Text Analytics Market Size & Share 2021 to 2027
Market Size by Component (Software [Customer Intelligence, Customer Relationship Management (CRM), Fraud Detection, Governance, Risk & Compliance (GRC) Management], Service [Professional Service, Managed Services]), by Deployment Model (On-premise, Cloud), by End Use (BFSI, Retail, Government, Healthcare & Lifesciences, IT & Telecom, Travel & Hospitality, Media & Entertainment), Industry Analysis Report, Regional Outlook, Growth Potential, & Forecast.Download Free PDF
Report Content
Chapter 1 Methodology & Scope
1.1 Scope & defintions
1.2 Methodology & forecast parameters
1.3 Region-wise COVID-19 impact anaysis
1.3.1 North America
1.3.2 Europe
1.3.3 Asia Pacific
1.3.4 Latin America
1.3.5 Middle East & Africa
1.4 Data Sources
1.4.1 Secondary
1.4.2 Primary
Chapter 2 Executive Summary
2.1 Text analytics industry 360º synopsis, 2016 – 2027
2.2 Business trends
2.3 Regional trends
2.4 component trends
2.5 deployment model trends
2.6 Application trends
Chapter 3 Text analytics Industry Insights
3.1 Introduction
3.2 Industry segmentation
3.3 Impact of COVID-19 outbreak
3.3.1 Global outlook
3.3.2 By region
3.3.2.1 North America
3.3.2.2 Europe
3.3.2.3 Asia Pacific
3.3.2.4 Latin America
3.3.2.5 Middle East & Africa
3.3.3 Industry value chain
3.3.3.1 Suppliers
3.3.3.2 Text analytics technology providers
3.3.3.3 Marketing & distribution channels
3.3.4 Competitive landscape
3.3.4.1 Strategy
3.3.4.2 Distribution network
3.3.4.3 Business growth
3.4 Evolution of text analytics
3.5 Text analytics industry architecture
3.6 Text analytics industry ecosystem analysis
3.6.1 Text analytics providers
3.6.2 Cloud service providers
3.6.3 Third party service providers
3.6.4 Marketing and distribution channel
3.6.5 Vendor matrix
3.7 Technology & innovation landscape
3.7.1 Network virtualization
3.7.2 Big data analytics
3.7.3 Artificial Intelligence
3.7.4 Natural Language Processing (NLP)
3.8 Regulatory landscape
3.8.1 North America
3.8.1.1 Standards on Privacy and Web Analytics (Canada)
3.8.1.2 Health Insurance Portability and Accountability Act (HIPAA) of 1996 (U
3.8.2 Europe
3.8.2.1 General Data Protection Regulation (GDPR)
3.8.2.2 Exception of Text & Data Mining (TDM) in Copyright in Digital Single Market (DSM Draft Directive - EU)
3.8.3 APAC
3.8.3.1 Information Security Technology- Personal Information Security Specification GB/T 35273-2017 (China)
3.8.3.2 Secure India National Digital Communications Policy 2018-Draft 66 (India)
3.8.4 LATAM
3.8.4.1 The General Data Protection Law (Brazil)
3.8.4.2 Personal Data Protection Act 25 326 (PDPA – Argentina)
3.8.5 MEA
3.8.5.1 Federal Law No 2 of 2019 on the use of ICT in Healthcare (UAE)
3.8.5.2 Privacy Protection Regulations (Data Security), 5777-2017 (Israel)
3.9 Industry impact forces
3.9.1 Growth drivers
