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IC20115343 |
Pages: 353 |
Apr 2021 |
The global natural language processing market was valued at $9,701.56 million in 2019, and is projected to reach $42,389.83 million by 2027, at a CAGR of 20.6%.
The adoption of natural language processing is rapidly increasing along with the increase in demand for big data, data analytics, powerful computing, and enhanced algorithms.
Complexities due to the usage of code-mixed language while implementing natural language processing solutions is hindering the market growth.
North America was the highest revenue contributor, accounting for $3,669.1 million in 2019, and is estimated to grow with a CAGR of 19.5%.
Natural language processing is a sub-field of linguistics, computer science, and artificial intelligence that is concerned with the interactions between computers and human language that results in computers processing and analyzing large amounts of natural language data.
The natural language processing market has witnessed a severe impact in 2020 due to the outbreak of the coronavirus pandemic. The pandemic increased the rate of attrition and affected almost every industry. The lockdown had a negative impact on the global manufacturing units and the supply chains as the continuity of operations of all the verticals was severely disrupted. The sectors or verticals facing the maximum impact are manufacturing, transportation, retail, supply chain and logistics and consumer goods. The availability of essential goods was impacted due to the lockdown regulations and also due to the lack of manpower. However, it is expected that by the end of 2021, the situation might come under control as the demand for natural language processing solutions and services is increasing due to the increased demand for enhancing customers experiences in various industries such as healthcare. To enable digital transformation initiatives several sectors are already planning to deploy a diverse array of natural language processing solutions and services. These initiatives will improve operations and enhance customer viewing experience. The reduction in operational costs, better customer experiences, improved customer rate of attrition, enhanced visibility into processes and operations, improved real-time decision-making are key business, and operational priorities are expected to drive the adoption of NLP.
It is important and necessary to understand the customers feedbacks and requirements which is becoming very difficult in the present scenario, because of the increasing number of channels through which the clients provide their requirement or feedback. In order to understand these requirements and feedbacks related to products or services and companies are constantly looking for an opportunity to understand and enhance customer experience capabilities. Artificial intelligence and natural language processing assist companies in analyzing the customer inquiry or feedbacks and is further converted them into individual solutions. These factors are anticipated to drive the market growth over the projected time frame.
To know more about global application security market drivers, get in touch with our analysts here.
Code-Mixed (CM) language is the alteration of languages within a conversation and is a common communicative phenomenon that occurs in multilingual communities across the world. CM language has been associated with informal or casual speech. There is evidence that the CM language has become the default code of communication in several societies, such as urban India and Mexico. CM also has pervaded written text, especially in computer-mediated communication and social media. NLP processes such as normalization, language identification, language modeling, part-of-speech tagging, dependency parsing, machine translation, and Automatic Speech Recognition (ASR) face issues while working on non-canonical multilingual data as two or more languages are mixed. The processes of NLP are restrained due to the presence of various codes and languages.
The healthcare sub-segment is generating a large amount of data nowadays, with an increased pace of digitalization among hospitals and other healthcare premises. Healthcare organizations are working on enormous amount of useful data with the analytics-driven approach. However, such organizations are finding it difficult without a sophisticated systems as it is challenging to analyze the text data. As a consequence, NLP has appeared as an important technology to extract meaningful insights from large volumes of data. The consequent demand for effective data management and advanced data analytics has also seen a significant rise in the healthcare industry over the last ten years. Moreover, it is expected that there will be a huge scope of opportunities for NLP technologies in the healthcare industry in the next five years. Personal Health Records (PHRs) are becoming widely accepted and new initiatives have been taken to make it easier to download and share medical records with different medical and insurance providers. For instance, NLP systems could extract any notes in a patient's electronic record that mention prescribed medications and if they were effective. It is expected that this market will further flourish with the growing trend of superior data management and analytics of mobile apps.
On the basis of component, natural language processing is divided into solutions and services.
