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Text Analytics Market

Pages: 210 | Base Year: 2024 | Release: July 2025 | Author: Versha V.

Market Definition

Text analytics is the process of deriving structured insights from unstructured text using natural language processing, machine learning, and statistical analysis. They allow organizations to identify patterns, extract key information, and interpret sentiments from sources such as customer reviews, emails, social media, and documents. 

Text analytics solutions are widely used in customer experience management, fraud detection, compliance monitoring, and market intelligence. The market also supports applications in healthcare, finance, and e-commerce, where timely insights from textual data improve decision-making, operational efficiency, and strategic planning.

The global text analytics market size was valued at USD 10.38 billion in 2024 and is projected to grow from USD 11.98 billion in 2025 to USD 37.51 billion by 2032, exhibiting a CAGR of 17.71% during the forecast period. 

This growth is attributed to the rising adoption of text analytics solutions across key end-use sectors such as retail, healthcare, BFSI, and telecommunications. Increasing demand for real-time insights, sentiment analysis, and customer experience optimization is driving the deployment of these tools in marketing, compliance monitoring, and risk management applications.

Key Highlights

  1. The text analytics industry size was valued at USD 10.38 billion in 2024.
  2. The market is projected to grow at a CAGR of 17.71% from 2025 to 2032.
  3. North America held a market share of 37.00% in 2024, with a valuation of USD 3.84 billion.
  4. The cloud-based segment garnered USD 6.44 billion in revenue in 2024.
  5. The large enterprises segment is expected to reach USD 23.20 billion by 2032.
  6. The social media monitoring segment is anticipated to witness the fastest CAGR of 22.81% over the forecast period.
  7. The BFSI (Banking, Financial Services & Insurance) segment garnered USD 2.08 billion in revenue in 2024.
  8. Asia Pacific is anticipated to grow at a CAGR of 21.73% during the forecast period.

Major companies operating in the global text analytics market are IBM, Microsoft, SAP SE, Lexalytics (an InMoment Company), Qualtrics, Open Text Corporation, LUMINOSO TECHNOLOGIES, INC., SAS Institute Inc., Infegy, Inc., Medallia Inc., Megaputer Intelligence Inc., Oracle, Cloud Software Group, Inc., Bitext Innovations Inc., and BasisTech.

Text Analytics Market Size & Share, By Revenue, 2025-2032

Text Analytics Market Report Scope

Segmentation

Details

By Deployment Mode

On-Premise, Cloud-Based

By Organization Size

Large Enterprises, Small & Medium Enterprises (SMEs)

By Application

Customer Experience Management, Fraud Detection & Risk Management, Competitive Intelligence, Marketing & Sales Management, Workforce Management, Social Media Monitoring, Predictive Analytics, Content Management, Other Applications

By Industry Vertical

BFSI (Banking, Financial Services & Insurance), Retail & E-commerce, Healthcare & Life Sciences, Government & Defense, IT & Telecom, Media & Entertainment, Education, Manufacturing, Transportation & Logistics, Others

By Region

North America: U.S., Canada, Mexico

Europe: France, UK, Spain, Germany, Italy, Russia, Rest of Europe

Asia-Pacific: China, Japan, India, Australia, ASEAN, South Korea, Rest of Asia-Pacific

Middle East & Africa: Turkey, U.A.E., Saudi Arabia, South Africa, Rest of Middle East & Africa

South America: Brazil, Argentina, Rest of South America

Text Analytics Market Regional Analysis

Based on region, the market has been classified into North America, Europe, Asia Pacific, Middle East & Africa, and South America.

Text Analytics Market Size & Share, By Region, 2025-2032

North America text analytics market share stood at 37.00% in 2024, valued at USD 3.84 billion. This dominance is attributed to the region’s widespread adoption of advanced analytics solutions, the presence of leading text analytics vendors, and high digital transformation across industries such as BFSI, healthcare, and retail.

Furthermore, increasing investment   by enterprises and government agencies in artificial intelligence, cloud infrastructure, and customer intelligence platforms is driving the deployment of text analytics solutions across commercial and public sectors.

