Global Natural Language Processing Market: Drivers, Restraints, Opportunities, Trends, and Forecasts to 2023
Global Natural Language Processing Market – Global Drivers, Restraints, Opportunities, Trends, and Forecasts up to 2023
Market Overview
In the present digitized world, 80% of the data generated is unstructured. Organizations are using natural language processing technology to unravel the meaning of such data to leverage business strategies and opportunities. A myriad of unstructured data is available online in the form of audio content, visual content and social footprints. Data has now become an asset for organizations. We have arrived into an era of automation of tedious cognitive tasks in businesses. Human beings fundamentally think, communicate and understand in an unstructured manner. Majority of the workflow in business and personal domain are either entirely controlled by humans or involves a human layer that converts the real-world inputs to computer inputs. NLP is gradually becoming ubiquitous in business enterprises and it has a wide array of functions ranging from chatbots and digital assistants such as Google Home, Siri and Alexa to compliance monitoring functions, business intelligence and analytics. Queries, email communication, videos, social media, support requests, customer reviews and so on are sources of useful insights that can be used to generate significant business value.
Natural language processing (NLP), also known as computational linguistics is an amalgamation of artificial intelligence, machine learning and linguistics. NLP is one of the most leveraged technologies in artificial intelligence and the growth of the technology is being propelled by the growth of related technologies such as deep learning and cognitive computing. NLP combines artificial intelligence, computer science and computational linguistics to help machines in reading texts by simulating the human ability of understanding languages. The technology offers competitive advantage to businesses in legal, media and digital ad services. Automotive, healthcare, education and the retail sectors are extensively investing in the technology, as NLP is continuously evolving and is capable of interpreting and adapting to a wide variety of human languages. Sentiment analysis is largely used in web and social media monitoring as it gives businesses access to the opinions of end-users about the organization and its services. Useful insights about customer preferences and attitudes can be obtained from the emoticons in social media. The use cases for natural language processing is diverse, covering customer service, autonomous vehicles, healthcare, banking, financial services and insurance (BFSI), manufacturing, retail and consumer goods, media and entertainment, research, education,high tech and electronics.
Technological mainstays namely Google, IBM, Microsoft and others are making significant investment in the field of natural language processing. NLP and text analytics have a major role to play in social media sentiment analysis, business intelligence, data governance, cognitive computing and business intelligence. Text analytics is a subset of NLP and is one amongst the two analytics options that NLP offers, alongside speech analytics. NLP helps in establishing relationships in documents, carrying out search, understanding the demarcations of sentences and phrases and determining names and places through semantic technologies. In the context of text analytics, NLP helps in identifying aspects of regulatory compliance, categorization, sentiment analysis and text clustering. NLP solutions are either statistics based, rule based or a hybrid.
Market Analysis
According to Infoholic Research, the Global Natural Language Processing market is expected to grow at a CAGR of 18.78% during the forecast period 2017–2023. The market is driven by factors such as the availability of a high volume of unstructured data, enhanced utility of smart devices, increased use of NLP in call centers, increased demand for better customer experience and expansive application areas. The future potential of the market is promising owing to opportunities such as developments in big data technologies, democratization of data, smart search and the emergence of human-like virtual assistants. The market growth is curbed by restraining factors such as difficulties in bridging gaps between humans and machines, training of researchers and loss of context and meaning.
Segmentation by Offerings
The market has been segmented and analyzed by the following offerings: Software, Hardware and Services.
Segmentation by Technologies
The market has been segmented and analyzed by the following technologies: Pattern and Image Recognition, Interactive Voice Response (IVR), Optical Character Recognition (OCR), Text Analytics, Speech Analytics, Classification and Categorization, Auto Coding, Professional Services and Support and Maintenance Services.
Segmentation by Regions
The market has been segmented and analyzed by the following regions: North America, EMEA, APAC and Latin America.
Segmentation by Verticals
The market has been segmented and analyzed by the following verticals: Healthcare and Lifesciences, Retail and Consumer Goods, High Tech and Electronics, Media and Entertainment, BFSI, Manufacturing, and Research and Education.