Source: Research Dive Analysis
The solution sub-segment was the highest contributor to the market, with $5,048.3 million in 2019, and is estimated to grow at a CAGR of 19.1% during the forecast period. The demand for NLP software tools and platforms is increasing globally due to the rising demand to gain real-time insights from voice or speech data across different verticals.
Source: Research Dive Analysis
The on-premises sub-segment was the highest contributor to the market, with $5,327.9 million in 2019, and is estimated to grow at a CAGR of 18.2% during the forecast period. Additionally, cloud sub segment is anticipated to grow at a highest CAGR, as cloud-based natural language processing platform enables users to utilize and analyze multilingual content, user-generated content, and other web-content in a more secure manner and can access this data from anywhere in the world.
Source: Research Dive Analysis
The statistical sub-segment was the highest contributor to the market, with $3,701.6 million in 2019, and is estimated to grow at a CAGR of 19.1% during the forecast period. Statistical natural language processing (NLP) intends to perform statistical inference for the field of natural language processing. Statistical NLP also enables natural conversations between chat-bots and humans.
Source: Research Dive Analysis
The machine translation (MT) sub-segment was the highest contributor to the market, with $2,394.3 million in 2019, and is expected to grow at a CAGR of 19.0% during the upcoming period. One of the key factor driving the MT sub-segment is this system enables you to save your time while translating large texts. This advantage of machine translation is increasing the sub-segment growth.
Source: Research Dive Analysis
The media and entertainment sub-segment was the highest contributor to the market, with $1,931.1 million in 2019, and is expected to grow at a CAGR of 19.1% during the forecast period. The rising adoption of digital platforms in entertainment has been transforming how media companies around the world operate and advertise to reach their audience. There is a dire need for adding personalization and delivering value to meet the rising customer expectations and demands. Several companies in the media and entertainment sector are turning to artificial intelligence (AI) technologies to deliver great customer experiences at a large scale.
Source: Research Dive Analysis
Investment Opportunities by Start-ups is Increasing the Market Share in North America
North America was the highest revenue contributor, accounting for $3,669.1 million in 2019, and is expected to experience the highest CAGR of 19.5%. The organizations in North America are investing in the advancements of NLP and its applications. With the increasing unstructured data produced by many start-ups in the U.S. are gradually deploying natural language processing services. Furthermore, many start-up companies are entering in the NLP market in the countries like U.S. This is due to increasing demand for AI and NLP enabled products and solutions that are present in the market.
Increasing Investments in Artificial Intelligence are Driving the Market Growth in Asia-Pacific Region
Asia-Pacific region is expected to grow at the highest CAGR of 21.1% during the forecast period from $2039.30 million in 2019 on the account of rising awareness and increasing investments in artificial intelligence. Increasing investment in AI by Chinese players such as Baidu and Alibaba are contributing significantly towards the revenue growth. Moreover, the increasing adoption of the smart devices in this region is also driving the growth of the market.
Source: Research Dive Analysis
Some of the leading NLP market players IBM, Microsoft, Google, Amazon, Facebook, Apple Inc., 3M, Intel, Baidu, Inc. SAS Institute Inc. Established as well as start-up organizations operating in the natural language processing industry are focusing majorly on advanced technological developments, mergers & acquisitions, business expansion, and others.