3.9.1.1 Growing demand for social media analytics
3.9.1.2 Increasing use of business intelligence tools
3.9.1.3 Proliferation of cloud computing technology
3.9.1.4 Growing demand for sentiment analysiss
3.9.2 Industry pitfalls & challenges
3.9.2.1 Lack of awareness
3.9.2.2 High cost of software
3.10 Growth potential analysis
3.11 Porter’s analysis
3.12 PESTEL analysis
Chapter 4 Competitive Landscape
4.1 Introduction
4.2 Market share analysis, 2020
4.3 Competive analysis of key market players, 2020
4.3.1 Amazon Web Service, Inc. (AWS)
4.3.2 IBM Corporation
4.3.3 Micro Focus LLC
4.3.4 Microsoft Corporation
4.3.5 SAP SE
4.4 Competive analysis of innovative market players, 2020
4.4.1 Khoros LLC
4.4.2 Medallia, Inc.
4.4.3 Opentext Corporation
4.4.4 SAS Institute
4.4.5 Verint Systems, Inc.
Chapter 5 Text Analytics Market, By component
5.1 Key trends, by component
5.2 Software
5.2.1 Market estimates and forecast, 2016 – 2027
5.2.2 Customer intelligence
5.2.2.1 Market estimates and forecast, 2016 – 2027
5.2.3 Customer Relationship Management (CRM)
5.2.3.1 Market estimates and forecast, 2016 – 2027
5.2.4 Governance, Risk, and Compliance (GRC) management
5.2.4.1 Market estimates and forecast, 2016 – 2027
5.2.5 Fraud detection
5.2.5.1 Market estimates and forecast, 2016 – 2027
5.2.6 Others
5.2.6.1 Market estimates and forecast, 2016 – 2027
5.3 Service
5.3.1 Market estimates and forecast, 2016 – 2027
5.3.2 Professional services
5.3.2.1 Market estimates and forecast, 2016 – 2027
5.3.3 Managed services
5.3.3.1 Market estimates and forecast, 2016 – 2027
Chapter 6 Text Analytics Market, By deployment model
6.1 Key trends, by deployment model
6.2 Cloud
6.2.1 Market estimates and forecast, 2016 – 2027
6.3 On-premise
6.3.1 Market estimates and forecast, 2016 – 2027
Chapter 7 Text Analytics Market, By Application
7.1 Key trends, by application
7.2 BFSI
7.2.1 Market estimates and forecast, 2016 – 2027
7.3 Retail
7.3.1 Market estimates and forecast, 2016 – 2027
7.4 Government
7.4.1 Market estimates and forecast, 2016 – 2027
7.5 Healthcare
7.5.1 Market estimates and forecast, 2016 – 2027
7.6 Media & advertising
7.6.1 Market estimates and forecast, 2016 – 2027
7.7 IT & telecom
7.7.1 Market estimates and forecast, 2016 – 2027
7.8 Travel & hospitality
7.8.1 Market estimates and forecast, 2016 – 2027
7.9 Others
7.9.1 Market estimates and forecast, 2016 – 2027
Chapter 8 Text Analytics Market, By Region
8.1 Key trends, by region
8.2 North America
8.2.1 Market estimates and forecast, 2016 – 2027
8.2.2 Market estimates and forecast, by component, 2016 – 2027
8.2.2.1 Market estimates and forecast, by software, 2016 – 2027
8.2.2.2 Market estimates and forecast, by service, 2016 – 2027
8.2.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.2.4 Market estimates and forecast, by application, 2016 – 2027