Benefits
The study covers and analyses the “Global Natural Language Processing Market”. Bringing out the complete key insights of the industry, the report aims to provide an opportunity for players to understand the latest trends, current market scenario, government initiatives, and technologies relevant to the market. In addition, it helps the venture capitalists in understanding the companies better and take informed decisions.The report covers drivers, restraints, and opportunities (DRO) affecting the market growth during the forecast period (2017–2023). It also contains an analysis of vendor profiles, which include financial health, business units, key business priorities, SWOT, strategies, and views. The report covers competitive landscape, which includes M&A, joint ventures and collaborations, and competitor comparison analysis. In the vendor profile section, for the companies that are privately held, financial information and revenue of segments will be limited.
Market Overview
In the present digitized world, 80% of the data generated is unstructured. Organizations are using natural language processing technology to unravel the meaning of such data to leverage business strategies and opportunities. A myriad of unstructured data is available online in the form of audio content, visual content and social footprints. Data has now become an asset for organizations. We have arrived into an era of automation of tedious cognitive tasks in businesses. Human beings fundamentally think, communicate and understand in an unstructured manner. Majority of the workflow in business and personal domain are either entirely controlled by humans or involves a human layer that converts the real-world inputs to computer inputs. NLP is gradually becoming ubiquitous in business enterprises and it has a wide array of functions ranging from chatbots and digital assistants such as Google Home, Siri and Alexa to compliance monitoring functions, business intelligence and analytics. Queries, email communication, videos, social media, support requests, customer reviews and so on are sources of useful insights that can be used to generate significant business value.
Natural language processing (NLP), also known as computational linguistics is an amalgamation of artificial intelligence, machine learning and linguistics. NLP is one of the most leveraged technologies in artificial intelligence and the growth of the technology is being propelled by the growth of related technologies such as deep learning and cognitive computing. NLP combines artificial intelligence, computer science and computational linguistics to help machines in reading texts by simulating the human ability of understanding languages. The technology offers competitive advantage to businesses in legal, media and digital ad services. Automotive, healthcare, education and the retail sectors are extensively investing in the technology, as NLP is continuously evolving and is capable of interpreting and adapting to a wide variety of human languages. Sentiment analysis is largely used in web and social media monitoring as it gives businesses access to the opinions of end-users about the organization and its services. Useful insights about customer preferences and attitudes can be obtained from the emoticons in social media. The use cases for natural language processing is diverse, covering customer service, autonomous vehicles, healthcare, banking, financial services and insurance (BFSI), manufacturing, retail and consumer goods, media and entertainment, research, education,high tech and electronics.
Technological mainstays namely Google, IBM, Microsoft and others are making significant investment in the field of natural language processing. NLP and text analytics have a major role to play in social media sentiment analysis, business intelligence, data governance, cognitive computing and business intelligence. Text analytics is a subset of NLP and is one amongst the two analytics options that NLP offers, alongside speech analytics. NLP helps in establishing relationships in documents, carrying out search, understanding the demarcations of sentences and phrases and determining names and places through semantic technologies. In the context of text analytics, NLP helps in identifying aspects of regulatory compliance, categorization, sentiment analysis and text clustering. NLP solutions are either statistics based, rule based or a hybrid.
Market Analysis
According to Infoholic Research, the Global Natural Language Processing market is expected to grow at a CAGR of 18.78% during the forecast period 2017–2023. The market is driven by factors such as the availability of a high volume of unstructured data, enhanced utility of smart devices, increased use of NLP in call centers, increased demand for better customer experience and expansive application areas. The future potential of the market is promising owing to opportunities such as developments in big data technologies, democratization of data, smart search and the emergence of human-like virtual assistants. The market growth is curbed by restraining factors such as difficulties in bridging gaps between humans and machines, training of researchers and loss of context and meaning.
Segmentation by Offerings
The market has been segmented and analyzed by the following offerings: Software, Hardware and Services.
Segmentation by Technologies
The market has been segmented and analyzed by the following technologies: Pattern and Image Recognition, Interactive Voice Response (IVR), Optical Character Recognition (OCR), Text Analytics, Speech Analytics, Classification and Categorization, Auto Coding, Professional Services and Support and Maintenance Services.
Segmentation by Regions
The market has been segmented and analyzed by the following regions: North America, EMEA, APAC and Latin America.
