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チャットボット 2018-2023年:小売業、eコマース、バンキング&医療

Chatbots

Retail, eCommerce, Banking & Healthcare 2018-2023

 

出版社 出版年月電子版価格 ページ数
Juniper Research
ジュニパーリサーチ社
2018年7月GBP2,990
企業ライセンス(PDF+Excel)
64

サマリー

このレポートは現在のチャットボット市場を調査し、5つの主要産業でのチャットボットの実装の影響、コスト削減、マネタイゼーションの可能性、規制背景などについて分析しています。

主な掲載内容  

調査対象セクタ

  • 銀行&金融
  • コマース&小売り
  • 医療
  • 旅行&ホスピタリティ
  • 保険

Overview

Juniper’s Chatbots research investigates the current state of the market; providing a comprehensive examination of this sector. The research looks at 5 major industries in depth; assessing the potential impact of chatbot implementation, based on factors such as monetisation potential, cost savings, reach and the regulatory landscape.
 
The study also contains insightful player analysis of leading Chatbot Development Tool vendors, alongside key expectations for stakeholders in the industry and Juniper’s Vendor Leaderboard; focusing on AI criterion.
 
The research gives in-depth coverage of the following key markets:
 

  • Banking & Finance
  • Commerce & Retail
  • Healthcare
  • Travel & Hospitality
  • Insurance

 
The research includes:

  • Market Trends & Opportunities (PDF)
  • 5 Year Market Sizing & Forecast Spreadsheet (PDF & Excel)

Key Features

  • Sector Impact Analysis: Investigates chatbot impact across 5 key industry verticals, with analysis of the following criteria:
    • Monetisation Opportunities
    • Potential User Base
    • Consumer Trust
    • Cost Saving Impact
    • Regulation
  • Sector Dynamics: In-depth analysis of the evolving chatbot landscape, including:
    • Key developments in the chatbot ecosystem
    • Market forces impacting chatbot evolution and take-up
    • Chatbot Threat Matrix in terms of present and future market challenges
  • Juniper Leaderboard: In-depth analysis of 15 Chatbot Development Tool vendors driving chatbot development, including their products, future strategies and AI capabilities.
  • Benchmark Industry Forecasts for Chatbots: Provided across SMS, web browser, discrete applications and messaging applications, quantifying the following indicators:
    • Total Chatbot Spend
    • Advertising Spend
    • Customer Service Provider Cost Savings
    • End User Time Savings

Key Questions

  1. What are the opportunities in terms of cost savings and monetisation from chatbot enablement?
  2. Which industries stand to benefit most from chatbot implementation?
  3. How is the chatbot ecosystem landscape developing?
  4. What are the key market forces impacting the chatbot market?
  5. Which key Chatbot Development Tool players are well positioned to influence the market over the next 5 years?

Companies Referenced

Allianz, Amazon, Asiana Airlines, Baidu, BotChain, Botkit, Botsify, Bottr, Chatfuel, Cleo, Conversable, EnCirca, Facebook, FSB (Financial Stability Board), GitHub, Google, Gupshup, HP, IBM, Ikea, Kik, KPMG, Lemonade, LINE, Macy’s, ManyChat, Massively AI, Mastercard, Microsoft, NHS, Octane AI, Pandorabots, Rasa, RBC, Slack, so-sure, Stack Overflow, Taco Bell, Telefonica, Telegram, Tencent, Twillio, Uber, UPS, WeChat, WhatsApp, Wit.ai, Yahoo.

Data & Interactive Forecast

Juniper’s Chatbot forecast suite includes:

  • Data splits for 8 key global regions in addition to country breakdowns for:
    • Brazil
    • Canada
    • China
    • Denmark
    • France
    • Germany
    • India
    • Japan
    • Norway
    • Portugal
    • Russia
    • Spain
    • South Korea
    • Sweden
    • UK
    • US
  • Total chatbots and chatbot apps accessed, advertising spend, time saved and total spend and savings, split by sector:
    • Banking
    • eCommerce & Retail
    • Healthcare
    • Social
  • Usage across SMS, web browser, discrete applications and messaging applications.
  • Interactive Scenario Tool allowing users to manipulate Juniper’s data for 7 different metrics.
  • Access to the full set of forecast data of 187 tables and over 33,660 datapoints.

Juniper Research’s highly granular IFxls (Interactive Excels) enable clients to manipulate Juniper’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.