Porter’s Five Forces Analysis for Natural Language Processing Market:
Aspect | Particulars |
Historical Market Estimations | 2018-2019 |
Base Year for Market Estimation | 2019 |
Forecast timeline for Market Projection | 2020-2027 |
Geographical Scope | North America, Europe, Asia-Pacific, LAMEA |
Segmentation by Component |
|
Segmentation by Deployment Mode |
|
Segmentation by Type |
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Segmentation by Application |
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Segmentation by Vertical |
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Key Countries Covered | The U.S.,Canada, Mexico, Germany, France, UK, Italy, Spain, Rest of Europe, China, Australia, Japan, India, South Korea, Rest of Asia-Pacific, Latin America, Middle East, and Africa |
Key Companies Profiled |
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1.Research Methodology
1.1.Desk Research
1.2.Real time insights and validation
1.3.Forecast model
1.4.Assumptions and forecast parameters
1.4.1.Assumptions
1.4.2.Forecast parameters
1.5.Data sources
1.5.1.Primary
1.5.2.Secondary
2.Executive Summary
2.1.360° summary
2.2.By component trends
2.3.By deployment mode trends
2.4.By type trends
2.5.By application trends
2.6.By vertical trends
3.Market overview
3.1.Market segmentation & definitions
3.2.Key takeaways
3.2.1.Top investment pockets
3.2.2.Top winning strategies
3.3.Porter’s five forces analysis
3.3.1.Bargaining power of consumers
3.3.2.Bargaining power of suppliers
3.3.3.Threat of new entrants
3.3.4.Threat of substitutes
3.3.5.Competitive rivalry in the market
3.4.Market dynamics
3.4.1.Drivers
3.4.2.Restraints
3.4.3.Opportunities
3.5.Technology landscape
3.6.Regulatory landscape
3.7.Patent landscape
3.8.Market value chain analysis
3.8.1.Stress point analysis
3.8.2.Raw material analysis
3.8.3.Manufacturing process
3.8.4.Distribution channel analysis
3.8.5.Operating vendors
3.8.5.1.Raw material suppliers
3.8.5.2.Product manufacturers
3.8.5.3.Product distributors
3.9.Strategic overview
4.Natural Language Processing Market, by Component
4.1.Solution
4.1.1.Market size and forecast, by region, 2019-2027
4.1.2.Comparative market share analysis, 2019 & 2027
4.2.Services
4.2.1.Market size and forecast, by region, 2019-2027
4.2.2.Comparative market share analysis, 2019 & 2027
5.Natural Language Processing Market, by Deployment Mode
5.1.On-Premise
5.1.1.Market size and forecast, by region, 2019-2027
5.1.2.Comparative market share analysis, 2019 & 2027
5.2.Cloud
5.2.1.Market size and forecast, by region, 2019-2027
5.2.2.Comparative market share analysis, 2019 & 2027
6.Natural Language Processing Market, by Type
6.1.Rule Based
6.1.1.Market size and forecast, by region, 2019-2027
6.1.2.Comparative market share analysis, 2019 & 2027
6.2.Statistical
6.2.1.Market size and forecast, by region, 2019-2027
6.2.2.Comparative market share analysis, 2019 & 2027
6.3.Hybrid
6.3.1.Market size and forecast, by region, 2019-2027
6.3.2.Comparative market share analysis, 2019 & 2027
7.Natural Language Processing Market, by Application
7.1.Machine Translation
7.1.1.Market size and forecast, by region, 2019-2027
7.1.2.Comparative market share analysis, 2019 & 2027
7.2.Automatic Summarization
7.2.1.Market size and forecast, by region, 2019-2027
7.2.2.Comparative market share analysis, 2019 & 2027
7.3.Sentiment Analysis
7.3.1.Market size and forecast, by region, 2019-2027
7.3.2.Comparative market share analysis, 2019 & 2027
7.4.Text Classification
7.4.1.Market size and forecast, by region, 2019-2027
7.4.2.Comparative market share analysis, 2019 & 2027
7.5.Question Answering
7.5.1.Market size and forecast, by region, 2019-2027
7.5.2.Comparative market share analysis, 2019 & 2027
7.6.Others
7.6.1.Market size and forecast, by region, 2019-2027
7.6.2.Comparative market share analysis, 2019 & 2027
8.Natural Language Processing Market, by Vertical
8.1.Automotive
8.1.1.Market size and forecast, by region, 2019-2027
8.1.2.Comparative market share analysis, 2019 & 2027
8.2.BFSI
8.2.1.Market size and forecast, by region, 2019-2027
8.2.2.Comparative market share analysis, 2019 & 2027
8.3.Government
8.3.1.Market size and forecast, by region, 2019-2027
8.3.2.Comparative market share analysis, 2019 & 2027
8.4.Media and Entertainment
8.4.1.Market size and forecast, by region, 2019-2027
8.4.2.Comparative market share analysis, 2019 & 2027
8.5.Consumer Goods
8.5.1.Market size and forecast, by region, 2019-2027
8.5.2.Comparative market share analysis, 2019 & 2027
8.6.Others
8.6.1.Market size and forecast, by region, 2019-2027
8.6.2.Comparative market share analysis, 2019 & 2027
9.Natural Language Processing Market, by Region
9.1.North America
9.1.1.Market size and forecast, by component, 2019-2027
9.1.2.Market size and forecast, by deployment mode, 2019-2027
9.1.3.Market size and forecast, by type, 2019-2027
9.1.4.Market size and forecast, by application, 2019-2027
9.1.5.Market size and forecast, by vertical, 2019-2027
9.1.6.Market size and forecast, by country, 2019-2027
9.1.7.Comparative market share analysis, 2019 & 2027
9.1.8.U.S.