8.2.5 U.S.
8.2.5.1 Market estimates and forecast, 2016 – 2027
8.2.5.2 Market estimates and forecast, by component, 2016 – 2027
8.2.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.2.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.2.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.2.5.4 Market estimates and forecast, by application, 2016 – 2027
8.2.6 Canada
8.2.6.1 Market estimates and forecast, 2016 – 2027
8.2.6.2 Market estimates and forecast, by component, 2016 – 2027
8.2.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.2.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.2.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.2.6.4 Market estimates and forecast, by application, 2016 – 2027
8.3 Europe
8.3.1 Market estimates and forecast, 2016 – 2027
8.3.2 Market estimates and forecast, by component, 2016 – 2027
8.3.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.4 Market estimates and forecast, by application, 2016 – 2027
8.3.5 UK
8.3.5.1 Market estimates and forecast, 2016 – 2027
8.3.5.2 Market estimates and forecast, by component, 2016 – 2027
8.3.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.5.4 Market estimates and forecast, by application, 2016 – 2027
8.3.6 Germany
8.3.6.1 Market estimates and forecast, 2016 – 2027
8.3.6.2 Market estimates and forecast, by component, 2016 – 2027
8.3.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.6.4 Market estimates and forecast, by application, 2016 – 2027
8.3.7 France
8.3.7.1 Market estimates and forecast, 2016 – 2027
8.3.7.2 Market estimates and forecast, by component, 2016 – 2027
8.3.7.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.7.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.7.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.7.4 Market estimates and forecast, by application, 2016 – 2027
8.3.8 Italy
8.3.8.1 Market estimates and forecast, 2016 – 2027
8.3.8.2 Market estimates and forecast, by component, 2016 – 2027
8.3.8.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.8.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.8.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.8.4 Market estimates and forecast, by application, 2016 – 2027
8.3.9 Spain
8.3.9.1 Market estimates and forecast, 2016 – 2027
8.3.9.2 Market estimates and forecast, by component, 2016 – 2027
8.3.9.2.1 Market estimates and forecast, by software, 2016 – 2027
8.3.9.2.2 Market estimates and forecast, by service, 2016 – 2027
8.3.9.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.3.9.4 Market estimates and forecast, by application, 2016 – 2027
8.4 Asia Pacific
8.4.1 Market estimates and forecast, 2016 – 2027
8.4.2 Market estimates and forecast, by component, 2016 – 2027
8.4.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.4 Market estimates and forecast, by application, 2016 – 2027
8.4.5 China
8.4.5.1 Market estimates and forecast, 2016 – 2027
8.4.5.2 Market estimates and forecast, by component, 2016 – 2027
8.4.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.5.4 Market estimates and forecast, by application, 2016 – 2027
8.4.6 India
8.4.6.1 Market estimates and forecast, 2016 – 2027
8.4.6.2 Market estimates and forecast, by component, 2016 – 2027
8.4.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.6.4 Market estimates and forecast, by application, 2016 – 2027
8.4.7 Japan
8.4.7.1 Market estimates and forecast, 2016 – 2027
8.4.7.2 Market estimates and forecast, by component, 2016 – 2027
8.4.7.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.7.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.7.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.7.4 Market estimates and forecast, by application, 2016 – 2027
8.4.8 South Korea
8.4.8.1 Market estimates and forecast, 2016 – 2027
8.4.8.2 Market estimates and forecast, by component, 2016 – 2027
8.4.8.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.8.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.8.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.8.4 Market estimates and forecast, by application, 2016 – 2027
8.4.9 Australia
8.4.9.1 Market estimates and forecast, 2016 – 2027
8.4.9.2 Market estimates and forecast, by component, 2016 – 2027
8.4.9.2.1 Market estimates and forecast, by software, 2016 – 2027
8.4.9.2.2 Market estimates and forecast, by service, 2016 – 2027
8.4.9.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.4.9.4 Market estimates and forecast, by application, 2016 – 2027
8.5 Latin America
8.5.1 Market estimates and forecast, 2016 – 2027
8.5.2 Market estimates and forecast, by component, 2016 – 2027
8.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.5.4 Market estimates and forecast, by application, 2016 – 2027
8.5.5 Brazil
8.5.5.1 Market estimates and forecast, 2016 – 2027
8.5.5.2 Market estimates and forecast, by component, 2016 – 2027
8.5.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.5.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.5.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.5.5.4 Market estimates and forecast, by application, 2016 – 2027
8.5.6 Mexico
8.5.6.1 Market estimates and forecast, 2016 – 2027
8.5.6.2 Market estimates and forecast, by component, 2016 – 2027
8.5.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.5.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.5.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.5.6.4 Market estimates and forecast, by application, 2016 – 2027
8.6 MEA
8.6.1 Market estimates and forecast, 2016 – 2027
8.6.2 Market estimates and forecast, by component, 2016 – 2027
8.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.6.4 Market estimates and forecast, by application, 2016 – 2027
8.6.5 South Africa
8.6.5.1 Market estimates and forecast, 2016 – 2027
8.6.5.2 Market estimates and forecast, by component, 2016 – 2027
8.6.5.2.1 Market estimates and forecast, by software, 2016 – 2027
8.6.5.2.2 Market estimates and forecast, by service, 2016 – 2027
8.6.5.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.6.5.4 Market estimates and forecast, by application, 2016 – 2027
