Global Natural Language Processing Market: Drivers, Restraints, Opportunities, Trends, and Forecasts to 2023

  • Product Code:
    RP-ID-10078073
  • Published Date:
    Mar 2019
  • Region:
    Global
  • Pages:
    99
  • Category:
    ICT & Telecom
  • Publisher:
    Infoholic Research
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.

Table of Contents
1. Industry Outlook 10
1.1 Industry Overview 10
1.2 Industry Trends 11
1.3 PEST Analysis 14
2 Report Outline 14
2.1 Report Scope 14
2.2 Report Summary 15
2.3 Research Methodology 16
2.4 Report Assumptions 17
3 Market Snapshot 18
3.1 Total Addressable Market 18
3.2 Segmented Addressable Market 18
3.3 Related Markets 18
3.3.1 Machine Learning Market 18
3.3.2 Artificial Intelligence Market 19
4 Market Outlook 20
4.1 Overview 20
4.2 Regulatory Bodies and Standards 21
4.3 Porter 5 (Five) Forces 21
5 Market Characteristics 23
5.1 Use Cases of Natural Language Processing 25
5.2 Market Segmentation 27
5.3 Market Dynamics 27
5.3.1 Drivers 28
5.3.1.1 High Volume of Unstructured Data 28
5.3.1.2 Enhanced utility of smart devices 29
5.3.1.3 Increased use of NLP in customer call centres 29
5.3.1.4 Increased demand for better customer experience 29
5.3.1.5 Expanding application areas 30
5.3.2 Restraints 30
5.3.2.1 Bridging the gap between humans and machines 30
5.3.2.2 Training of researchers 30
5.3.2.3 Loss of context and meaning 30
5.3.3 Opportunities 32
5.3.3.1 Development in Big Data Technologies 32
5.3.3.2 NLP will democratize data 32
5.3.3.3 Smart Search 32
5.3.3.4 Emergence of human like virtual assistants 32
5.4 DRO – Impact Analysis 32
6 Trends, Roadmap, and Projects 33
6.1 Market Trends & Impact 33
6.2 Technology Roadmap 34
7 Geographic Segmentation: Market Size and Analysis 35
7.1 Overview 35
7.2 North America 36
7.2.1 US 38
7.2.2 Canada 38
7.3 EMEA 38
7.3.1 The UK 39
7.3.2 Germany 39
7.4 Asia Pacific 40
7.4.1 India 40
7.4.2 China 41
7.4.3 Japan 41
7.5 Latin America 42
8. Natural Language Processing Market by Offerings 43
8.1 Software Offerings 44
8.2 Hardware 45
8.3 Services 46
9. Natural Language Processing Market by Deployment Mode 47
9.1 Public 49
9.2 Private 50
9.3 Hybrid 51
10. Global Natural Language Processing Market by Technologies 51
10.1 Pattern and Image Recognition 53
10.2 Interactive Voice Response (IVR) 53
10.3 Optical Character Recognition (OCR) 54
10.4 Text Analytics 54
10.5 Speech Analytics 55
10.6 Classification and Categorization 56
10.7 Auto Coding 56
10.8 Professional Services 57
10.9 Support and Maintenance Services 58
11. Natural Language Processing Market by Verticals 59
11.1 Healthcare and Lifesciences 60
11.2 Retail and Consumer Goods 61
11.3 High Tech and Electronics 61
11.4 Media and Entertainment 62
11.5 BFSI 63
11.6 Manufacturing 63
11.7 Research and Education 64
12. Vendors Profiles 66
12.1 Microsoft Corporation 66
12.1.1 Overview 66
12.1.2 Business Units 67
12.1.3 Microsoft Corporation in Natural Language Processing 68
12.1.4 Business Focus 69
12.1.5 SWOT Analysis 70
12.1.6 Business Strategies 70
12.2 IBM Corporation 72
12.2.1 Overview 72
12.2.2 Business Units 73
12.2.3 Geographic Revenue 75
12.2.4 IBM Corporation in Natural Language Processing 75
12.2.5 Business Focus 76
12.2.6 SWOT Analysis 76
12.2.7 Business Strategies 77
12.3 Google Inc. 78
12.3.1 Overview 78
12.3.2 Business Units 79
12.3.3 Geographic Revenue 80
12.3.4 Google Inc. in Natural Language Processing 81
12.3.5 Business Focus 82
12.3.6 SWOT Analysis 82
12.3.7 Business Strategies 83
12.4 Apple Inc. 83
12.4.1 Overview 83
12.4.2 Business units 84
12.4.3 Geographic revenue 86
12.4.4 Apple in Natural Language Processing 87
12.4.5 Business focus 87
12.4.6 SWOT analysis 88
12.4.7 Business strategies 88
13 Companies to Watch for 92
13.1 Addstructure 92
13.1.1 Overview 92
13.1.2 Addstructure Offerings 92
13.2 Angel.ai 92
13.2.1 Overview 92
13.2.2 Angel.ai Offerings 93
13.3 Klevu Oy 93
13.3.1 Overview 93
13.3.2 Klevu Offerings 93
13.4 Twiggle 93
13.4.1 Overview 93
13.4.2 Twiggle Offerings 94
13.5 Dialogflow (Formerly known as Api.ai) 94
13.5.1 Overview 94
13.5.2 Dialogflow Offerings 95
13.6 Mindmeld (Acquired by Cisco) 95
13.6.1 Overview 95
13.6.2 Mindmeld Offerings 95
13.7 DigitalGenius 96
13.7.1 Overview 96
13.7.2 DigitalGenius Offerings 96
13.8 Inbenta 96
13.8.1 Overview 96
13.8.2 Inbenta Offerings 97
13.9 Satisfi Labs Inc. 97
13.9.1 Overview 97
13.9.2 Satisfi Labs Inc. Offerings 97
13.10 NetBase 97
13.10.1 Overview 97
13.10.2 NetBase Offerings 98
Annexure 99
Abbreviations 99

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Microsoft Corporation,IBM Corporation,Google Inc.Apple Inc.,Addstructure, Angel.ai, Klevu Oy,Twiggle, Dialogflow (Formerly known as Api.ai), Mindmeld (Acquired by Cisco), DigitalGenius, inbenta, Satisfi Labs Inc. NetBase
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