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챗봇 : 벤더의 기회와 시장 예측(2020-2024년)

Chatbots: Vendor Opportunities & Market Forecasts 2020-2024

리서치사 Juniper Research Ltd
발행일 2020년 03월 상품 코드 928092
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챗봇 : 벤더의 기회와 시장 예측(2020-2024년) Chatbots: Vendor Opportunities & Market Forecasts 2020-2024
발행일 : 2020년 03월 페이지 정보 : 영문

챗봇(Chatbots) 시장에 대해 종합적으로 조사했으며, 시장 현황 분석, 비용 절감 가능성, 서비스에 대한 소비자의 신뢰, 챗봇에 대한 지출 등 시장 심층 평가, Juniper Research Leaderboard를 이용한 벤더 분석 등의 정보를 제공합니다.

주요 조사 내용

  • 부문별 영향 분석 : 6개 주요 산업의 챗봇 도입 영향 분석
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    • 헬스케어
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    • 여행, 관광 및 접객
  • 산업 예측 벤치마크 : 웹 브라우저, 디스크리트 애플리케이션, 메시징 애플리케이션에 탑재된 챗봇, 아래 지표를 정량화
    • 챗봇 이용
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  • 챗봇 시장 역학 : 발전하는 챗봇 상황에 대한 상세 분석
    • 챗봇 에코시스템의 주요 발전
    • 챗봇의 발전과 활용의 원동력
    • 챗봇 시장의 현재/향후 과제
  • Juniper Research Leaderboard : 제품 개요, 향후 전략, 인공지능(AI) 기능이 있는 챗봇 개발을 촉진하는 챗봇 개발 툴 벤더 15개사에 대한 상세 분석
    • Botsify
    • Chatfuel
    • Conversable
    • FlowXO
    • Google Dialogflow
    • Gupshup
    • IBM Watson
    • Kasisto
    • ManyChat
    • Massively.ai
    • Microsoft
    • Octane AI
    • Pandorabots
    • Rasa
    • Reply.ai
LSH 20.03.19

Overview

Juniper Research's new ‘Chatbots ’ research investigates the current state of the market; providing a comprehensive examination of this sector. The research provides an in-depth assessment of the chatbot market; evaluating potential for cost savings, consumer trust in services, and spend on chatbots.

The study also contains insightful player analysis of leading Chatbot Development Tool vendors, alongside key expectations for stakeholders in the industry and Juniper Research's Vendor Leaderboard; focusing on AI criterion.

The research gives in-depth coverage of the following key markets:

  • Banking & Finance
  • eCommerce & Retail
  • Healthcare
  • Human Resources
  • Insurance
  • Travel, Tourism & Hospitality

The research includes:

  • Market Trends & Opportunities (PDF)
  • 5-Year Market Sizing & Forecast Spreadsheet (Excel)
  • 12 months' Access to harvest Online Data Platform

Key Features

  • Sector Impact Analysis: Considers the impact of chatbot implementation for 6 key industry verticals, including:
    • Banking & Finance
    • eCommerce & Retail
    • Healthcare
    • Human Resources
    • Insurance
    • Travel, Tourism & Hospitality
  • Benchmark Industry Forecasts: Provided by chatbots embedded in web browsers, discrete applications and messaging applications; quantifying the following indicators:
    • Chatbot Usage
    • In-app Purchases
    • Advertising Spend
    • Cost Savings for Businesses
    • End User Time Savings
  • Chatbot Market Dynamics: In-depth analysis of the evolving chatbot landscape, including:
    • Key developments in the chatbot ecosystem
    • Driving forces behind chatbot evolution and uptake
    • Present and future challenges to the chatbot market
  • Juniper Research Leaderboard: In-depth analysis of 15 Chatbot Development Tools vendors driving chatbot development, including product overviews, future strategies and AI capabilities:
    • Botsify
    • Chatfuel
    • Conversable
    • FlowXO
    • Google Dialogflow
    • Gupshup
    • IBM Watson
    • Kasisto
    • ManyChat
    • Massively.ai
    • Microsoft
    • Octane AI
    • Pandorabots
    • Rasa
    • Reply.ai

Key Questions

  • 1. Which chatbot developers are currently leading the market?
  • 2. Which technologies will be essential to maximise future success in the chatbot market?
  • 3. What is the potential for leveraging advertising on chatbots over the next 5 years?
  • 4. What are the key market forces impacting the chatbot market?
  • 5. What will the value of the chatbot industry be in 2024?

