Natural Language Processing Market Size, Growth, Demands Outlook and Forecasts to 2030

 According to the research report, the global naturallanguage processing market size is expected to touch USD 361.6 Billion by 2030, from USD 18.6 Billion in 2021, growing with a significant CAGR of 39.06% from 2022 to 2030. 

The natural language processing market report offers a comprehensive study of the current state expected at the major drivers, market strategies, and key vendors’ growth. The report presents energetic visions to conclude and study the market size, market hopes, and competitive surroundings. The research also focuses on the important achievements of the market, research & development, and regional growth of the leading competitors operating in the market. The current trends of the global natural language processing market in conjunction with the geographical landscape of this vertical have also been included in this report.

The report offers intricate dynamics about different aspects of the global natural language processing market, which aids companies operating in the market in making strategic development decisions. The study also elaborates on significant changes that are highly anticipated to configure growth of the global natural language processing market during the forecast period. It also includes a key indicator assessment that highlights growth prospects of this market and estimates statistics related to growth of the market in terms of value (US$ Mn) and volume (tons).

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 Report Scope of the Natural Language Processing Market

Report Coverage	Details
Market Size in 2022	USD 25.86 Billion
Market Size by 2030	USD 361.6 Billion
Growth Rate from 2022 to 2030	CAGR of 39.06%
Base Year	2021
Forecast Period	2022 to 2030
Segments Covered	Technology, Industry Vertical, Enterprise size, Type, Deployment, Component, Application and Geography

This study covers a detailed segmentation of the global natural language processing market, along with key information and a competition outlook. The report mentions company profiles of players that are currently dominating the global natural language processing market, wherein various developments, expansions, and winning strategies practiced and implemented by leading players have been presented in detail.

Key Players

 

• Spark Cognition, Inc
• Conversica
• Linguamatics
• Narrative science
• SAP SE
• Veritone Inc.
• SAS Institute Inc.
• Inbenta
• Intel Corporation
• Google, Inc
• IBM Corporation
• Hewlett Packard Enterprise Development LP
• Microsoft Corporation
• Biadu, Inc
• Amazon Web Services, Inc
• Facebook,Inc
• Apple,Inc
• Bitext
• Health Fidelity
• Linguamatics
• Automated Insights
• Gnani.ai
• Niki
• Mihup
• Observe.Al
• Hyro
• Just Al
• RaGaVeRa

Market Segmentation

 By Technology

• Interactive voice response
• Optical character recognition
• Text analytics
• Speech analytics
• Classification and categorization
• Pattern and image recognition
• Ohers (Coding, Professional services, etc)

By Industry Vertical 

• Manufacturing
• Advertising and media
• Automotive and transportation
• Banking financial services and insurance (BFSI)
• High tech and telecom
• Energy utilities
• Government and public sector
• Education
• Transport and logistics
• Retail and ecommerce
• Healthcare

By Enterprise size

• Small Enterprises
• Medium-sized enterprises
• Large enterprises

By Type

• Rule-based
• Statistical
• Hybrid 

By Deployment

• On premises
• Cloud (Public cloud and private cloud)
• Hybrid

By Component

• Solutions
  • Platform
  • Software tools
• Services
  • Professional Services
    • Consulting
    • System integration and implementation
    • Support and maintenance
  • Managed Services

By Application

• Language scoring
• Content management
• Automatic summarization
• Risk and threat detection
• Data extraction
• Sentiment analysis
• Others (HR and Recruiting branding, advertising, portfolio monitoring)

By Geography

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa (MEA)

Research Methodology

The research methodology adopted by analysts for compiling the global natural language processing market report is based on detailed primary as well as secondary research. With the help of in-depth insights of the market-affiliated information that is obtained and legitimated by market-admissible resources, analysts have offered riveting observations and authentic forecasts for the global market.

During the primary research phase, analysts interviewed market stakeholders, investors, brand managers, vice presidents, and sales and marketing managers. Based on data obtained through interviews of genuine resources, analysts have emphasized the changing scenario of the global market.

For secondary research, analysts scrutinized numerous annual report publications, white papers, market association publications, and company websites to obtain the necessary understanding of the global natural language processing market.

