The text analytics market was valued at US$ 3.23 billion in 2017 and is projected to reach US$ 18.28 billion by 2025. it is expected to grow at a CAGR of 24.2% during the forecast period of 2017 to 2025.

Text analytics is playing an increasingly important role is several use cases and is carries the potential to be incorporated in number of process and application across different industry verticals. Owing to increasing competitiveness, companies are seeking for advanced analytical solutions capable of leveraging large volume of data and assist them in better and faster decision making. With use of sentiment analysis and voice of customer (VoC) solutions companies can improve customer intimacy and service enabling them to drive customer satisfaction, loyalty and revenue.

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Text Analytics Market – Company Profiles

Angoss Software Corporation
Averbis GmbH
Basis Technology
Biomax Informatics AG
Bitext Innovations S.L.
Cambridge Semantics, Inc.
Clarabridge
Clarivate Analytics
Elsevier
Expert System Group
IBM Corporation
KNIME

The deployment type segment is further segmented into In- Premises and Cloud Based text analytics. Based on Technology the market is segmented into Natural Language Processing (NLP), Automate Machine Learning and Hybrid. NLP prepares the text for more advanced analysis and consist of methods identifying text by parts of speech; synonyms, root words & stems, roles identification (subject, object and action) and others. Hybrid on the other hand comprise of analytical software integrated with machine learning and linguistic capabilities.

Range of application and opportunities across diverse fields is driving the growth of the market

Text analytics is creating value across several industrial verticals. Leading players are making continuous improvements in the language processing algorithms to make companies aware of the latest industry trends across different industry verticals. In Europe, leading sports traders are leveraging the benefits of text analytics by analyzing twitter feeds in order to gain deep understanding of the game and sports trends at domestic level. The twitter feeds posted across the region in different languages is used by NLP algorithms and machine learning process which enable the companies to extract the hidden patterns.

On the basis of technology, text analytics can be distinguished into three types: natural language processing, automated machine learning and hybrid. Natural language processing is a scientific discipline that is concerned with making the natural language accessible to machines on the basis of text analytics. Automated machine learning promotes the development of malleable software packages which can be instantiated automatically in a data-driven way..

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