Text Analytics Market Overview

Text analytics is a set of techniques that involve using linguistic, statistical, and machine learning methods to structure and model the information content of textual sources. The information obtained can be used for business intelligence, exploratory data analysis, research, and investigation. The process typically involves managing, interpreting and analyzing unstructured data from text sources such as websites, books, reviews, and articles. The ultimate goal is to turn text into data for analysis, by applying natural language processing techniques, algorithms, and analytical methods. Applications for text analytics are broad and include security monitoring and analysis, customer relationship management, scientific literature mining, and sentiment analysis. Text mining computer programs are available from many commercial and open source companies and sources 1.

By 2030, the Text Analytics Market Forecast projects growth of $9 billion. Moreover, a rise in the CAGR of 17% between 2020 and 2030 is anticipated.

The text analysis method retrieves high-quality information from the already available text sources. This process is also known as data mining used in multiple industries. Text analysis technology is specially used in various fields due to the summarization, classification, and making unstructured data accessible and valuable. The need for the Text Analytics Market Revenue needs is rapidly increasing in multiple industries.

The covid 19 pandemics affected the market growth and lowered the sales rate and market share. It creates multiple issues on the livelihood of people and their businesses. The Covid-19 analysis hampered the sales chain, the global market growth, and lowered market revenue. Major driving factors affect the Text Analytics Market Growth rate, including the increasing rate of effective brand building social media analysis, followed by others like the rapidly increasing big data market. This market is segmented based on different segments.

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Market Segmentation

The Text analytics market can be segmented based on multiple factors based on Component, Application, Deployment, and verticals.

Segmentation By Component:

The Text analytics industry is segmented based on Components, further categorized into Software, Services, Managed Services, and Professional Services.

Segmentation By Application:

The market for text analytics is segmented on Applications that are further categorized into Documentation Management, Workforce Management, Customer Experience Management, Marketing Management, and Risk and Compliance Management.

Segmentation By Deployment:

The Text analytics market is segmented based on Deployment are Cloud and On-premise.

Segmentation By Vertical:

The Text analytics industry is segmented on verticals: BFSI, Retail, E-Commerce, Government, I.T. and others like Telecommunications, Manufacturing, Energy and Utilities, Travel and Hospitality.

Regional Analysis

The regional analysis of the text analytics market is divided into multiple regions: North America, Asia Pacific, Europe, and the Rest of the World. Among all the above-discussed areas, North America has estimated the growth and holds the largest share of the market. After North America, the Asia-Pacific is projected to grow fastest for the upcoming forecast period. The North American region will witness significant growth and compete with the European area. North America is accounted for the competitive market growth due to the increasing population on social media platforms and the increasing development of mobile technology.

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The prominent market players are as follows:

IBM Corporation (U.S.)

MeaningCloud LLC (U.S.)

SAP SE (Germany)

KNIME.com AG (Switzerland)

SAS Institute, Inc. (U.S.)

Luminoso Technologies, Inc. (U.S.)

Clarabridge, Inc. (U.S.)

Industry News

This market has a vast potential in expanding the text analytics industry, especially in the Asia-Pacific region. Most organizations use this to offer actionable insights from the different text sources. The industry's main objective is to accumulate the various forms of structured and unstructured data. It renders help to penetrate the organization, and that's why it has a considerable Text Analytics Industry Demand over the forecast period.

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