Segmentation by Verticals
The market has been segmented and analyzed by the following verticals: Healthcare and Lifesciences, Retail and Consumer Goods, High Tech and Electronics, Media and Entertainment, BFSI, Manufacturing, and Research and Education.
Benefits
The study covers and analyses the “Global Natural Language Processing Market”. Bringing out the complete key insights of the industry, the report aims to provide an opportunity for players to understand the latest trends, current market scenario, government initiatives, and technologies relevant to the market. In addition, it helps the venture capitalists in understanding the companies better and take informed decisions.
1. INDUSTRY OUTLOOK
1.1 Industry Overview
1.2 Industry Trends
1.3 PEST Analysis
2 REPORT OUTLINE
2.1 Report Scope
2.2 Report Summary
2.3 Research Methodology
2.4 Report Assumptions
3 MARKET SNAPSHOT
3.1 Total Addressable Market
3.2 Segmented Addressable Market
3.3 Related Markets
3.3.1 Machine Learning Market
3.3.2 Artificial Intelligence Market
4 MARKET OUTLOOK
4.1 Overview
4.2 Regulatory Bodies and Standards
4.3 Porter 5 (Five) Forces
5 MARKET CHARACTERISTICS
5.1 Use Cases of Natural Language Processing
5.2 Market Segmentation
5.3 Market Dynamics
5.3.1 Drivers
5.3.1.1 High Volume of Unstructured Data
5.3.1.2 Enhanced utility of smart devices
5.3.1.3 Increased use of NLP in customer call centres
5.3.1.4 Increased demand for better customer experience
5.3.1.5 Expanding application areas
5.3.2 Restraints
5.3.2.1 Bridging the gap between humans and machines
5.3.2.2 Training of researchers
5.3.2.3 Loss of context and meaning
5.3.3 Opportunities
5.3.3.1 Development in Big Data Technologies
5.3.3.2 NLP will democratize data
5.3.3.3 Smart Search
5.3.3.4 Emergence of human like virtual assistants
5.4 DRO – Impact Analysis
6 TRENDS, ROADMAP, AND PROJECTS
6.1 Market Trends & Impact
6.2 Technology Roadmap
7 GEOGRAPHIC SEGMENTATION: MARKET SIZE AND ANALYSIS
7.1 Overview
7.2 North America
7.2.1 US
7.2.2 Canada
7.3 EMEA
7.3.1 The UK
7.3.2 Germany
7.4 Asia Pacific
7.4.1 India
7.4.2 China
7.4.3 Japan
7.5 Latin America
8. NATURAL LANGUAGE PROCESSING MARKET BY OFFERINGS
8.1 Software Offerings
8.2 Hardware
8.3 Services
9. NATURAL LANGUAGE PROCESSING MARKET BY DEPLOYMENT MODE
9.1 Public
9.2 Private
9.3 Hybrid
10. GLOBAL NATURAL LANGUAGE PROCESSING MARKET BY TECHNOLOGIES
10.1 Pattern and Image Recognition
10.2 Interactive Voice Response (IVR)
10.3 Optical Character Recognition (OCR)
10.4 Text Analytics
10.5 Speech Analytics
10.6 Classification and Categorization
10.7 Auto Coding
10.8 Professional Services
10.9 Support and Maintenance Services
11. NATURAL LANGUAGE PROCESSING MARKET BY VERTICALS
11.1 Healthcare and Lifesciences
11.2 Retail and Consumer Goods
11.3 High Tech and Electronics
11.4 Media and Entertainment
11.5 BFSI
11.6 Manufacturing
11.7 Research and Education
12. VENDORS PROFILES
12.1 Microsoft Corporation
12.1.1 Overview
12.1.2 Business Units
12.1.3 Microsoft Corporation in Natural Language Processing
12.1.4 Business Focus
12.1.5 SWOT Analysis
12.1.6 Business Strategies
12.2 IBM Corporation
12.2.1 Overview
12.2.2 Business Units
12.2.3 Geographic Revenue
12.2.4 IBM Corporation in Natural Language Processing
12.2.5 Business Focus
12.2.6 SWOT Analysis
12.2.7 Business Strategies
12.3 Google Inc.
12.3.1 Overview
12.3.2 Business Units
12.3.3 Geographic Revenue
12.3.4 Google Inc. in Natural Language Processing
12.3.5 Business Focus
12.3.6 SWOT Analysis
12.3.7 Business Strategies
12.4 Apple Inc.
12.4.1 Overview
12.4.2 Business units
12.4.3 Geographic revenue
12.4.4 Apple in Natural Language Processing
12.4.5 Business focus
12.4.6 SWOT analysis
12.4.7 Business strategies
13 COMPANIES TO WATCH FOR
13.1 Addstructure
13.1.1 Overview
13.1.2 Addstructure Offerings
13.2 Angel.ai
13.2.1 Overview
13.2.2 Angel.ai Offerings
13.3 Klevu Oy
13.3.1 Overview
13.3.2 Klevu Offerings
13.4 Twiggle
13.4.1 Overview
13.4.2 Twiggle Offerings
13.5 Dialogflow (Formerly known as Api.ai)
13.5.1 Overview
13.5.2 Dialogflow Offerings
13.6 Mindmeld (Acquired by Cisco)
13.6.1 Overview
13.6.2 Mindmeld Offerings
13.7 DigitalGenius
13.7.1 Overview
13.7.2 DigitalGenius Offerings
13.8 Inbenta
13.8.1 Overview
13.8.2 Inbenta Offerings
13.9 Satisfi Labs Inc.
13.9.1 Overview
13.9.2 Satisfi Labs Inc. Offerings
