Text Analytics Market Synopsis

Text Analytics Market Size Was Valued at USD 7.69 Billion in 2023, and is Projected to Reach USD 154.25 Billion by 2032, Growing at a CAGR of 39.54% From 2024-2032.

Text Analytics, also known as Text Mining, is a sector of Natural Language Processing (NLP) that concentrates on obtaining valuable information from unstructured text data in order to make business decisions.

• Text Analytics is a beneficial tool for organizations to extract valuable insights from unstructured data sources like social media, reviews, and feedback forms. Organizations can enhance customer experience and build loyalty by examining this data to gain insight into customers' needs and preferences.
• The competitive edge enables companies to remain ahead of rivals by making informed choices using market trends and customer feedback. Text Analytics also allows companies to gauge customer feelings, pinpoint reasons for grievances, and enhance operational efficiency by automating the analysis procedure.
• Text Analytics assists organizations in making data-driven decisions that support business growth, enhance product development, and increase employee engagement through actionable insights. Furthermore, Text Analytics can aid in discovering fresh business prospects, managing crisis scenarios, and enhancing supply chain effectiveness.
• Text Analytics could revolutionize the way businesses function by offering immediate insights, cutting expenses, and enabling proactive risk management and compliance actions.

Top Active Players Involved Are:

Clarabridge, Inc. (US), IBM (US), Luminoso Technologies, Inc. (US), Megaputer Intelligence, Inc. (US), Microsoft Corporation (US), Micro Focus LLC (US), Open Text Corporation (Canada), Oracle Corporation (US), SAP SE (Germany), SAS Institute (US), Lexalytics (US), Tableau (US) (acquired by Salesforce), MeaningCloud (Spain), NetBase Solutions (US), Ravenpack (US), Rosette (US), LexisNexis (US), Attensity (US), Brandwatch (UK), Crimson Hexagon (US), Talkwalker (Luxembourg), Sprout Social (US), Hootsuite (Canada), Lexicon Analytics (US), Infegy (US), and Other Active Players.

Text Analytics Market Trend Analysis

Adoption for Fraud Detection

• Due to the quick expansion of digital transactions, there has been a rise in fraudulent activities, causing organizations to suffer substantial financial losses. As per a report from the Association of Certified Fraud Examiners (ACFE), on average, 5% of a company's revenue is lost to fraud annually.
• Conventional methods like rule-based systems are now ineffective in identifying complex fraud schemes. Organizations require sophisticated analytical skills to detect and stop fraudulent behaviors.
• Text Analytics, a branch of Natural Language Processing (NLP), is being more widely utilized for detecting fraud. Text Analytics can detect potentially fraudulent activity by examining extensive unstructured data, like emails, chat logs, and social media posts for patterns and anomalies.
• Text Analytics, a subset of Natural Language Processing (NLP), is increasingly being used for fraud detection.

Source: Company Database

• The fraud detection and prevention (FDP) market was worth 19.5 billion U.S. dollars in 2018. The market in 2023 exceeded 63.5 billion U.S. dollars. Firms offer FDP methods to prevent fraudulent insurance claims, identity theft, and money laundering.

Rising Concerns About Data Privacy

• Regulations such as GDPR and CCPA place strict restrictions on data access, storage, and processing, which limits organizations' ability to collect sufficient data for text analytics. Masking data for privacy can decrease the precision of text analytics models, resulting in decreased adoption rates.
• Adhering to regulations takes away resources from text analytics projects, causing delays in their progress. Concerns about privacy decrease customer trust, making it challenging to gather enough data for effective text analysis.
• Organizations are reluctant to embrace text analytics due to cybersecurity threats, as they are afraid of potential data breaches. Addressing ethical issues like bias in AI and discriminatory results is necessary, leading to further obstacles in adoption.
• Organizations may find text analytics solutions less appealing as compliance costs rise. Privacy regulations limit the global reach of text analytics projects by restricting international data sharing.

Rising Adoption of the Internet of Things

• The growing need for text analytics is a result of the surging volume of unstructured data produced by IoT devices, including logs, sensor readings, and user engagements.
• The information can offer important thoughts on device efficiency, user actions, and environmental situations. IoT devices present fresh potential for text analysis, such as predictive maintenance, real-time monitoring, and improving customer experience.
• Text analytics can be combined with AI and ML algorithms to examine the large amount of data produced by IoT devices and create innovative business models such as device-as-a-service. Analyzing text data near the data source is important for efficient analysis in IoT settings.