TABLE OF CONTENT

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Natural Language Processing Market 

5.1. COVID-19 Landscape: Natural Language Processing Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Natural Language Processing Market, By Technology

8.1. Natural Language Processing Market, by Technology, 2022-2030

8.1.1. Interactive voice response

8.1.1.1. Market Revenue and Forecast (2017-2030)

8.1.2. Optical character recognition

8.1.2.1. Market Revenue and Forecast (2017-2030)

8.1.3. Text analytics

8.1.3.1. Market Revenue and Forecast (2017-2030)

8.1.4. Speech analytics

8.1.4.1. Market Revenue and Forecast (2017-2030)

8.1.5. Classification and categorization

8.1.5.1. Market Revenue and Forecast (2017-2030)

8.1.5. Pattern and image recognition

8.1.5.1. Market Revenue and Forecast (2017-2030)

8.1.5. Ohers (Coding, Professional services, etc)

8.1.5.1. Market Revenue and Forecast (2017-2030)

Chapter 9. Global Natural Language Processing Market, By Industry Vertical

9.1. Natural Language Processing Market, by Industry Vertical, 2022-2030

9.1.1. Manufacturing

9.1.1.1. Market Revenue and Forecast (2017-2030)

9.1.2. Advertising and media

9.1.2.1. Market Revenue and Forecast (2017-2030)

9.1.3. Automotive and transportation

9.1.3.1. Market Revenue and Forecast (2017-2030)

9.1.4. Banking financial services and insurance (BFSI)

9.1.4.1. Market Revenue and Forecast (2017-2030)

9.1.5. High tech and telecom

9.1.5.1. Market Revenue and Forecast (2017-2030)

9.1.6. Energy utilities

9.1.6.1. Market Revenue and Forecast (2017-2030)

9.1.7. Government and public sector

9.1.7.1. Market Revenue and Forecast (2017-2030)

9.1.8. Education

9.1.8.1. Market Revenue and Forecast (2017-2030)

9.1.9. Transport and logistics

9.1.9.1. Market Revenue and Forecast (2017-2030)

9.1.10. Retail and ecommerce

9.1.10.1. Market Revenue and Forecast (2017-2030)

9.1.11. Healthcare

9.1.11.1. Market Revenue and Forecast (2017-2030)

Chapter 10. Global Natural Language Processing Market, By Enterprise size

10.1. Natural Language Processing Market, by Enterprise size, 2022-2030

10.1.1. Small Enterprises

10.1.1.1. Market Revenue and Forecast (2017-2030)

10.1.2. Medium-sized enterprises

10.1.2.1. Market Revenue and Forecast (2017-2030)

10.1.3. Large enterprises

10.1.3.1. Market Revenue and Forecast (2017-2030)

Chapter 11. Global Natural Language Processing Market, By Type

11.1. Natural Language Processing Market, by Type, 2022-2030

11.1.1. Rule-based

11.1.1.1. Market Revenue and Forecast (2017-2030)

11.1.2. Statistical

11.1.2.1. Market Revenue and Forecast (2017-2030)

11.1.3. Hybrid

11.1.3.1. Market Revenue and Forecast (2017-2030)

Chapter 12. Global Natural Language Processing Market, By Deployment

12.1. Natural Language Processing Market, by Deployment, 2022-2030

12.1.1. On premises

12.1.1.1. Market Revenue and Forecast (2017-2030)

12.1.2. Cloud (Public cloud and private cloud)

12.1.2.1. Market Revenue and Forecast (2017-2030)

12.1.3. Hybrid

12.1.3.1. Market Revenue and Forecast (2017-2030)

Chapter 13. Global Natural Language Processing Market, By Component

13.1. Natural Language Processing Market, by Component, 2022-2030

13.1.1. Solutions

13.1.1.1. Market Revenue and Forecast (2017-2030)

13.1.2. Services

13.1.2.1. Market Revenue and Forecast (2017-2030)

Chapter 14. Global Natural Language Processing Market, Regional Estimates and Trend Forecast

14.1. North America

14.1.1. Market Revenue and Forecast, by Technology (2017-2030)

14.1.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.1.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.1.4. Market Revenue and Forecast, by Type (2017-2030)

14.1.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.1.6. Market Revenue and Forecast, by Component (2017-2030)

14.1.7. U.S.

14.1.7.1. Market Revenue and Forecast, by Technology (2017-2030)

14.1.7.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.1.7.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.1.7.4. Market Revenue and Forecast, by Type (2017-2030)

14.1.8. Market Revenue and Forecast, by Deployment (2017-2030)

14.1.8.1. Market Revenue and Forecast, by Component (2017-2030) 

14.1.9. Rest of North America

14.1.9.1. Market Revenue and Forecast, by Technology (2017-2030)

14.1.9.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.1.9.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.1.9.4. Market Revenue and Forecast, by Type (2017-2030)

14.1.10. Market Revenue and Forecast, by Deployment (2017-2030)

14.1.11. Market Revenue and Forecast, by Component (2017-2030)

14.1.11.1.