13.10 NetBase
13.10.1 Overview
13.10.2 NetBase Offerings
Annexure
Abbreviations
Tables
Table 1 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY REGIONS, 2017-2023 ($BILLION)
Table 2 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OFFERINGS, 2017-2023 ($BILLION)
Table 3 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY DEPLOYMENT MODE, 2017-2023 ($BILLION)
Table 4 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY TECHNOLOGIES, 2017-2023 ($BILLION)
Table 5 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY VERTICALS, 2017-2023 ($BILLION)
Charts
Chart 1 PEST ANALYSIS OF GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 2 RESEARCH METHODOLOGY OF NATURAL LANGUAGE PROCESSING MARKET
Chart 3 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE, 2017-2023 ($BILLION)
Chart 4 PORTER 5 FORCES ON GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 5 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SEGMENTATION
Chart 6 MARKET DYNAMICS – DRIVERS, RESTRAINTS & OPPORTUNITIES
Chart 7 DRO – IMPACT ANALYSIS OF GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 8 TECHNOLOGY ROADMAP FOR GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 9 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SHARE BY GEOGRAPHIES, 2017 AND 2023
Chart 10 NATURAL LANGUAGE MARKET REVENUE IN NORTH AMERICA, 2017–2023 ($BILLION)
Chart 11 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE IN EMEA, 2017–2023 ($BILLION)
Chart 12 NATURAL LANGUAGE PROCESSING MARKET REVENUE IN ASIA PACIFIC, 2017–2023 ($BILLION)
Chart 13 NATURAL LANGUAGE PROCESSING MARKET REVENUE IN LATIN AMERICA, 2017–2023 ($BILLION)
Chart 14 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OFFERINGS ($MILLION)
Chart 15 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SOFTWARE OFFERINGS ($BILLION)
Chart 16 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HARDWARE OFFERINGS ($BILLION)
Chart 17 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SERVICES OFFERINGS ($BILLION)
Chart 18 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY DEPOLOYMENT MODES ($BILLION)
Chart 19 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PUBLIC DEPLOYMENT MODE ($BILLION)
Chart 20 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PRIVATE DEPLOYMENT MODE ($BILLION)
Chart 21 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HYBRID DEPLOYMENT MODE ($BILLION)
Chart 22 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY APPLICATIONS, 2017–2023 ($BILLION)
Chart 23 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PATTERN AND IMAGE RECOGNITION, 2017–2023 ($BILLION)
Chart 24 GLOBAL NATURAL LANGUAGE MARKET REVENUE BY INTERACTIVE VOICE RESPONSE, 2017–2023 ($BILLION)
Chart 25 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OPTICAL CHARACTER RECOGNITION, 2017–2023 ($BILLION)
Chart 26 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY TEXT ANALYTICS, 2017–2023 ($BILLION)
Chart 27 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SPEECH ANALYTICS, 2017–2023 ($BILLION)
Chart 28 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY CLASSFICATION AND CATEGORIZATION, 2017–2023 ($BILLION)
Chart 29 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY AUTO CODING, 2017–2023 ($BILLION)
Chart 30 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PROFESSIONAL SERVICES, 2017–2023 ($BILLION)
Chart 31 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SUPPORT AND MAINTENANCE SERVICES, 2017–2023 ($BILLION)
Chart 32 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY VERTICALS, 2017–2023 ($BILLION)
Chart 33 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HEALTHCARE AND LIFESCIENCES, 2017-2023 ($BILLION)
Chart 34 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY RETAIL AND CONSUMER GOODS, 2017-2023 ($BILLION)
Chart 35 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HIGH TECH AND ELECTRONICS, 2017-2023 ($BILLION)
Chart 36 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY MEDIA AND ENTERTAINMENT, 2017-2023 ($BILLION)
Chart 37 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY BFSI, 2017-2023 ($BILLION)
Chart 38 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY MANUFACTURING, 2017-2023 ($BILLION)
Chart 39 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY RESEARCH AND EDUCATION, 2017-2023 ($BILLION)
Chart 40 MICROSOFT CORPORATION: OVERVIEW SNAPSHOT
Chart 41 MICROSOFT CORPORATION: BUSINESS UNITS
Chart 42 MICROSOFT CORPORATION: SWOT ANALYSIS
Chart 43 IBM CORPORATION: OVERVIEW SNAPSHOT
Chart 44 IBM CORPORATION: BUSINESS UNITS
Chart 45 IBM CORPORATION: GEOGRAPHIC REVENUE
Chart 46 IBM CORPORATION: SWOT ANALYSIS
Chart 47 GOOGLE INC.: OVERVIEW SNAPSHOT
Chart 48 GOOGLE INC.: BUSINESS UNITS
Chart 49 GOOGLE INC.: GEOGRAPHIC REVENUE
Chart 50 GOOGLE INC.: SWOT ANALYSIS
Chart 51 APPLE INC.: OVERVIEW SNAPSHOT
Chart 52 APPLE INC.: BUSINESS UNITS
Chart 53 APPLE INC.: GEOGRAPHIC REVENUE
Chart 54 APPLE INC.: SWOT ANALYSIS
1.1 Industry Overview
1.2 Industry Trends
1.3 PEST Analysis
2 REPORT OUTLINE
2.1 Report Scope
2.2 Report Summary
2.3 Research Methodology
2.4 Report Assumptions
3 MARKET SNAPSHOT
3.1 Total Addressable Market
3.2 Segmented Addressable Market
3.3 Related Markets
3.3.1 Machine Learning Market
3.3.2 Artificial Intelligence Market
4 MARKET OUTLOOK
4.1 Overview
4.2 Regulatory Bodies and Standards
4.3 Porter 5 (Five) Forces
5 MARKET CHARACTERISTICS
5.1 Use Cases of Natural Language Processing
5.2 Market Segmentation
5.3 Market Dynamics
5.3.1 Drivers
5.3.1.1 High Volume of Unstructured Data
5.3.1.2 Enhanced utility of smart devices
5.3.1.3 Increased use of NLP in customer call centres
5.3.1.4 Increased demand for better customer experience
5.3.1.5 Expanding application areas
5.3.2 Restraints
5.3.2.1 Bridging the gap between humans and machines
5.3.2.2 Training of researchers
5.3.2.3 Loss of context and meaning
5.3.3 Opportunities
5.3.3.1 Development in Big Data Technologies
5.3.3.2 NLP will democratize data
5.3.3.3 Smart Search
5.3.3.4 Emergence of human like virtual assistants
5.4 DRO – Impact Analysis
6 TRENDS, ROADMAP, AND PROJECTS
6.1 Market Trends & Impact
6.2 Technology Roadmap
7 GEOGRAPHIC SEGMENTATION: MARKET SIZE AND ANALYSIS
7.1 Overview
7.2 North America
7.2.1 US
7.2.2 Canada
7.3 EMEA
7.3.1 The UK
7.3.2 Germany
7.4 Asia Pacific
7.4.1 India
7.4.2 China
7.4.3 Japan
7.5 Latin America
8. NATURAL LANGUAGE PROCESSING MARKET BY OFFERINGS
8.1 Software Offerings
8.2 Hardware
8.3 Services
9. NATURAL LANGUAGE PROCESSING MARKET BY DEPLOYMENT MODE
9.1 Public
9.2 Private
9.3 Hybrid
10. GLOBAL NATURAL LANGUAGE PROCESSING MARKET BY TECHNOLOGIES
10.1 Pattern and Image Recognition
10.2 Interactive Voice Response (IVR)
10.3 Optical Character Recognition (OCR)
10.4 Text Analytics
10.5 Speech Analytics
10.6 Classification and Categorization
10.7 Auto Coding
10.8 Professional Services
10.9 Support and Maintenance Services
11. NATURAL LANGUAGE PROCESSING MARKET BY VERTICALS
11.1 Healthcare and Lifesciences
11.2 Retail and Consumer Goods
11.3 High Tech and Electronics
11.4 Media and Entertainment
11.5 BFSI
11.6 Manufacturing
11.7 Research and Education
12. VENDORS PROFILES
12.1 Microsoft Corporation
12.1.1 Overview
12.1.2 Business Units
12.1.3 Microsoft Corporation in Natural Language Processing
12.1.4 Business Focus
12.1.5 SWOT Analysis
12.1.6 Business Strategies
12.2 IBM Corporation
12.2.1 Overview
12.2.2 Business Units
12.2.3 Geographic Revenue
12.2.4 IBM Corporation in Natural Language Processing
12.2.5 Business Focus
12.2.6 SWOT Analysis
12.2.7 Business Strategies
12.3 Google Inc.
12.3.1 Overview
12.3.2 Business Units
12.3.3 Geographic Revenue
12.3.4 Google Inc. in Natural Language Processing
12.3.5 Business Focus
12.3.6 SWOT Analysis
12.3.7 Business Strategies
12.4 Apple Inc.
12.4.1 Overview
12.4.2 Business units
12.4.3 Geographic revenue
12.4.4 Apple in Natural Language Processing
12.4.5 Business focus
12.4.6 SWOT analysis
12.4.7 Business strategies
13 COMPANIES TO WATCH FOR
13.1 Addstructure
13.1.1 Overview
13.1.2 Addstructure Offerings
13.2 Angel.ai
13.2.1 Overview
13.2.2 Angel.ai Offerings
13.3 Klevu Oy
13.3.1 Overview
13.3.2 Klevu Offerings
13.4 Twiggle
13.4.1 Overview
13.4.2 Twiggle Offerings
13.5 Dialogflow (Formerly known as Api.ai)
13.5.1 Overview
13.5.2 Dialogflow Offerings
13.6 Mindmeld (Acquired by Cisco)
13.6.1 Overview
13.6.2 Mindmeld Offerings
13.7 DigitalGenius
13.7.1 Overview
13.7.2 DigitalGenius Offerings
13.8 Inbenta
13.8.1 Overview
13.8.2 Inbenta Offerings
13.9 Satisfi Labs Inc.
13.9.1 Overview
13.9.2 Satisfi Labs Inc. Offerings
13.10 NetBase
13.10.1 Overview
13.10.2 NetBase Offerings
Annexure
Abbreviations
Tables
Table 1 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY REGIONS, 2017-2023 ($BILLION)
Table 2 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OFFERINGS, 2017-2023 ($BILLION)
Table 3 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY DEPLOYMENT MODE, 2017-2023 ($BILLION)
Table 4 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY TECHNOLOGIES, 2017-2023 ($BILLION)
Table 5 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY VERTICALS, 2017-2023 ($BILLION)
Charts
Chart 1 PEST ANALYSIS OF GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 2 RESEARCH METHODOLOGY OF NATURAL LANGUAGE PROCESSING MARKET
Chart 3 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE, 2017-2023 ($BILLION)
Chart 4 PORTER 5 FORCES ON GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 5 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SEGMENTATION
Chart 6 MARKET DYNAMICS – DRIVERS, RESTRAINTS & OPPORTUNITIES
Chart 7 DRO – IMPACT ANALYSIS OF GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 8 TECHNOLOGY ROADMAP FOR GLOBAL NATURAL LANGUAGE PROCESSING MARKET
Chart 9 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SHARE BY GEOGRAPHIES, 2017 AND 2023
Chart 10 NATURAL LANGUAGE MARKET REVENUE IN NORTH AMERICA, 2017–2023 ($BILLION)
Chart 11 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE IN EMEA, 2017–2023 ($BILLION)
Chart 12 NATURAL LANGUAGE PROCESSING MARKET REVENUE IN ASIA PACIFIC, 2017–2023 ($BILLION)
Chart 13 NATURAL LANGUAGE PROCESSING MARKET REVENUE IN LATIN AMERICA, 2017–2023 ($BILLION)
Chart 14 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OFFERINGS ($MILLION)
Chart 15 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SOFTWARE OFFERINGS ($BILLION)
Chart 16 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HARDWARE OFFERINGS ($BILLION)
Chart 17 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SERVICES OFFERINGS ($BILLION)
Chart 18 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY DEPOLOYMENT MODES ($BILLION)
Chart 19 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PUBLIC DEPLOYMENT MODE ($BILLION)
Chart 20 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PRIVATE DEPLOYMENT MODE ($BILLION)
Chart 21 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HYBRID DEPLOYMENT MODE ($BILLION)
Chart 22 NATURAL LANGUAGE PROCESSING MARKET REVENUE BY APPLICATIONS, 2017–2023 ($BILLION)
Chart 23 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PATTERN AND IMAGE RECOGNITION, 2017–2023 ($BILLION)
Chart 24 GLOBAL NATURAL LANGUAGE MARKET REVENUE BY INTERACTIVE VOICE RESPONSE, 2017–2023 ($BILLION)
Chart 25 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY OPTICAL CHARACTER RECOGNITION, 2017–2023 ($BILLION)
Chart 26 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY TEXT ANALYTICS, 2017–2023 ($BILLION)
Chart 27 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SPEECH ANALYTICS, 2017–2023 ($BILLION)
Chart 28 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY CLASSFICATION AND CATEGORIZATION, 2017–2023 ($BILLION)
Chart 29 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY AUTO CODING, 2017–2023 ($BILLION)
Chart 30 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY PROFESSIONAL SERVICES, 2017–2023 ($BILLION)
Chart 31 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY SUPPORT AND MAINTENANCE SERVICES, 2017–2023 ($BILLION)
Chart 32 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY VERTICALS, 2017–2023 ($BILLION)
Chart 33 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HEALTHCARE AND LIFESCIENCES, 2017-2023 ($BILLION)
Chart 34 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY RETAIL AND CONSUMER GOODS, 2017-2023 ($BILLION)
Chart 35 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY HIGH TECH AND ELECTRONICS, 2017-2023 ($BILLION)
Chart 36 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY MEDIA AND ENTERTAINMENT, 2017-2023 ($BILLION)
Chart 37 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY BFSI, 2017-2023 ($BILLION)
Chart 38 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY MANUFACTURING, 2017-2023 ($BILLION)
Chart 39 GLOBAL NATURAL LANGUAGE PROCESSING MARKET REVENUE BY RESEARCH AND EDUCATION, 2017-2023 ($BILLION)
Chart 40 MICROSOFT CORPORATION: OVERVIEW SNAPSHOT
Chart 41 MICROSOFT CORPORATION: BUSINESS UNITS
Chart 42 MICROSOFT CORPORATION: SWOT ANALYSIS
Chart 43 IBM CORPORATION: OVERVIEW SNAPSHOT
Chart 44 IBM CORPORATION: BUSINESS UNITS
Chart 45 IBM CORPORATION: GEOGRAPHIC REVENUE
Chart 46 IBM CORPORATION: SWOT ANALYSIS
Chart 47 GOOGLE INC.: OVERVIEW SNAPSHOT
Chart 48 GOOGLE INC.: BUSINESS UNITS
Chart 49 GOOGLE INC.: GEOGRAPHIC REVENUE
Chart 50 GOOGLE INC.: SWOT ANALYSIS
Chart 51 APPLE INC.: OVERVIEW SNAPSHOT
Chart 52 APPLE INC.: BUSINESS UNITS
Chart 53 APPLE INC.: GEOGRAPHIC REVENUE
Chart 54 APPLE INC.: SWOT ANALYSIS