8.6.6 GCC
8.6.6.1 Market estimates and forecast, 2016 – 2027
8.6.6.2 Market estimates and forecast, by component, 2016 – 2027
8.6.6.2.1 Market estimates and forecast, by software, 2016 – 2027
8.6.6.2.2 Market estimates and forecast, by service, 2016 – 2027
8.6.6.3 Market estimates and forecast, by deployment model, 2016 – 2027
8.6.6.4 Market estimates and forecast, by application, 2016 – 2027
Chapter 9 Company Profiles
9.1 Amazon Web Services, Inc. (AWS)
9.1.1 Business Overview
9.1.2 Financial Data
9.1.3 Product Landscape
9.1.4 Strategic Outlook
9.1.5 SWOT Analysis
9.2 Angoss Software Corporation (Altair Engineering, Inc.)
9.2.1 Business Overview
9.2.2 Financial Data
9.2.3 Product Landscape
9.2.4 Strategic Outlook
9.2.5 SWOT Analysis
9.3 Basis Technology Corporation
9.3.1 Business Overview
9.3.2 Financial Data
9.3.3 Product Landscape
9.3.4 Strategic Outlook
9.3.5 SWOT Analysis
9.4 Bitext Innovations, S.L.
9.4.1 Business Overview
9.4.2 Financial Data
9.4.3 Product Landscape
9.4.4 Strategic Outlook
9.4.5 SWOT Analysis
9.5 Brandwatch
9.5.1 Business Overview
9.5.2 Financial Data
9.5.3 Product Landscape
9.5.4 Strategic Outlook
9.5.5 SWOT Analysis
9.6 Clarabridge, Inc.
9.6.1 Business Overview
9.6.2 Financial Data
9.6.3 Product Landscape
9.6.4 Strategic Outlook
9.6.5 SWOT Analysis
9.7 IBM Corporation
9.7.1 Business Overview
9.7.2 Financial Data
9.7.3 Product Landscape
9.7.4 Strategic Outlook
9.7.5 SWOT Analysis
9.8 Interactions LLC
9.8.1 Business Overview
9.8.2 Financial Data
9.8.3 Product Landscape
9.8.4 Strategic Outlook
9.8.5 SWOT Analysis
9.9 Jive software (Aurea Software, Inc.)
9.9.1 Business Overview
9.9.2 Financial Data
9.9.3 Product Landscape
9.9.4 Strategic Outlook
9.9.5 SWOT Analysis
9.10 Khoros, LLC
9.10.1 Business Overview
9.10.2 Financial Data
9.10.3 Product Landscape
9.10.4 Strategic Outlook
9.10.5 SWOT Analysis
9.11 Lexalytics, Inc.
9.11.1 Business Overview
9.11.2 Financial Data
9.11.3 Product Landscape
9.11.4 Strategic Outlook
9.11.5 SWOT Analysis
9.12 Luminoso Technologies, Inc.
9.12.1 Business Overview
9.12.2 Financial Data
9.12.3 Product Landscape
9.12.4 Strategic Outlook
9.12.5 SWOT Analysis
9.13 Medallia, Inc.
9.13.1 Business Overview
9.13.2 Financial Data
9.13.3 Product Landscape
9.13.4 Strategic Outlook
9.13.5 SWOT Analysis
9.14 Megaputer Intelligence, Inc.
9.14.1 Business Overview
9.14.2 Financial Data
9.14.3 Product Landscape
9.14.4 Strategic Outlook
9.14.5 SWOT Analysis
9.15 Micro Focus LLC
9.15.1 Business Overview
9.15.2 Financial Data
9.15.3 Product Landscape
9.15.4 Strategic Outlook
9.15.5 SWOT Analysis
9.16 Microsoft Corporation
9.16.1 Business Overview
9.16.2 Financial Data
9.16.3 Product Landscape
9.16.4 Strategic Outlook
9.16.5 SWOT Analysis
9.17 NetBase Solutions, Inc.
9.17.1 Business Overview
9.17.2 Financial Data
9.17.3 Product Landscape
9.17.4 Strategic Outlook
9.17.5 SWOT Analysis
9.18 OpenText Corporation
9.18.1 Business Overview
9.18.2 Financial Data
