Text Mining Market 2024 - Outlook, Overview And Competitor Analysis 2033

The text mining market size has grown exponentially in recent years. It will grow from $5.86 billion in 2023 to $7.05 billion in 2024 at a compound annual growth rate (CAGR) of 20.3%. The growth in the historic period can be attributed to the growing demand for data-driven decision-making across industries, the development of more sophisticated machine learning algorithms, the integration of text mining with customer relationship management (CRM) systems, regulatory requirements, the emergence of sentiment analysis, and adoption of text mining for fraud detection and risk management.

The text mining market size is expected to see exponential growth in the next few years. It will grow to $14.82 billion in 2028 at a compound annual growth rate (CAGR) of 20.4%. The growth in the forecast period can be attributed to increasing demand for efficient data extraction and analysis from unstructured text sources, expansion of industries, integration of text mining with other data analytics tools for comprehensive insights, increasing focus on customer experience management and personalization, growing awareness among enterprises, growth of big data analytics. Major trends in the forecast period include text classification, topic modeling, contextual understanding, multilingual text mining, and advancements in deep learning.

Market Overview -
Text mining refers to the process of extracting meaningful information and insights from unstructured text data. It involves techniques such as natural language processing (NLP), machine learning, and statistical analysis to uncover patterns, trends, and relationships within large volumes of textual information, enabling tasks like sentiment analysis, document categorization, and information retrieval.

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Digitization Trends Fuels Growth In The Text Mining Market Expansion
 The growing trend of digitization is expected to propel the growth of the text mining market going forward. Digitization refers to converting analog information into digital format, typically involving data representation as binary numbers for storage and processing on computers or other digital devices. The growing digitization trend is fueled by its ability to streamline processes, enhance connectivity, and enable efficient access to information in various sectors. Digitization facilitates efficient text mining by converting analog data into machine-readable formats, enabling advanced analysis and extracting valuable insights from textual content. For instance, in November 2023, according to the Central Digital and Data Office, a U.K.-based government body, between April 2022 and April 2023, the government's digital and data profession experienced a notable expansion of 19%, effectively meeting crucial demands for digital expertise. Therefore, the growing trend of digitization is driving the growth of the text mining market.

Competitive Landscape -
Major companies operating in the text mining market are Microsoft Corporation, International Business Machines Corporation, SAP SE, Capgemini SE, SAS Institute, Confirmit, Basis Technology, Kingland Systems LLC, KNIME, Altair Engineering Inc., RapidMiner, Bitext, Mozenda, InMoment, Semantic Web Company GmbH, Wonderflow, PrediCX, NextWealth Entrepreneurs Private Limited, Angoss Software Corporation, Averbis GmbH, Netowl Inc., MeaningCloud, DeepOpinion, Funnel Science, SmatSocial

Enhancing Text Mining Capabilities By Advanced Natural Language Processing
Major companies operating in the text mining market are focusing on developing advanced solutions, such as advanced natural language processing, to gain a competitive edge in the market. This advanced natural language processing is useful to text mining because it enhances text mining capabilities by enabling more accurate, efficient, and nuanced analysis of textual data. For instance, in May 2023, ONTOFORCE NV, a Belgium-based data science company, launched advanced Natural Language Processing (NLP) capabilities to unlock valuable insights from unstructured data sources in life sciences. This initiative aligns with the increasing importance of NLP in the industry, where up to 80% of data is stored in unstructured formats, making it challenging to access and analyze.

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Key Segments -

The text mining market covered in this report is segmented -

1) By Product: On-premise, Cloud-based
2) 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
3) By End-Use: Healthcare, Retail, Banking, Financial Services And Insurance (BFSI), Government, Media And Entertainment, Other End Users

Key highlights covered in the report -
1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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