Data & Interactive Forecast

Juniper Research's ‘Chatbot’ forecast suite includes:

  • Data splits for 8 key global regions and 16 countries, including:
    • Brazil
    • Canada
    • China
    • Denmark
    • France
    • Germany
    • India
    • Japan
    • Norway
    • Portugal
    • Russia
    • Spain
    • South Korea
    • Sweden
    • UK
    • US
  • Total Value of the Chatbot Market, with technology splits including:
    • Discrete Application Chatbots
    • Messaging Application Chatbots
    • Web-browser Chatbots
  • For messaging application, discrete application and web-browser chatbots, the data is split by key industry verticals:
    • Banking
    • eCommerce
    • Healthcare
    • Retail
    • Social
  • Interactive Scenario Tool allowing users to manipulate Juniper Research's data for 10 different metrics.
  • Access to the full set of forecast data, containing 172 tables and over 30,500 datapoints.

Juniper Research's highly granular IFxls (Interactive Excels) enable clients to manipulate Juniper Research's forecast data and charts to test their own assumptions using the Interactive Scenario Tool; and compare select markets side by side in customised charts and tables. IFxls greatly increase clients' ability to both understand a particular market and to integrate their own views into the model.

Table of Contents

1. Market Status, Trends & Ecosystem

  • 1.1. Introduction
    • 1.2.1. Far East & China Dominates 2019
      • Figure 1.1: Global Chatbot Usage & Adoption Snapshot, 2019
    • 1.2.2. Cost Savings in 2019
    • 1.2.3. Segment Performance in 2019
  • 1.3. The Chatbot Ecosystem
    • 1.3.1. Natural Language Processing & Natural Language Understanding
    • 1.3.2. Conversational AI Maturity Levels: Scripted to Contextual
      • i. Scripted Chatbots
      • ii. NLP Chatbots
      • iii. Contextual Chatbots
    • 1.3.3. Chatbot Deployment Platforms & Chatbot Development Tools: An Overview
      • Figure 1.2: An Example of the Chatbot Ecosystem
    • 1.3.4. Key Drivers in the Chatbot Market
    • 1.3.5. Issues Facing the Chatbot Market
      • Figure 1.3: The Uncanny Valley
    • 1.3.6. The State of AI
      • Case Study: Google Duplex

2. Market Prospects: Chatbot Sector Analysis

  • 2.1. Chatbot Sector Analysis Summary
    • 2.1.1. Banking & Finance
      • Case Study: ila Bank
    • 2.1.2. eCommerce & Retail
    • 2.1.3. Healthcare
      • Case Study: Woebot
    • 2.1.4. Travel, Tourism & Hospitality
      • Case Study: Bebot
    • 2.1.5. Human Resources
    • 2.1.6. Insurance
  • 2.2. Criteria Analysis
    • 2.2.1. Banking & Finance
      • i. Monetisation Opportunities
      • ii. Potential User Base
        • Figure 2.1: Number of Active Online Banking Individuals (m), Split by 8 Key Regions 2019-2024
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations
    • 2.2.2. eCommerce & Retail
      • i. Monetisation Opportunities
      • ii. Potential User Base
        • Figure 2.2: Number of Adults Ages 15+ Who Access Commerce & Retail Websites (m). Split by 8 Key Regions 2019-2024
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations
    • 2.2.3. Healthcare
      • i. Monetisation Opportunities
      • ii. Potential User Base
        • Figure 2.3: Total Number of Visits to Online Healthcare Sites per Annum (m) Split by 8 Key Regions 2019-2024
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations
    • 2.2.4. Human Resources
      • i. Monetisation Opportunities
      • ii. Potential User Base
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations
        • Case Study: ‘Dottie' by Domino's
    • 2.2.5. Insurance
      • i. Monetisation Opportunities
      • ii. Potential User Base
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations
    • 2.2.6. Travel, Tourism & Hospitality
      • i. Monetisation Opportunities
      • ii. Potential User Base
      • iii. Consumer Trust
      • iv. Cost Savings Impact
      • v. Regulations

3. Competitive Landscape: Key Player Analysis & Positioning

  • 3.1. Vendor Analysis & Leaderboard Introduction
    • 3.1.1. Stakeholder Assessment Criteria
      • Table 3.1: Leaderboard Capability & Positioning Criteria for CDT Players
      • Figure 3.2: Juniper Research Leaderboard for CDT Vendors
      • Table 3.3: CDT Vendor Leaderboard Scoring Heatmap
    • 3.1.2. Chatbots: Vendor Groupings
      • i. Established Leaders
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
    • 3.1.3. Limitations & Interpretation
  • 3.2. Chatbots: Vendor Profiles
    • 3.2.1. Botsify
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.2. Chatfuel
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.3. Conversable
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.4. Flow XO
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.5. Google Dialogflow
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.6. Gupshup
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.7. IBM Watson
      • i. Corporate
        • Table 3.4: IBM Select Financial Information 2017-2019
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.8. Kasisto
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.9. ManyChat
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.10. Massively.ai
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.11. Microsoft
      • i. Corporate
        • Table 3.5: Microsoft Select Financial Information ($bn) 2018-2019
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.12. Octane AI
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.13. Pandorabots
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.14. Rasa
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 3.2.15. Reply.ai
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities

4. Chatbots: Market Sizing & Forecasts

  • 4.1 Chatbots Market Summary
    • Figure 4.1: Chatbots Forecast Split
    • 4.1.1. Total Number of Chatbots Accessed Per Annum
      • Figure & Table 4.2: Total Number of Chatbots & Chatbot Apps Accessed per annum (m), Split by 8 Key Regions 2019-2024
    • 4.1.2. Total Retail Spend on Chatbots & Chatbot Applications
      • Figure & Table 4.3: Total Retail Spend over Chatbots & Chatbot Applications ($m), Split by 8 Key Regions 2019-2024.
    • 4.1.3. Total Advertising Spend on Chatbots & Chatbot Applications
      • Figure & Table 4.4: Total Advertising Spend on Chatbots & Chatbot Applications ($m), Split by 8 Key Regions 2019-2024
    • 4.1.4. Cost Savings for Businesses
      • Figure & Table 4.5: Total Cost Savings for Businesses for Chatbots & Chatbot Applications ($m), Split by 8 Key Regions 2019-2024
  • 4.2. The Total Marketing for Messaging Application Chatbots
    • 4.2.1. Introduction
      • Figure 4.6: Methodology for Messaging Application Chatbots
    • 4.2.2. Total Number of Messaging App Chatbots Accessed Per Annum
      • Figure & Table 4.7: Total Number of Chatbots Accessed per annum (m) Split by Key Regions 2019-2024
    • 4.2.3. Total Number of Messaging App Chatbots that Generate Revenue
      • Figure & Table 4.8: Total Number of Messaging App Chatbots that Generate Revenue (m), Split by 8 Key Regions 2019-2024
    • 4.2.4. Total Spend from Messaging Application Chatbots
      • Figure & Table 4.9: Total Spend from Messaging Application Chatbots ($m), Split by 8 Key Regions 2019-2024
    • 4.2.5. Total Time Saved by Messaging Chatbots
      • Figure & Table 4.10: Total Time Saved by Messaging Application Chatbots (millions of hours), Split by 8 Key Regions 2019- 2024
  • 4.3. The Total Market for Discrete Application Chatbots
    • 4.3.1. Introduction
      • Figure 4.11: Methodology for Discrete Application Chatbots
    • 4.3.2. Total Number of Chatbot-enabled Applications Accessed Per Annum
      • Figure & Table 4.12: Total Chatbot-enabled Applications Accessed per annum (m), Split by 8 Key Regions 2019-2024
    • 4.3.3. Total Retail Spend from Chatbot-enabled Applications
      • Figure & Table 4.13: Total Retail Spend from Chatbot-enabled Applications ($m), Split by 8 Key Regions 2019-2024
    • 4.3.4. Total Advertising Spend on Chatbot-enabled Applications
      • Figure & Table 4.14: Total Advertising Spend on Chatbot-enabled Applications ($m), Split by 8 Key Regions 2019-2024
  • 4.4. The Total Market for Web-based Chatbots
    • Figure 4.15: Web-based Chatbots Forecast Methodology
    • 4.4.1. Total Number of Website Visits that are Chatbot-enabled
      • Figure & Table 4.16: Total Number of Chatbot Site Visits per annum (m), Split by 8 Key Regions 2019-2024
    • 4.4.2. Total Retail Spend from Web-based Chatbots
      • Figure & Table 4.17: Total Retail Spend from Web-based Chatbots ($m), Split by 8 Key Regions 2019-2024
    • 4.4.3. Total Advertising Spend on Web-based Chatbots
      • Figure & Table 4.18: Total Advertising Spend on Web-based Chatbots ($m), Split by 8 Key Regions 2019-2024
    • 4.4.4. Total Time Saved from Web-based Chatbots
      • Figure & Table 4.19: Total Time Saved from Web-based Chatbots in Hours (m), Split by 8 key Regions 2019-2024
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