9.1.8.1.Market size and forecast, by component, 2019-2027
9.1.8.2.Market size and forecast, by deployment mode, 2019-2027
9.1.8.3.Market size and forecast, by type, 2019-2027
9.1.8.4.Market size and forecast, by application, 2019-2027
9.1.8.5.Market size and forecast, by vertical, 2019-2027
9.1.8.6.Comparative market share analysis, 2019 & 2027
9.1.9.Canada
9.1.9.1.Market size and forecast, by component, 2019-2027
9.1.9.2.Market size and forecast, by deployment mode, 2019-2027
9.1.9.3.Market size and forecast, by type, 2019-2027
9.1.9.4.Market size and forecast, by application, 2019-2027
9.1.9.5.Market size and forecast, by vertical, 2019-2027
9.1.9.6.Comparative market share analysis, 2019 & 2027
9.1.10.Mexico
9.1.10.1.Market size and forecast, by component, 2019-2027
9.1.10.2.Market size and forecast, by deployment mode, 2019-2027
9.1.10.3.Market size and forecast, by type, 2019-2027
9.1.10.4.Market size and forecast, by application, 2019-2027
9.1.10.5.Market size and forecast, by vertical, 2019-2027
9.1.10.6.Comparative market share analysis, 2019 & 2027
9.2.Europe
9.2.1.Market size and forecast, by component, 2019-2027
9.2.2.Market size and forecast, by deployment mode, 2019-2027
9.2.3.Market size and forecast, by type, 2019-2027
9.2.4.Market size and forecast, by application, 2019-2027
9.2.5.Market size and forecast, by vertical, 2019-2027
9.2.6.Market size and forecast, by country, 2019-2027
9.2.7.Comparative market share analysis, 2019 & 2027
9.2.8.Germany
9.2.8.1.Market size and forecast, by component, 2019-2027
9.2.8.2.Market size and forecast, by deployment mode, 2019-2027
9.2.8.3.Market size and forecast, by type, 2019-2027
9.2.8.4.Market size and forecast, by application, 2019-2027
9.2.8.5.Market size and forecast, by vertical, 2019-2027
9.2.8.6.Comparative market share analysis, 2019 & 2027
9.2.9.UK
9.2.9.1.Market size and forecast, by component, 2019-2027
9.2.9.2.Market size and forecast, by deployment mode, 2019-2027
9.2.9.3.Market size and forecast, by type, 2019-2027
9.2.9.4.Market size and forecast, by application, 2019-2027
9.2.9.5.Market size and forecast, by vertical, 2019-2027
9.2.9.6.Comparative market share analysis, 2019 & 2027
9.2.10.France
9.2.10.1.Market size and forecast, by component, 2019-2027
9.2.10.2.Market size and forecast, by deployment mode, 2019-2027
9.2.10.3.Market size and forecast, by type, 2019-2027
9.2.10.4.Market size and forecast, by application, 2019-2027
9.2.10.5.Market size and forecast, by vertical, 2019-2027
9.2.10.6.Comparative market share analysis, 2019 & 2027
9.2.11.Spain
9.2.11.1.Market size and forecast, by component, 2019-2027
9.2.11.2.Market size and forecast, by deployment mode, 2019-2027
9.2.11.3.Market size and forecast, by type, 2019-2027
9.2.11.4.Market size and forecast, by application, 2019-2027
9.2.11.5.Market size and forecast, by vertical, 2019-2027
9.2.11.6.Comparative market share analysis, 2019 & 2027
9.2.12.Italy
9.2.12.1.Market size and forecast, by component, 2019-2027
9.2.12.2.Market size and forecast, by deployment mode, 2019-2027
9.2.12.3.Market size and forecast, by type, 2019-2027