9.18.3 Product Landscape
9.18.4 Strategic Outlook
9.18.5 SWOT Analysis
9.19 RapidMiner, Inc.
9.19.1 Business Overview
9.19.2 Financial Data
9.19.3 Product Landscape
9.19.4 Strategic Outlook
9.19.5 SWOT Analysis
9.20 SAP SE
9.20.1 Business Overview
9.20.2 Financial Data
9.20.3 Product Landscape
9.20.4 Strategic Outlook
9.20.5 SWOT Analysis
9.21 SAS Institute, Inc.
9.21.1 Business Overview
9.21.2 Financial Data
9.21.3 Product Landscape
9.21.4 Strategic Outlook
9.21.5 SWOT Analysis
9.22 Unmetric, Inc.
9.22.1 Business Overview
9.22.2 Financial Data
9.22.3 Product Landscape
9.22.4 Strategic Outlook
9.22.5 SWOT Analysis
9.23 Verint Systems, Inc
9.23.1 Business Overview
9.23.2 Financial Data
9.23.3 Product Landscape
9.23.4 Strategic Outlook
9.23.5 SWOT Analysis
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Base Year: 2020
Companies Profiled: 23
Tables and Figures: 338
Countries covered: 16
Pages: 250
Download Free PDF
Base Year: 2020
Companies Profiled: 23
Tables and Figures: 338
Countries covered: 16
Pages: 250
Download Free PDF
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Preeti Wadhwani. 2021, March. Text Analytics Market Size By Component (Software [Customer Intelligence, Customer Relationship Management (CRM), Fraud Detection, Governance, Risk & Compliance (GRC) Management], Service [Professional Service, Managed Services]), By Deployment Model (On-premise, Cloud), By End-use (BFSI, Retail, Government, Healthcare & Lifesciences, IT & Telecom, Travel & Hospitality, Media & Entertainment), Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2021 – 2027 (Report ID: GMI2215). Global Market Insights Inc. Retrieved August 1, 2026, from https://www.gminsights.com/toc/details/text-analytics-market
Text Analytics Market
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Text Analytics Market Size
Text Analytics Market size exceeded USD 6 billion in 2020 and is poised to register gains at around 20% CAGR between 2021 and 2027. Increasing popularity of social media analytics for gaining crucial business insights is likely to fuel the industry growth. Social media analytics enables organizations to gain better understanding of customer preferences and offer customized ads to expand market presence across a diverse clientele. Text analytics has become a key enabler for marketing agencies to track the digital footprints of customers such as browsing behavior, keyword search, and liked pages.
The text analytics industry has received a strong impetus amid the ongoing COVID-19 pandemic. Market acceleration in the text analytics space has been substantial as R&D focus has shifted to a global analysis of textual data. Text analytics has been rapidly deployed to detect patterns from which conclusions can be drawn for quick decision-making. For instance, SAS Institute aims to analyze over 50,000 full text documents on COVID-19 to provide healthcare researchers with future action plans.
