.1. Forecast Methodology
  • 6.2. Enterprise VDA Software Revenue
    • 6.2.1. Enterprise VDA Software Revenue by Use Case
    • 6.2.2. Enterprise VDA Software Revenue by Region
    • 6.2.3. Enterprise VDA Total Revenue by Segment
  • 6.3. Enterprise VDA User Forecasts
    • 6.3.1. Unique Active Enterprise VDA Users by Region
    • 6.3.2. Enterprise VDA Users by Use Case
  • 6.4. Enterprise VDA Software Revenue by Industry
    • 6.4.1. Enterprise VDA Software Revenue, Business Services Industry
    • 6.4.2. Enterprise VDA Software Revenue, Education Industry
    • 6.4.3. Enterprise VDA Software Revenue, Finance Industry
    • 6.4.4. Enterprise VDA Software Revenue, Healthcare Industry
  • 6.5. Enterprise VDA-Driven Services Revenue
    • 6.5.1. Enterprise VDA-Driven Installation Services
    • 6.5.2. Enterprise VDA-Driven Training Services
    • 6.5.3. Enterprise VDA-Driven Customization Services
    • 6.5.4. Enterprise VDA-Driven Application Integration Services
    • 6.5.5. Enterprise VDA-Driven Support and Maintenance Services
    • 6.5.6. Enterprise VDA-Driven Cloud Services Revenue
  • 6.6. Enterprise VDA-Driven Hardware Revenue
    • 6.6.1. Enterprise VDA-Driven GPU Chip Revenue
    • 6.6.2. Enterprise VDA-Driven CPU, ASIC, FPGA Revenue
    • 6.6.3. Enterprise VDA-Driven Network Products Revenue
    • 6.6.4. Enterprise VDA-Driven Storage Device Revenue
  • 6.7. Active Enterprise VDA Users by Region and Use Case
    • 6.7.1. Active Enterprise VDA Users by Use Case, North America
    • 6.7.2. Active Enterprise VDA Users by Use Case, Europe
    • 6.7.3. Active Enterprise VDA Users by Use Case, Asia Pacific
    • 6.7.4. Active Enterprise VDA Users by Use Case, Latin America
    • 6.7.5. Active Enterprise VDA Users by Use Case, Middle East & Africa
  • 6.8. Recommendations

7. Company Directory

8. Acronym and Abbreviation List

9. Table of Contents

10. Table of Charts and Figures

11. Scope of Study, Sources and Methodology, Notes

Tables

  • Enterprise VDA Software Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Total Revenue by Segment, World Markets: 2016-2025
  • Enterprise VDA Hardware Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Total Software, Service, and Hardware Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue by Industry, World Markets: 2016-2025
  • Enterprise VDA Software Revenue by Use Case, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Business Services Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Education Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Finance Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Healthcare Industry by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Hardware Revenue by Product Category, World Markets: 2016-2025
  • Enterprise VDA-Driven Cloud Services Revenue, World Markets: 2016-2025
  • Enterprise VDA Cloud Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven CPU, ASIC, FPGA Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven GPU Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Network Products Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Storage Devices Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Services Revenue by Service Category: 2016-2025
  • Enterprise VDA-Driven Installation Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Training Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Customization Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Application Integration Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Support and Maintenance Services Revenue by Region, World Markets: 2016-2025
  • Unique Active Enterprise VDA Users by Region, World Markets: 2017-2025
  • Active Enterprise VDA Users by Use Case, World Markets: 2017-2025
  • Active Enterprise VDA Users by Use Case, North America: 2017-2025
  • Active Enterprise VDA Users by Use Case, Europe: 2017-2025
  • Active Enterprise VDA Users by Use Case, Asia Pacific: 2017-2025
  • Active Enterprise VDA Users by Use Case, Latin America: 2017-2025
  • Active Enterprise VDA Users by Use Case, Middle East & Africa: 2017-2025 Charts
  • Enterprise VDA Software Revenue by Use Case, World Markets: 2016-2025
  • Enterprise VDA Software Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Total Revenue by Segment, World Markets: 2016-2025
  • Enterprise VDA Software Revenue by Use Case, World Markets: 2016-2025
  • Enterprise VDA Software Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA Total Revenue by Segment, World Markets: 2016-2025
  • Unique Active Enterprise VDA Users by Region, World Markets: 2017-2025
  • Active Enterprise VDA Users by Use Case, World Markets: 2017-2025
  • Enterprise VDA Software Revenue by Industry, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Business Services Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Education Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Finance Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Software Revenue in the Healthcare Industry by Region, World Markets: 2016-2025
  • Enterprise VDA Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Installation Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Training Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Customization Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Application Integration Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Support and Maintenance Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Cloud Services Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Hardware Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Hardware Revenue by Product Category, World Markets: 2016-2025
  • Enterprise VDA-Driven GPU Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven CPU, ASIC, FPGA Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Network Products Revenue by Region, World Markets: 2016-2025
  • Enterprise VDA-Driven Storage Device Revenue by Region, World Markets: 2016-2025
  • Active Enterprise VDA Users by Use Case, North America: 2017-2025
  • Active Enterprise VDA Users by Use Case, Europe: 2017-2025
  • Active Enterprise VDA Users by Use Case, Asia Pacific: 2017-2025
  • Active Enterprise VDA Users by Use Case, Latin America: 2017-2025
  • Active Enterprise VDA Users by Use Case, Middle East & Africa: 2017-2025 Figures
  • Attitudes toward and Experiences with IVR
  • Messaging versus Other Communication
  • McKinsey 2016 Survey of Customer Care Executives
  • Customer Service Channel Performance Survey
  • McKinsey Matrix for Automated and Live Customer Interaction Roles
  • Snaps' View of Potential Chatbot Platforms
  • Store Loyalty Card Chatbots on LINE
  • CTBC Bank Bot
  • Mya
  • Examples of Word Embeddings
  • Progression of Natural Language Generation
  • Artificial Intelligence Encompasses Numerous Technologies
  • Schematic Representation of a Deep Neural Network
  • iDAvatars Demo of a Virtual Digital Assistant for Patients
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