9.2.12.4.Market size and forecast, by application, 2019-2027
9.2.12.5.Market size and forecast, by vertical, 2019-2027
9.2.12.6.Comparative market share analysis, 2019 & 2027
9.2.13.Rest of Europe
9.2.13.1.Market size and forecast, by component, 2019-2027
9.2.13.2.Market size and forecast, by deployment mode, 2019-2027
9.2.13.3.Market size and forecast, by type, 2019-2027
9.2.13.4.Market size and forecast, by application, 2019-2027
9.2.13.5.Market size and forecast, by vertical, 2019-2027
9.2.13.6.Comparative market share analysis, 2019 & 2027
9.3.Asia Pacific
9.3.1.Market size and forecast, by component, 2019-2027
9.3.2.Market size and forecast, by deployment mode, 2019-2027
9.3.3.Market size and forecast, by type, 2019-2027
9.3.4.Market size and forecast, by application, 2019-2027
9.3.5.Market size and forecast, by vertical, 2019-2027
9.3.6.Market size and forecast, by country, 2019-2027
9.3.7.Comparative market share analysis, 2019 & 2027
9.3.8.China
9.3.8.1.Market size and forecast, by component, 2019-2027
9.3.8.2.Market size and forecast, by deployment mode, 2019-2027
9.3.8.3.Market size and forecast, by type, 2019-2027
9.3.8.4.Market size and forecast, by application, 2019-2027
9.3.8.5.Market size and forecast, by vertical, 2019-2027
9.3.8.6.Comparative market share analysis, 2019 & 2027
9.3.9.India
9.3.9.1.Market size and forecast, by component, 2019-2027
9.3.9.2.Market size and forecast, by deployment mode, 2019-2027
9.3.9.3.Market size and forecast, by type, 2019-2027
9.3.9.4.Market size and forecast, by application, 2019-2027
9.3.9.5.Market size and forecast, by vertical, 2019-2027
9.3.9.6.Comparative market share analysis, 2019 & 2027
9.3.10.Japan
9.3.10.1.Market size and forecast, by component, 2019-2027
9.3.10.2.Market size and forecast, by deployment mode, 2019-2027
9.3.10.3.Market size and forecast, by type, 2019-2027
9.3.10.4.Market size and forecast, by application, 2019-2027
9.3.10.5.Market size and forecast, by vertical, 2019-2027
9.3.10.6.Comparative market share analysis, 2019 & 2027
9.3.11.Australia
9.3.11.1.Market size and forecast, by component, 2019-2027
9.3.11.2.Market size and forecast, by deployment mode, 2019-2027
9.3.11.3.Market size and forecast, by type, 2019-2027
9.3.11.4.Market size and forecast, by application, 2019-2027
9.3.11.5.Market size and forecast, by vertical, 2019-2027
9.3.11.6.Comparative market share analysis, 2019 & 2027
9.3.12.South Korea
9.3.12.1.Market size and forecast, by component, 2019-2027
9.3.12.2.Market size and forecast, by deployment mode, 2019-2027
9.3.12.3.Market size and forecast, by type, 2019-2027
9.3.12.4.Market size and forecast, by application, 2019-2027
9.3.12.5.Market size and forecast, by vertical, 2019-2027
9.3.12.6.Comparative market share analysis, 2019 & 2027
9.3.13.Rest of Asia Pacific
9.3.13.1.Market size and forecast, by component, 2019-2027
9.3.13.2.Market size and forecast, by deployment mode, 2019-2027
9.3.13.3.Market size and forecast, by type, 2019-2027
9.3.13.4.Market size and forecast, by application, 2019-2027
9.3.13.5.Market size and forecast, by vertical, 2019-2027
9.3.13.6.Comparative market share analysis, 2019 & 2027