The increasing traction of enterprises toward sentiment analysis has emerged as the major driving force behind text analytics market demand. With the proliferation of online reviews, blogs, ratings, and recommendations, businesses are pressurized to ensure that their services receive good ratings for maintaining market competitiveness. Text analytics assists such enterprises in understanding customer sentiments and improving their services for enhanced customer satisfaction.
Text Analytics Market Analysis
In Italy, the customer intelligence segment generated over USD 5.15 million revenue in 2020. Digital channels have emerged as the first point of interaction between enterprises and target customers. The analysis of consumer sentiments on these platforms is becoming a crucial part of customer intelligence. Text mining and analytics enable enterprises to process and analyze large volumes of customer-related textual data to derive valuable business information.
For instance, Epipoli, a major gift card vendor in Italy, deployed customer intelligence solutions from SAS for improving customer conversion rates. The company used text mining to build detailed customer profiles of its potential customers, increasing customer conversion rates by 23%.
The cloud segment in Japan accounted for more than USD 74.75 million in 2020. The growing adoption of cloud technology by enterprises for improving business capabilities will expand the market for cloud-based text analytics software. Enterprises deploying text analytics software on the cloud can increase computing resources during peak loads and reduce them during idle hours, paying only for the exact amount of computing resources being used.
Enterprises offering cloud-based solutions are boosting market competitiveness through add-on services such as speech-to-text API and optical character recognition API in real time, complementing the results obtained from text analytics.
In Canada text analytics market, the retail segment is set to attain a market share of above 30% by 2027. The increasing adoption of text mining solutions in the regional retail industry is driven by the growing need to cut costs and target customers more efficiently. The optimization of promotions, identification of right marketing strategies, and the maximization of sales through discounts can be effectively carried out by leveraging the customer behavioral data.
As per the July 2020 press release by Walmart Canada, the retailer announced its plans to infuse USD 3.5 billion into its Canadian stores as the pandemic continues to trigger increased e-commerce and physical retail. With plans to renovate 150 more stores in the near future with new checkout experience to reduce touchpoints, text analytics will be at the fore.
Asia Pacific is expected to register significant growth in the text analytics market with a nearly 25% CAGR through 2027. The regional industry is characterized by increasing demand for text analytics solutions in the BFSI sector to improve customer experience and reduce the risks associated with frauds. Text analytics is becoming a viable solution for the detection of fraudulent claims in the regional insurance industry. Fake personal details, wrong transaction dates, and incorrect addresses can be extracted and evaluated by text mining algorithms, which has strongly propelled the market expansion.
Text Analytics Market Share
The global text analytics market remains highly consolidated with technology giants, such as IBM, SAP, and SAS, dominating the market share. Prominent players are placing an ever-growing emphasis on delivering advanced solutions that can cater to the changing dynamics of consumer sentiments, especially during the pandemic. For instance, in July 2020, Microsoft included text mining capabilities within its Azure Cognitive Services product. The text analytics for health feature can process various data types and tasks including extracting more than 100 types of personally identifiable information from unstructured texts.
Another major development included the release of COVID-19 search tool by SAS Institute in March 2020, which can extract text and numerical data from more than 50,000 research articles and allow users quick access to relevant information. The market has also witnessed several strategic alliances between key players to launch new products with added functionalities and to maintain revenue share & profitability, such as the June 2019 acquisition of Cooldata by Medallia to propel its big data handling capabilities.
Some of the key players operating in the text analytics market are:
This market research report on text analytics includes in-depth coverage of the industry with estimates & forecast in terms of revenue in USD from 2016 to 2027 for the following segments:
Market, By Component
Market, By Deployment Model
Market, By Application
The above information has been provided for the following regions and countries: