“Natural Language Market Analysis, Growth Opportunities and Recent Trends by Leading Manufacturers & Regions”
From $8.3 billion in 2018, the revenue generated from the sale of such solutions is predicted to increase to $22.9 billion by 2024, at a CAGR of 19.7% during 2019–2024 (forecast period).
The major reasons behind the growth of the natural language processing (NLP) market are the rising focus on an enhanced consumer experience, rapid business process automation, creation of high volumes of data, and rise in the number of contact centers. From $8.3 billion in 2018, the revenue generated from the sale of such solutions is predicted to increase to $22.9 billion by 2024, at a CAGR of 19.7% during 2019–2024 (forecast period). A subfield of artificial intelligence, NLP helps machines and computers understand the language of humans.
Based on type, the market for natural language processing is categorized into hybrid, rule-based, and statistical. Among these, the statistical category held the largest share in 2018, as this technology utilizes machine learning algorithms to analyze data, rather than requiring human effort. This is rather important in today’s times, when two quintillion bytes of data is being created daily. Via traditional tools, structured data in the form of spreadsheets and databases is easy to process, but not the unstructured data sourced from videos and images, social media, and documents and blogs.
By leveraging automatic translation, speech processing, natural language generation (NLG), and sentiment analysis, NLP helps prioritize the extracted information, thereby helping organizations in making the best use of structured as well as unstructured data. Therefore, the growing volume of data, especially in the unstructured form, is driving the natural language processing market, by creating the need for a technology which can help companies in effectively processing and studying it, in order to derive actionable insights.
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Information extraction, machine translation, question answering, text processing, and report generation are the various divisions under the application segment. Among these, the machine translation division dominated the natural language processing market in 2018, as organizations generate a heavy demand for solutions that can translate a given text into numerous languages. This is itself a result of the rising adoption of chatbots for enhancing the experience of customers, to build brand loyalty and increase revenue.
Among the various virtual assistants employed by business in recent years, chatbots have been one of the most popular, as they help companies handle customers’ concerns quickly and efficiently. Further, chatbots which work on NLP are able to process various languages, which helps in the smoothening of processes, particularly those related to customer support. These chatbots establish the primary contact between the business and customers, sorting out as much of the latter’s concerns as possible, before handing over the case to human employees.
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The need to enhance customer experience is one of the major drivers for the natural language processing market progress. Customers communicate with organizations via chat messages, e-mails, social media platforms, and phone calls, thereby making it difficult to process all the data. NLP helps here by studying the feedback, while saving time and reducing human involvement and errors. With the technology, companies are able to analyze consumers’ preference for the different services and products on offer as well as understand how their decisions are impacted by the cultural and technological scenario.
Across the world, North America was the largest natural language processing market in 2018, owing to the increasing need for better customer experience, rising volume of data, and heavy investments in research and development (R&D) in the field of AI. During the forecast period, Asia-Pacific would observe the highest market CAGR, as a result of the technological enhancements in Japan, India, and China, adoption of cloud computing, and escalating number of contact centers and small and medium enterprises.
Therefore, as an increasing volume of data is created in the unstructured form, the demand for tools to efficiently analyze it will also grow.
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