Regions:
8 Key Regions - includes North America, Latin America, West Europe, Central & East Europe, Far East & China, Indian Subcontinent, Rest of Asia Pacific and Africa & Middle East
 
Countries:
Brazil, Canada, China, Denmark, France, Germany, India, Japan, South Korea, Norway, Portugal, Russian Federation, Spain, Sweden, UK, USA

 



目次

Table of Contents

1. Market Status, Trends & Ecosystem

1.1 Introduction . 5
1.2 Current Market Status . 5
1.2.1 Far East & China Dominates 2017 . 5
Figure 1.1: Chatbot Usage & Adoption Snapshot, 2017 . 5
1.2.2 Cost Savings in 2017 . 6
Figure 1.2: Total Cost Savings for Businesses for Chatbots & Chatbot
Applications (%), Split by Industry in 2017: $13.5 million . 6
1.2.3 Segment Performance in 2017. 6
Figure 1.3: Total Number of Chatbots Accessed (%), Split by Type in 2017 . 7
1.3 The Chatbot Ecosystem . 7
1.3.1 Chatbot Platforms & Chatbot Development Tools: An
Overview . 8
Figure 1.4: Chatbot Ecosystem . 8
1.3.2 Key Drivers in the Chatbot Market . 9
1.3.3 The State of AI . 9
Case Study: Google Duplex . 10
1.3.4 Issues Facing the Chatbot Market. 11
Figure 1.5: The Scale of the Challenge - Juniper Threat Matrix for Chatbots . 11

2. Market Prospects: Chatbots Sector Analysis

2.1 Introduction . 15
2.2 Chatbot Sector Analysis Summary . 15
Table 2.1: Sector Analysis Heatmap . 15
2.2.1 Banking & Finance . 15
2.2.2 Commerce & Retail . 15
2.2.3 Healthcare . 16
2.2.4 Travel & Hospitality . 16
2.2.5 Insurance . 16
2.3 Criteria Analysis . 16
2.3.1 Banking & Finance . 16
i. Monetisation Opportunities . 16
Case Study: Cleo . 17
ii. Potential User Base . 18
Figure 2.2: Number of Active Online Banking Individuals (m) Split by 8 Key
Regions 2018-2023 . 18
iii. Consumer Trust . 18
iv. Cost Savings Impact. 19
Figure 2.3: Banking & Finance - Chatbot Implementation vs Baseline: Annual
Cost ($000), Split by Scenario, Year 1-Year 5 . 19
v. Regulations . 20
2.3.2 Commerce & Retail . 20
i. Monetisation Opportunities . 20
Figure 2.4: Octane AI Abandoned Cart Messaging for Pure Cycle . 21
ii. Potential User Base . 21
Figure 2.5: Number of Adults, Ages 15+ Who Access Commerce & Retail
Websites (m) Split by 8 Key Regions 2018-2023 . 21
iii. Consumer Trust . 22
iv. Cost Saving Impact . 22
Figure 2.6: Commerce & Retail - Chatbot Implementation vs Baseline: Annual
Cost ($000), Split by Scenario, Year 1-Year 5 . 22
v. Regulations . 23
2.3.3 Healthcare. 23
i. Monetisation Opportunities . 23
ii. Potential User Base . 23
Figure 2.7: Total Number of Visits to Online Healthcare Sites per Annum (m) Split
by 8 Key Regions 2018-2023. 24
iii. Consumer Trust . 24
Figure 2.8: Your.MD . 24
iv. Cost Saving Impact . 25
Figure 2.9: Healthcare - Chatbot Implementation vs Baseline: Annual Cost ($000),
Split by Scenario, Year 1-Year 5 . 25
v. Regulations . 25
2.3.4 Travel & Hospitality . 26
i. Monetisation Opportunities . 26
ii. Potential User Base . 26
iii. Consumer Trust . 26
iv. Cost Saving Impact . 27
Figure 2.8: Travel & Hospitality - Chatbot Implementation vs Baseline: Annual
Cost ($000), Split by Scenario, Year 1-Year 5 . 27
v. Regulations . 27
2.3.5 Insurance . 27
i. Monetisation Opportunities . 27
ii. Potential User Base . 28
Figure 2.9: Total Insurance Premiums Generated via Digital Platforms ($m) Split
by 8 Key Regions 2017-2022. 28
iii. Consumer Trust . 28
iv. Cost Saving Impact . 28
Figure 2.10: Insurance - Chatbot Implementation vs Baseline: Annual Cost
($000), Split by Scenario, Year 1-Year 5 . 29
v. Regulations . 29