14.2. Europe

14.2.1. Market Revenue and Forecast, by Technology (2017-2030)

14.2.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.2.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.2.4. Market Revenue and Forecast, by Type (2017-2030) 

14.2.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.2.6. Market Revenue and Forecast, by Component (2017-2030)

14.2.7.

14.2.8. UK

14.2.8.1. Market Revenue and Forecast, by Technology (2017-2030)

14.2.8.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.2.8.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.2.9. Market Revenue and Forecast, by Type (2017-2030) 

14.2.10. Market Revenue and Forecast, by Deployment (2017-2030)

14.2.10.1. Market Revenue and Forecast, by Component (2017-2030) 

14.2.11. Germany

14.2.11.1. Market Revenue and Forecast, by Technology (2017-2030)

14.2.11.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.2.11.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.2.12. Market Revenue and Forecast, by Type (2017-2030)

14.2.13. Market Revenue and Forecast, by Deployment (2017-2030)

14.2.14. Market Revenue and Forecast, by Component (2017-2030)

14.2.14.1.

14.2.15. France

14.2.15.1. Market Revenue and Forecast, by Technology (2017-2030)

14.2.15.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.2.15.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.2.15.4. Market Revenue and Forecast, by Type (2017-2030)

14.2.16. Market Revenue and Forecast, by Deployment (2017-2030)

14.2.16.1. Market Revenue and Forecast, by Component (2017-2030)

14.2.17. Rest of Europe

14.2.17.1. Market Revenue and Forecast, by Technology (2017-2030)

14.2.17.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.2.17.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.2.17.4. Market Revenue and Forecast, by Type (2017-2030)

14.2.18. Market Revenue and Forecast, by Deployment (2017-2030)

14.2.18.1. Market Revenue and Forecast, by Component (2017-2030)

14.3. APAC

14.3.1. Market Revenue and Forecast, by Technology (2017-2030)

14.3.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.3.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.3.4. Market Revenue and Forecast, by Type (2017-2030)

14.3.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.3.6. Market Revenue and Forecast, by Component (2017-2030)

14.3.7. India

14.3.7.1. Market Revenue and Forecast, by Technology (2017-2030)

14.3.7.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.3.7.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.3.7.4. Market Revenue and Forecast, by Type (2017-2030)

14.3.8. Market Revenue and Forecast, by Deployment (2017-2030)

14.3.9. Market Revenue and Forecast, by Component (2017-2030)

14.3.10. China

14.3.10.1. Market Revenue and Forecast, by Technology (2017-2030)

14.3.10.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.3.10.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.3.10.4. Market Revenue and Forecast, by Type (2017-2030)

14.3.11. Market Revenue and Forecast, by Deployment (2017-2030)

14.3.11.1. Market Revenue and Forecast, by Component (2017-2030)

14.3.12. Japan

14.3.12.1. Market Revenue and Forecast, by Technology (2017-2030)

14.3.12.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.3.12.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.3.12.4. Market Revenue and Forecast, by Type (2017-2030)

14.3.12.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.3.12.6. Market Revenue and Forecast, by Component (2017-2030)

14.3.13. Rest of APAC

14.3.13.1. Market Revenue and Forecast, by Technology (2017-2030)

14.3.13.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.3.13.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.3.13.4. Market Revenue and Forecast, by Type (2017-2030)

14.3.13.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.3.13.6. Market Revenue and Forecast, by Component (2017-2030)

14.4. MEA

14.4.1. Market Revenue and Forecast, by Technology (2017-2030)

14.4.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.4.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.4.4. Market Revenue and Forecast, by Type (2017-2030)

14.4.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.4.6. Market Revenue and Forecast, by Component (2017-2030)

