Text Mining Global Market Report 2026

Text mining refers to the systematic process of extracting valuable insights and information from unstructured text data. This involves utilizing techniques such as natural language processing (NLP), machine learning, and statistical analysis to uncover patterns, trends, and relationships within extensive textual datasets. Key tasks facilitated by text mining include sentiment analysis, document categorization, and information retrieval.

The primary product types in text mining are on-premise and cloud-based solutions. On-premise text mining software is installed and operated on the organization's internal computers or servers, rather than being hosted on a remote facility or cloud service. These applications find application across various domains including data analysis and forecasting, fraud and spam detection, intelligence and law enforcement, customer relationship management (CRM), NLP-driven text mining, and sentiment analysis. End-users of text mining software span diverse sectors such as healthcare, retail, banking, financial services and insurance (BFSI), government, media and entertainment, among others.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

Tariffs on software and data services have influenced the text mining market by increasing costs of cloud-based deployments and advanced analytics tools, particularly affecting regions such as north america, europe, and asia-pacific. Segments like cloud-based solutions and large-scale enterprise applications are most impacted, but tariffs have also encouraged local deployment strategies, customization, and development of more cost-effective on-premise text mining solutions.

The text mining market research report is one of a series of new reports from The Business Research Company that provides text mining market statistics, including text mining industry global market size, regional shares, competitors with a text mining market share, detailed text mining market segments, market trends and opportunities, and any further data you may need to thrive in the text mining industry. This text mining market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The text mining market size has grown exponentially in recent years. It will grow from $8.47 billion in 2025 to $10.19 billion in 2026 at a compound annual growth rate (CAGR) of 20.3%. The growth in the historic period can be attributed to growing need for data-driven decision making, adoption of nlp technologies in enterprises, increasing volumes of unstructured data, early use in healthcare and bfsi sectors, initial deployment of on-premise text mining solutions.

The text mining market size is expected to see rapid growth in the next few years. It will grow to $19.16 billion in 2030 at a compound annual growth rate (CAGR) of 17.1%. The growth in the forecast period can be attributed to expansion of cloud-based text mining solutions, adoption in media and entertainment, integration with ai and ml platforms, increasing use in government and intelligence sectors, rising demand for real-time and scalable text mining capabilities. Major trends in the forecast period include integration with crm systems, enhanced sentiment analysis capabilities, advanced fraud and spam detection, real-time data analysis and forecasting, improved data security and privacy controls.

The upward trajectory of digitization is poised to be a significant driver propelling the growth of the text mining market in the foreseeable future. Digitization, characterized by the conversion of analog information into digital format, serves as a cornerstone for streamlining processes, enhancing connectivity, and facilitating efficient access to information across various sectors. The growing digitization trend plays a pivotal role in enabling efficient text mining endeavors by transforming analog data into machine-readable formats, thereby empowering advanced analysis and extraction of valuable insights from textual content. For instance, insights from the Central Digital and Data Office in November 2023 highlight a notable 19% expansion within the government's digital and data profession between April 2022 and April 2023, effectively meeting crucial demands for digital expertise. This underscores the pivotal role of digitization in propelling the growth trajectory of the text mining market.

Key players within the text mining market landscape are strategically focused on developing advanced solutions, notably advanced natural language processing (NLP), to gain a competitive edge in the market. Advanced NLP holds significant utility in text mining endeavors as it enhances text mining capabilities by enabling more accurate, efficient, and nuanced analysis of textual data. For instance, ONTOFORCE NV, a leading data science company based in Belgium, launched advanced Natural Language Processing (NLP) capabilities in May 2023 to unlock valuable insights from unstructured data sources in life sciences. This strategic initiative aligns with the increasing significance of NLP within the industry, where up to 80% of data is stored in unstructured formats, posing challenges for access and analysis. By leveraging advanced NLP capabilities, organizations can extract meaningful insights from unstructured textual data, thereby enhancing decision-making processes and driving innovation across diverse domains.

In January 2025, S&P Global Inc., a U.S.-based provider of market intelligence and analytics solutions, acquired ProntoNLP Inc. for an undisclosed amount. Through this acquisition, S&P Global aims to strengthen its text mining and natural language processing (NLP) capabilities by integrating ProntoNLP's generative AI-powered tools for analyzing unstructured textual data, including event detection and sentiment scoring. ProntoNLP Inc. is a U.S.-based company that provides natural language processing and AI solutions to extract insights from large volumes of unstructured text.

Major companies operating in the text mining market report are Microsoft Corporation, International Business Machines Corporation, SAP SE, SAS Institute, Confirmit, Basis Technology, KNIME, RapidMiner, Bitext, InMoment, Semantic Web Company GmbH, Wonderflow, Averbis GmbH, MeaningCloud, DeepOpinion, Oracle Corporation, Google LLC Natural Language API, Amazon Web Services Comprehend, Lexalytics Inc., Clarabridge Inc., Amenity Analytics, MonkeyLearn, TextRazor, Provalis Research, Aylien Ltd.

North America was the largest region in the text mining market in 2025. Asia Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the text mining market are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the text mining market are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The text mining market includes revenues earned by entities by providing services such as named entity recognition (NER), topic modeling, entity recognition, document summarization, and sentiment analysis. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Text Mining Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses text mining market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for text mining ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The text mining market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
• The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
• The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
• The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
• The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
• The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
• Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

• Markets Covered:1) By Component: Software; Services
• 2) By Deployment: On-Premise; Cloud-Based
• 3) By Application: Data Analysis And Forecasting; Fraud Or Spam Detection; Intelligence And Law Enforcement; Customer Relationship Management (CRM); Text Mining For Natural Language Processing (NLP); Text Mining For Sentiment Analysis
• 4) By End-Use: Healthcare; Retail; Banking, Financial Services And Insurance (BFSI); Government; Media And Entertainment; Other End Users
• Subsegments:
• 1) By Software: Natural Language Processing (NLP) Software; Sentiment Analysis Software; Entity Recognition Software; Text Classification And Clustering Software; Topic Modeling Software
• 2) By Services: Implementation And Integration Services; Data Preparation And Annotation Services; Custom Model Development Services; Training And Support Services; Consulting And Advisory Services
• Companies Mentioned: Microsoft Corporation; International Business Machines Corporation; SAP SE; SAS Institute; Confirmit; Basis Technology; KNIME; RapidMiner; Bitext; InMoment; Semantic Web Company GmbH; Wonderflow; Averbis GmbH; MeaningCloud; DeepOpinion; Oracle Corporation; Google LLC Natural Language API; Amazon Web Services Comprehend; Lexalytics Inc.; Clarabridge Inc.; Amenity Analytics; MonkeyLearn; TextRazor; Provalis Research; Aylien Ltd.
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
• Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time Series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
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