3. Competitive Landscape: Key Player Analysis & Positioning

3.1 Vendor Analysis & Leaderboard Introduction . 31
Table 3.2: CDT Vendor Leaderboard Scoring Heatmap . 33
3.2 Vendor Profiles . 36
3.2.1 Established Leaders . 36
3.2.2 Leading Challengers . 37
Case Study: Bot to Bot Communication Platforms. 40
3.2.3 Disruptors & Emulators . 41

4. Chatbots: Market Sizing & Forecasts

4.1 Chatbots Market Summary . 44
4.1.1 Introduction . 44
Figure 4.1: Chatbots Forecast Split . 44
4.1.2 Number of Chatbots Accessed Per Annum . 45
Figure & Table 4.2: Total Chatbot & Chatbot Apps Accessed per Annum (m), Split
by 8 Key Regions 2018-2023 . 45
4.1.3 Total Chatbots & Chatbot Application Spend . 46
Figure & Table 4.3: Total Spend from Chatbots & Chatbot Applications ($m), Split
by 8 Key Regions 2018-2023 . 46
4.1.4 Advertising Spend on Chatbots & Chatbot Applications . 47
Figure & Table 4.4: Total Advertising Spend on Chatbots & Chatbot Applications
($m), Split by 8 Key Regions 2018-2023 . 47
4.1.5 Cost Savings for Businesses . 48
Figure & Table 4.5: Total Cost Savings for Businesses for Chatbots & Chatbot
Applications ($m), Split by 8 Key Regions 2018-2023 . 48
Figure & Table 4.6: Total Cost Savings for Businesses for Chatbots & Chatbot
Applications (%), Split by Industry in 2023: $11.5 billion . 49
4.2 The Total Market for Messaging Application Chatbots . 50
4.2.1 Introduction . 50
Figure 4.7: Methodology for Messaging Application Chatbots . 50
4.2.2 Messaging App Chatbots which take Transactions . 51
Figure & Table 4.8: Total Messaging Application Chatbots Accessed per Annum
which Take Transactions (m), Split by 8 Key Regions 2018-2023 . 51
4.2.3 Total Spend from Messaging Application Chatbots. 52
Figure & Table 4.9: Total Spend from Messaging Application Chatbots ($m), Split
by 8 Key Regions 2018-2023. 52
4.2.4 Total Time Saved by Messaging Chatbots . 53
Figure & Table 4.10: Total Time Saved by Messaging Application Chatbots
(millions of hours), Split by 8 Key Regions 2018-2023 . 53
4.3 The Total Market for Discrete Application Chatbots . 54
4.3.1 Introduction . 54
Figure 4.11: Methodology for Discrete Application Chatbots . 54
4.3.2 Chatbot-enabled Applications Accessed Per Annum . 55
Figure & Table 4.12: Total Chatbot-enabled Applications Accessed per Annum
(m), Split by 8 Key Regions 2018-2023. 55
4.3.3 Total Spend Over Chatbot-enabled Applications . 56
Figure & Table 4.13: Total Spend from Chatbot-enabled Applications ($m), Split
by 8 Key Regions 2018-2023. 56
4.3.4 Total Advertising Spend on Chatbot-enabled Applications . 57
Figure & Table 4.14: Total Advertising Spend on Chatbot-enabled Applications
($m), Split by 8 Key Regions 2018-2023. 57
4.4 The Total Market for Web-based Chatbots . 58
4.4.1 Introduction . 58
Figure 4.15: Methodology for Web-based Chatbots . 58
4.4.2 Number of Chatbot-enabled Website Interactions Per
Annum . 59
Figure & Table 4.16: Total Number of Chatbot Site Visits per Annum (m), Split by
8 Key Regions 2018-2023 . 59
4.4.3 Total Spend Over Web-based Chatbots . 60
Figure & Table 4.17: Total Retail Spend from Web-based Chatbots ($m), Spit by 8
Key Regions 2018-2023 . 60
4.4.4 Total Time Saved from Web-based Chatbots . 61
Figure & Table 4.18: Total Time Saved from Web-based Chatbots in Hours (m),
Split by 8 Key Regions 2018-2023 . 61
4.4.5 Total Advertising Spend on Web-based Chatbots . 62
Figure & Table 4.19: Total Advertising Spend on Web-based Chatbots ($m), Split
by 8 Key Regions 2018-2023 . 62
4.5 Total Market for SMS Chatbots . 63
Figure 4.20: Methodology for SMS Chatbots . 63
4.5.1 Total A2P Messages Sent which are from Chatbot
Interactions . 64
Figure & Table 4.21: Total Number of A2P Messages Sent as a Result of Chatbot
Interactions per Annum (m), Split by 8 Key Regions 2018-2023 . 64

 

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