Text Analytics Market Segment Analysis:

Text Analytics market is segmented on the basis of Component, Deployment, Application, Enterprise Size, and End-user.

By Enterprise Size, Large Enterprises Segment Is Expected to Dominate the Market During the Forecast Period

There are two segments by enterprise size such as large enterprises, and small & medium enterprises. Among these, the large enterprises segment is expected to dominate the market during the forecast period.

• Large businesses are quick to embrace text analytics tools, spending a lot of money to take advantage of better understanding of customers, more efficient operations, and better decision-making. Their intricate business activities produce large quantities of disorganized data from sources such as customer reviews, social media, and IoT devices.
• Text analytics assists in interpreting this data and guides business decisions. Large companies benefit more from text analytics due to their size, which helps improve various aspects of their business like customer satisfaction, product development, marketing efforts, and finding new sources of revenue.
• Text analytics is needed to analyze massive amounts of data, recognize trends, and forecast patterns, requiring advanced analytical skills. In order to comply with regulations such as GDPR and HIPAA, sensitive data is categorized by text analytics to protect data privacy. Big corporations use their IT systems to seamlessly incorporate text analysis solutions and increase the size of their operations. Analyzing large amounts of unstructured data through text analytics provides a competitive edge, enhancing market positioning and increasing revenue share compared to rivals.

By End-user, Retail & E-Commerce Segment Held the Largest Share In 2023

There are four segments by end-user such as BFSI, healthcare, energy & utility, retail & e-commerce. Among these, the retail & e-commerce segment held the largest share in 2023.

• The retail and e-commerce sector collects a wide range of customer feedback through product reviews, social media, email, surveys, and chat interactions. Retailers utilize text analytics to examine this feedback and understand customer preferences and behaviours.
• In a competitive market, companies need to focus on retaining customers by using text analytics to evaluate sentiment and feedback. Text analytics can enhance personalization and recommendation tactics to provide tailored offers using customer information.
• Moreover, the use of text analytics in supply chain operations involves analysing social media data, customer complaints, and reviews to improve pricing, inventory management, and product development.
• The text analytics has the potential to assist retailers in reducing expenses, improving productivity, and identifying opportunities for operational improvement.

Text Analytics Market Regional Insights:

North America is Expected to Dominate the Market Over the Forecast Period

• Text Analytics adoption is most prominent in North America, particularly in the United States, because of the large presence of tech companies, research institutions, and government agencies.
• The area is home to many Fortune 500 firms that produce significant amounts of unstructured data, leading to a need for Text Analytics. Investments in artificial intelligence and analytics have fostered a robust network of new companies and top industry firms.
• Government initiatives such as NIST's Text Analytics Program aid in the expansion of the market. Sectors such as healthcare, finance, and retail depend greatly on Text Analytics. An adept labour force and a conducive business setting also contribute to the increase and advancement in the area.

Text Analytics Market Active Players

• Clarabridge, Inc. (US)
• IBM (US)
• Luminoso Technologies, Inc. (US)
• Megaputer Intelligence, Inc. (US)
• Microsoft Corporation (US)
• Micro Focus LLC (US)
• Open Text Corporation (Canada)
• Oracle Corporation (US)
• SAP SE (Germany)
• SAS Institute (US)
• Lexalytics (US)
• Tableau (US) (acquired by Salesforce)
• MeaningCloud (Spain)
• NetBase Solutions (US)
• Ravenpack (US)
• Rosette (US)
• LexisNexis (US)
• Attensity (US)
• Brandwatch (UK)
• Crimson Hexagon (US)
• Talkwalker (Luxembourg)
• Sprout Social (US)
• Hootsuite (Canada)
• Lexicon Analytics (US)
• Infegy (US), and Other Active Players.

Key Industry Developments in the Text Analytics Market:

• In May 2024, IBM announced the evolution and expansion of Qiskit, its widely used quantum software. Qiskit, was initially launched in 2017. The latest version of Qiskit has been enhanced to provide better performance, evolving into a comprehensive software stack. This expansion equips IBM Quantum Network members with powerful capabilities to explore and develop quantum algorithms.
• In April 2024, Microsoft hosted a business application launch event to showcase the latest AI features in Dynamics 365 and Microsoft Power Platform. Attendees explored how AI advancements and Microsoft Copilot can improve team collaboration, streamline processes, and adapt to evolving business demands.