According to a new report published by Introspective Market Research, titled, “Text Analytics Market by Component, Deployment Mode, and End User, The Global Text Analytics Market Size Was Valued at USD 15.55 Billion in 2023 and is Projected to Reach USD 70.03 Billion by 2032, Growing at a CAGR of 18.20%.” The Text Analytics Market is gaining strong momentum worldwide, owing to the rising volume of unstructured textual data generated from digital platforms, customer interactions, and enterprise communications. Text analytics leverages artificial intelligence, natural language processing (NLP), and machine learning to extract meaningful insights from raw text data. These insights are critical for improving decision-making, understanding customer sentiment, and optimizing business strategies across industries such as BFSI, retail, healthcare, and IT.
Unlike traditional data management techniques, text analytics can efficiently interpret vast quantities of qualitative data—from emails and social media to research reports and customer feedback. Its ability to uncover hidden trends, detect fraud, and enhance marketing campaigns is transforming how organizations engage with stakeholders. The growing adoption of cloud computing, automation tools, and advanced analytics solutions continues to accelerate the global expansion of this market.
The Text Analytics Market is segmented into Component, Deployment Mode, and End User.
By Component, the market is categorized into (Software, Services, and Solutions).
By Deployment Mode, the market is categorized into (On-Premise and Cloud-Based).
By End User, the market is categorized into (BFSI, Healthcare, Retail & E-commerce, Government, IT & Telecom, and Others).
A major growth driver for the Text Analytics Market is the rising dependence on customer experience management and social media monitoring. As organizations collect growing volumes of unstructured content, there is an increasing need to analyze and understand customer sentiments, preferences, and feedback. Text analytics tools allow companies to perform automated sentiment analysis and trend detection, helping them enhance brand reputation, reduce churn rates, and achieve higher operational efficiency in a data-intensive environment.
A prominent market opportunity lies in the rapid integration of text analytics with generative AI and large language models (LLMs). These technologies enhance contextual understanding, improve predictive accuracy, and enable human-like text processing in multiple languages. Enterprises are exploring advanced AI-driven analytics for business intelligence, risk mitigation, and compliance monitoring. The continued expansion of cloud infrastructure and AI-as-a-Service platforms provides a scalable foundation for deploying next-generation, multi-domain text analytics solutions globally.
Text Analytics Market, Segmentation
The Text Analytics Market is segmented on the basis of Component, Deployment Mode, and End User.
Component
The Component segment is further classified into Software, Services, and Solutions. Among these, the Software sub-segment accounted for the highest market share in 2023. Software solutions form the backbone of text analytics operations, facilitating sentiment analysis, content categorization, and semantic search. Continuous advancements in NLP algorithms and automation frameworks have enhanced the capability of text analytics software to process real-time data more accurately, driving its widespread enterprise adoption.
Deployment Mode
The Deployment Mode segment is further classified into On-Premise and Cloud-Based. Among these, the Cloud-Based sub-segment accounted for the highest market share in 2023. Cloud deployment is preferred due to its scalability, cost efficiency, and ease of integration with existing enterprise analytics ecosystems. With the rise of hybrid work models and global data access demands, cloud-based text analytics platforms enable real-time insights, ensuring rapid implementation without heavy infrastructure investments.
Some of The Leading/Active Market Players Are–
- IBM Corporation (U.S.)
- SAS Institute Inc. (U.S.)
- Microsoft Corporation (U.S.)
- Google LLC (U.S.)
- Oracle Corporation (U.S.)
- SAP SE (Germany)
- Amazon Web Services, Inc. (U.S.)
- Lexalytics, Inc. (U.S.)
- MeaningCloud LLC (Spain)
- Aylien Ltd. (Ireland)
- InMoment, Inc. (U.S.)
- Verint Systems Inc. (U.S.)
- Basis Technology Corporation (U.S.)
- Clarabridge, Inc. (U.S.)
- OpenText Corporation (Canada)
- and other active players.
Key Industry Developments
In March 2024, Microsoft expanded its Azure AI Text Analytics platform with multilingual sentiment analysis and real-time entity recognition capabilities.
This enhancement improves support for global enterprises managing multilingual content, enabling sophisticated emotion recognition and context-based interpretation across more than 25 languages.
In July 2024, IBM Watson introduced advanced generative NLP modules within its Watson Discovery platform to enhance automated knowledge extraction.
These new features leverage transformer-based models to improve text summarization, topic modeling, and semantic similarity analysis for large-scale enterprise datasets.
Key Findings of the Study
- Software dominated the component segment in 2023.
- Cloud-based deployment held the largest market share.
- North America led the global market in revenue contribution.
- Growth driven by rising demand for real-time sentiment analysis.
- AI and generative NLP integration is redefining analytics capabilities.