14.4.7. GCC

14.4.7.1. Market Revenue and Forecast, by Technology (2017-2030)

14.4.7.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.4.7.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.4.7.4. Market Revenue and Forecast, by Type (2017-2030)

14.4.8. Market Revenue and Forecast, by Deployment (2017-2030)

14.4.9. Market Revenue and Forecast, by Component (2017-2030)

14.4.10. North Africa

14.4.10.1. Market Revenue and Forecast, by Technology (2017-2030)

14.4.10.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.4.10.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.4.10.4. Market Revenue and Forecast, by Type (2017-2030)

14.4.11. Market Revenue and Forecast, by Deployment (2017-2030)

14.4.12. Market Revenue and Forecast, by Component (2017-2030)

14.4.13. South Africa

14.4.13.1. Market Revenue and Forecast, by Technology (2017-2030)

14.4.13.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.4.13.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.4.13.4. Market Revenue and Forecast, by Type (2017-2030)

14.4.13.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.4.13.6. Market Revenue and Forecast, by Component (2017-2030)

14.4.14. Rest of MEA

14.4.14.1. Market Revenue and Forecast, by Technology (2017-2030)

14.4.14.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.4.14.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.4.14.4. Market Revenue and Forecast, by Type (2017-2030)

14.4.14.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.4.14.6. Market Revenue and Forecast, by Component (2017-2030)

14.5. Latin America

14.5.1. Market Revenue and Forecast, by Technology (2017-2030)

14.5.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.5.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.5.4. Market Revenue and Forecast, by Type (2017-2030)

14.5.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.5.6. Market Revenue and Forecast, by Component (2017-2030)

14.5.7. Brazil

14.5.7.1. Market Revenue and Forecast, by Technology (2017-2030)

14.5.7.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.5.7.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.5.7.4. Market Revenue and Forecast, by Type (2017-2030)

14.5.8. Market Revenue and Forecast, by Deployment (2017-2030)

14.5.8.1. Market Revenue and Forecast, by Component (2017-2030)

14.5.9. Rest of LATAM

14.5.9.1. Market Revenue and Forecast, by Technology (2017-2030)

14.5.9.2. Market Revenue and Forecast, by Industry Vertical (2017-2030)

14.5.9.3. Market Revenue and Forecast, by Enterprise size (2017-2030)

14.5.9.4. Market Revenue and Forecast, by Type (2017-2030)

14.5.9.5. Market Revenue and Forecast, by Deployment (2017-2030)

14.5.9.6. Market Revenue and Forecast, by Component (2017-2030)

Chapter 15. Company Profiles

15.1. Spark Cognition, Inc

15.1.1. Company Overview

15.1.2. Product Offerings

15.1.3. Financial Performance

15.1.4. Recent Initiatives

15.2. Conversica

15.2.1. Company Overview

15.2.2. Product Offerings

15.2.3. Financial Performance

15.2.4. Recent Initiatives

15.3. Linguamatics

15.3.1. Company Overview

15.3.2. Product Offerings

15.3.3. Financial Performance

15.3.4. Recent Initiatives

15.4. Narrative science

15.4.1. Company Overview

15.4.2. Product Offerings

15.4.3. Financial Performance

15.4.4. Recent Initiatives

15.5. SAP SE

15.5.1. Company Overview

15.5.2. Product Offerings

15.5.3. Financial Performance

15.5.4. Recent Initiatives

15.6. Veritone Inc.

15.6.1. Company Overview

15.6.2. Product Offerings

15.6.3. Financial Performance

15.6.4. Recent Initiatives

15.7. Veritone Inc.

15.7.1. Company Overview

15.7.2. Product Offerings

15.7.3. Financial Performance

15.7.4. Recent Initiatives

15.8. Inbenta

15.8.1. Company Overview

15.8.2. Product Offerings

15.8.3. Financial Performance

15.8.4. Recent Initiatives

15.9. Intel Corporation

15.9.1. Company Overview

15.9.2. Product Offerings

15.9.3. Financial Performance

15.9.4. Recent Initiatives

15.10. Google, Inc

15.10.1. Company Overview

15.10.2. Product Offerings

15.10.3. Financial Performance

15.10.4. Recent Initiatives

Chapter 16. Research Methodology

16.1. Primary Research

16.2. Secondary Research

16.3. Assumptions

Chapter 17. Appendix

17.1. About Us

17.2. Glossary of Terms

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