  • In July 2023, U.S.-based Accuity Healthcare announced the integration of Microsoft’s Text Analytics technology into its proprietary solution to enhance clinical documentation and coding accuracy. The integration leverages natural language processing to extract key medical concepts, aiming to improve data quality and compliance in healthcare operations.

The region’s emphasis on real-time data analysis, personalized customer engagement, and strict regulatory compliance further reinforces its leadership in the market. Growing demand for predictive analytics, multilingual processing capabilities, and integration with business intelligence tools along with continuous innovation in natural language processing technologies, supports sustained regional market expansion.

The Asia-Pacific text analytics industry is set to grow at a CAGR of 21.73% over the forecast period. This growth is supported by the region’s accelerating digital transformation and increasing reliance on data-driven decision-making across industries. Expanding internet connectivity, rising adoption of cloud platforms, and the proliferation of digital communication channels are creating a strong demand for real-time and scalable text analytics solutions.

Government-backed digitalization efforts, combined with rapid developments in e-commerce, telecom, and financial services, are further advancing the market across Asia-Pacific.

Moreover, the growing need for multilingual processing, automation in customer interaction, and AI integration in enterprise systems is driving adoption across both emerging and developed economies. Additionally, organizations are increasingly implementing advanced text analytics tools to improve operational efficiency, enhance personalization, and meet compliance requirements across the region.

Text Analytics Market Overview

The growing emphasis on data-driven decision-making, operational efficiency, and personalized engagement is fueling market expansion. Additionally, ongoing advancements in artificial intelligence, natural language processing, and cloud-based analytics platforms, along with the surge in unstructured data from digital channels, are accelerating market development.

  • In May 2023, ITHAKA upgraded Constellate, their cloud-based lab platform for teaching text analysis and data skills using tools like JupyterLab. The update includes a streamlined dashboard, snapshot-sharing for lessons, and a quicker setup of personalized workspace environments, making it easier for educators to integrate hands-on NLP and text analytics into curricula.

Market Driver

Surge in Unstructured Data Across Digital Channels

The progress of the text analytics market is propelled by the surge in unstructured data generated across a growing number of digital channels. Organizations are handling massive volumes of text-based inputs from emails, social media platforms, chat transcripts, customer reviews, and web content, which lack a standardized structure.

Traditional data tools fall short in managing and interpreting this information, increasing the demand for text analytics solutions that can deliver contextual understanding and extract meaningful insights.

The need to make informed, real-time decisions is intensifying across industries, prompting greater investment in artificial intelligence and natural language processing technologies. Businesses are turning to text analytics to enhance customer experience, optimize operations, and gain a competitive edge, which continues to drive strong market growth.

Market Challenge

Limited Accuracy in Multilingual and Domain-Specific Applications

Limited accuracy in multilingual and domain-specific applications presents a significant barrier to the widespread adoption of text analytics solutions. Many platforms struggle to interpret industry-specific terminology, technical language, and context-sensitive expressions leading to reduced insight quality in sectors such as healthcare, legal, and finance.

Additionally, language diversity including low-resource languages and regional dialects complicates text processing, often resulting in inconsistent sentiment analysis, entity extraction, and intent recognition across geographies and user bases. These limitations reduce the overall effectiveness of text analytics solutions and restrict their full potential in specialized and multilingual environments. 

Overcoming this challenge requires the use of multilingual NLP models trained on domain-specific datasets to enhance contextual accuracy. Techniques such as transfer learning, language localization, and human-in-the-loop validation are being adopted to improve performance. These advancements enable reliable insights and support wider adoption across specialized sectors and diverse linguistic environments.

  • In January 2023, Lexalytics expanded its natural language processing platform by adding native-language support for 11 new languages, including Arabic, Polish, Thai, and Turkish. The update enhances key functions such as sentiment analysis, entity extraction, and categorization without relying on machine translation, enabling more accurate multilingual text analytics.

Market Trend

Advancements in Artificial Intelligence and Natural Language Processing

Advancements in artificial intelligence and natural language processing are transforming the text analytics market by enabling deeper contextual analysis, faster data processing, and more accurate interpretation of language.

Innovations in deep learning, transformer-based models, and semantic understanding are allowing text analytics platforms to detect sentiment, identify intent, and extract key entities with high precision across diverse text formats. These technologies are enhancing solution capabilities in applications such as customer sentiment analysis, compliance monitoring, and market intelligence.