9.4.LAMEA
9.4.1.Market size and forecast, by component, 2019-2027
9.4.2.Market size and forecast, by deployment mode, 2019-2027
9.4.3.Market size and forecast, by type, 2019-2027
9.4.4.Market size and forecast, by application, 2019-2027
9.4.5.Market size and forecast, by vertical, 2019-2027
9.4.6.Market size and forecast, by country, 2019-2027
9.4.7.Comparative market share analysis, 2019 & 2027
9.4.8.Latin America
9.4.8.1.Market size and forecast, by component, 2019-2027
9.4.8.2.Market size and forecast, by deployment mode, 2019-2027
9.4.8.3.Market size and forecast, by type, 2019-2027
9.4.8.4.Market size and forecast, by application, 2019-2027
9.4.8.5.Market size and forecast, by vertical, 2019-2027
9.4.8.6.Comparative market share analysis, 2019 & 2027
9.4.9.Middle East
9.4.9.1.Market size and forecast, by component, 2019-2027
9.4.9.2.Market size and forecast, by deployment mode, 2019-2027
9.4.9.3.Market size and forecast, by type, 2019-2027
9.4.9.4.Market size and forecast, by application, 2019-2027
9.4.9.5.Market size and forecast, by vertical, 2019-2027
9.4.9.6.Comparative market share analysis, 2019 & 2027
9.4.10.Africa
9.4.10.1.Market size and forecast, by component, 2019-2027
9.4.10.2.Market size and forecast, by deployment mode, 2019-2027
9.4.10.3.Market size and forecast, by type, 2019-2027
9.4.10.4.Market size and forecast, by application, 2019-2027
9.4.10.5.Market size and forecast, by vertical, 2019-2027
9.4.10.6.Comparative market share analysis, 2019 & 2027
10.Company profiles
10.1.IBM
10.1.1.Business overview
10.1.2.Financial performance
10.1.3.Product portfolio
10.1.4.Recent strategic moves & developments
10.1.5.SWOT analysis
10.2.Microsoft
10.2.1.Business overview
10.2.2.Financial performance
10.2.3.Product portfolio
10.2.4.Recent strategic moves & developments
10.2.5.SWOT analysis
10.3.Google. Inc
10.3.1.Business overview
10.3.2.Financial performance
10.3.3.Product portfolio
10.3.4.Recent strategic moves & developments
10.3.5.SWOT analysis
10.4.Amazon
10.4.1.Business overview
10.4.2.Financial performance
10.4.3.Product portfolio
10.4.4.Recent strategic moves & developments
10.4.5.SWOT analysis
10.5.Facebook
10.5.1.Business overview
10.5.2.Financial performance
10.5.3.Product portfolio
10.5.4.Recent strategic moves & developments
10.5.5.SWOT analysis
10.6.Apple
10.6.1.Business overview
10.6.2.Financial performance
10.6.3.Product portfolio
10.6.4.Recent strategic moves & developments
10.6.5.SWOT analysis
10.7.3M
10.7.1.Business overview
10.7.2.Financial performance
10.7.3.Product portfolio
10.7.4.Recent strategic moves & developments
10.7.5.SWOT analysis
10.8.Intel
10.8.1.Business overview
10.8.2.Financial performance
10.8.3.Product portfolio
10.8.4.Recent strategic moves & developments
10.8.5.SWOT analysis
10.9.Baidu
10.9.1.Business overview
10.9.2.Financial performance
10.9.3.Product portfolio
10.9.4.Recent strategic moves & developments
10.9.5.SWOT analysis
10.10.SAS
10.10.1.Business overview
10.10.2.Financial performance
10.10.3.Product portfolio
10.10.4.Recent strategic moves & developments
10.10.5.SWOT analysis
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