Text Analytics Market Overview by Top Players Segments Demand and Forecast till 2028

The "Text Analytics Market" is expected to grow from US$ 8.45 billion in 2022 to US$ 27.63 billion by 2028; it is estimated to record a CAGR of 20.4% from 2022 to 2028.

Text analytics plays an increasingly important role in several use cases across different industry verticals. For example, the insurance industry has different and distinct use cases such as claims automation, policy review, and risk engineering that require text analysis. Text analytics allows insurance companies to locate specific information within minimal time. Digital advertising is another end use of text analytics. Unlike a cookie-based approach, contextual advertising analyzes text on a webpage to understand content in an in-depth manner. Widening number of industries using text analytics would drive the overall text analytics market growth.

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Companies Profiled in this report includes:

• IBM Corporation
• SAP SE
• SAS Institute Inc.
• Clarabridge
• Expert Systems
• OpenText Corp.
• Basis Technology
• Linguamatics
• ANGOSS SOFTWARE CORPORATION
• KNIME

Owing to increasing competitiveness, companies are seeking advanced analytical solutions capable of utilizing large volumes of data, thereby aiding in better and faster decision-making. With the use of sentiment analysis and voice-of-customer (VoC) solutions, companies can improve customer intimacy and service quality, which enables them to drive customer satisfaction, loyalty, and revenue. The use of text analytics solutions in risk management and fraud detection application in the banking and financial sector helps save millions of dollars over a deal. This will further contribute towards the growth of text analytics market.

Text categorization is one of the prominent use cases of text analytics. The process is based on machine learning and models taken from current datasets, further matching the model data sets with new datasets for making predictions. In text categorization, the end user's system is fed with a pre-built set of text examples and their relevant categories. A machine learning algorithm learns how each text is categorized and creates rules for itself. When new text is presented, it applies these rules to categorize it. This supervised learning-based approach to text categorization saves the time and effort required to set and implement new rules. Growing demand for text categorization will help in fueling the text analytics market growth.

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Text Analytics Market Segmentation:

By Deployment Type:
• Cloud-Based
• On-Premise

By Technology:
• NLP, AML
• Hybrid

By Application:
• Predictive Analysis
• Competitive Intelligence
• Fraud/Spam Detection
• Social Media Monitoring

By Vertical:
• BFSI
• Telecom
• FMCG
• Government
• Academia
• Education
• Legal & Intellectual Property
• Healthcare
• Pharmaceuticals
• Chemistry & Materials
• Retail

Regional Analysis of Text Analytics Market:

APAC ranked third in terms of text analytics market share in 2022. Continuous growth in the retail, banking, fast-moving consumer goods (FMCG), and healthcare sectors in emerging markets of the Philippines, China, India, and Australia have attracted several international enterprises targeting these economies for the expansion of their business. With the expansion of business into the mentioned countries, their day-to-day functions would create enormous amounts of unstructured text through. This factor is projected to develop growth opportunities for vendors operating in APAC and thus impacting text analytics market. Also, the proliferation of the healthcare sector in Australia, Japan, Taiwan, South Korea, China, Singapore, etc., is anticipated to generate significant demand for text analytics platforms owing to the generation of huge amount of unstructured textual data. ~80% of biomedical data created is unstructured text, which requires text analytics solutions to unlock insights with the use of natural language processing-based solutions.
Owing to continuous technological advancements, it is projected that the advent of different AI regulations in the US, Europe, and Asia will promote the adoption of AI solutions in Asia Pacific by 2025. This adoption will further triggering the machine learning and automated machine learning platform penetration. The use of machine learning platforms would lead to new data categories, thereby expanding the scope of text categorization.

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This release was published on openPR.