The integration of machine learning algorithms enables continuous improvement through data-driven learning, while multilingual processing capabilities support global deployment. Additionally, real-time text processing and intelligent automation are improving responsiveness and decision-making across industries.

The development of scalable, cloud-based platforms with advanced NLP features is driving widespread adoption in sectors such as healthcare, finance, retail, and telecommunications. .

Market Segmentation

  • By Deployment Mode (On-Premise and Cloud-Based): The cloud-based segment earned USD 6.44 billion in 2024 due to increasing demand for scalable, cost-effective, and easily deployable text analytics solutions across industries.
  • By Organization Size (Large Enterprises and Small & Medium Enterprises (SMEs)): The large enterprises segment held 68.00% of the market in 2024, attributed to their extensive unstructured data volumes, larger analytics budgets, and demand for enterprise‑grade text analytics capabilities.
  • By Application (Customer Experience Management, Fraud Detection & Risk Management, Competitive Intelligence, Marketing & Sales Management, Workforce Management, Social Media Monitoring, Predictive Analytics, Content Management, and Other Applications): The customer experience management segment is projected to reach USD 7.39 billion by 2032, owing to rising demand for real-time sentiment analysis, personalized engagement, and data-driven strategies to enhance customer satisfaction and retention.
  • By Industry Vertical (BFSI (Banking, Financial Services & Insurance), Retail & E-commerce, Healthcare & Life Sciences, Government & Defense, IT & Telecom, Media & Entertainment, Education, Manufacturing, Transportation & Logistics, and Others): The retail & e-commerce segment is anticipated to grow at a CAGR of 21.53% through the projection period, mainly due to increasing use of text analytics for personalized marketing, customer sentiment tracking, and real-time product feedback analysis.

Regulatory Frameworks

  • In the European Union, the General Data Protection Regulation (GDPR) regulates the collection, processing, and storage of personal data. It ensures that organizations using text analytics tools handle unstructured data such as emails, reviews, and social media content with strict user consent, transparency, and data protection measures.
  • In the U.S. (California), the California Consumer Privacy Act (CCPA) regulates the commercial use of consumer data. It grants individuals rights over their personal information and requires businesses deploying text analytics to disclose data usage, offer opt-outs, and maintain responsible data practices.
  • In India, the Digital Personal Data Protection Act (DPDPA), 2023 regulates the processing of digital personal data. It requires organizations leveraging text analytics tools to obtain clear user consent and implement safeguards to protect user information analyzed from digital text sources.

Competitive Landscape

The text analytics industry is characterized by the presence of several established technology leaders and emerging analytics providers competing based on platform innovation, natural language processing capabilities, and industry-specific solutions. Key market participants are focusing on advancements in artificial intelligence, machine learning models, and multilingual processing to improve analytical accuracy, scalability, and real-time performance.

Companies are also investing in research and development to create adaptive, cloud-based solutions tailored to the specific needs and language of industries such as BFSI, healthcare, retail, and telecommunications.

Furthermore, strategic partnerships with cloud service providers, system integrators, and enterprise software vendors, along with mergers and acquisitions are being pursued to enhance global presence, accelerate product innovation, and expand application reach across compliance monitoring, customer engagement, and competitive intelligence.

Key Companies in Text Analytics Market:

  • IBM
  • Microsoft
  • SAP SE
  • Lexalytics (an InMoment Company)
  • Qualtrics
  • Open Text Corporation
  • LUMINOSO TECHNOLOGIES, INC.
  • SAS Institute Inc.
  • Infegy, Inc.
  • Medallia Inc.
  • Megaputer Intelligence Inc.
  • Oracle
  • Cloud Software Group, Inc.
  • Bitext Innovations Inc.
  • BasisTech

Recent Developments (Launch)

  • In June 2025, InMoment launched its AI-based Conversational Intelligence platform to analyze contact center data using generative AI, NLP, and large language models. The solution enhances sentiment and intent analysis, helping organizations improve first-call resolution, agent performance, and customer satisfaction. One of its key capabilities includes extracting speaker-level insights through AI-driven text analytics, enabling deeper analysis of unstructured conversation data.
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Frequently Asked Questions

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