Market Players in Natural Language Processing (NLP) Market are IBM, SAS, Nuance Communications, Microsoft, 3M, M*Modal, Fuji Xerox and NetBase.
(PRWEB) August 08, 2014
The report, "Natural Language Processing (NLP) Market [IVR, OCR, Pattern Recognition, Auto Coding, Text Analytics, Speech Analytics, Machine Translation, Information Extraction, Question Answer, Report Generation] - Worldwide Market Forecast and Analysis (2013 - 2018)," defines and segments the global Natural Language Processing (NLP) market into various sub-segments with in-depth analysis and forecast of revenues. It also identifies drivers, opportunities, and restraints for this market, with insights into industry trends and their impacts over time.
Browse 105 Market Data Tables and 37 Figures spread through 199 Pages and In-Depth Table of Content on “Natural Language Processing (NLP) Market:”
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The Natural Language Processing (NLP) market is estimated to grow $9,858.4 million in 2018. This represents a Compounded Annual Growth Rate (CAGR) of 21.1% 2018. In terms of regional growth, North America is expected to be the biggest market in terms of revenue contribution. European and APAC region is expected to experience increased market traction due to increasing adoption across various verticals and investment support in research projects from the regional government.
MarketsandMarkets has segmented the NLP market by type: rule-based NLP, statistical NLP, hybrid NLP; by type of technologies- recognition technologies: Interactive Voice Response (IVR), Optical Character Recognition (OCR), and pattern and image recognition, operational technologies: auto coding and classification and categorization, analytics technologies: text analytics and speech analytics; by type of services: installation and maintenance, training and certification, consulting services and other services; by type of application: machine translation, information extraction, report generation, question answering, and other applications; by type of end user- Consumer NLP and Enterprise NLP: it includes BFSI, Automotive, healthcare, IT and Communication, legal and commercial offices, government defense and aerospace, media and advertisement, academia and education, web and e-commerce and other verticals; by deployment type: on-premise NLP and on-demand NLP; by regions: North America (NA), Asia Pacific (APAC), Europe, Middle East Africa (MEA) and Latin America (LA).
MarketsandMarkets observes that there is an increasing demand of NLP technology in web and e-commerce, healthcare, IT, and telecommunication industry for enhancing customer experience and operational processes by integrated NLP software solutions. Hence, even though the adoption of the NLP technology and is majorly seen in the healthcare vertical, we expect that these software solutions will continue to show steady growth in other verticals as well.
The major forces driving this market are the growing demand for enhanced customer experience, increase in adoption of smartphone, leveraging big data and growth in machine to machine (M2M) technologies. Furthermore, industries such as healthcare, BFSI, social websites, and e-commerce channels have witnessed exponential rise in real time customer data and transaction information. NLP technology can leverage this unstructured data for analyzing customer needs, expectations and enhancing customer experience by optimizing cost effective lingual response system in organizational processes. By using NLP software solutions, organization can have better insights on customer’s perception, optimize business processes, and reduce operational cost.
While the NLP market is growing at a steady pace across various verticals, MarketsandMarkets observes some of the major vendors such as Nuance Communications, M*Modal, IBM and many other companies who are continuously innovating their NLP software solutions which can be easily integrated into enterprise platforms. Further, MarketsandMarkets expects that on-demand NLP software solutions are expected to have continuous growth and adoption rate in the long term, thereby creating customizable stack services and applications facilitating quicker customer adoption of the same.
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