Text Analytics Market Statistics, 2030
The global text analytics market size was valued at $5.86 billion in 2020, and is projected to reach $29.42 billion by 2030, growing at a CAGR of 17.8 % from 2021 to 2030.
Surge in need for social media analytics and predictive analytics for businesses is boosting the growth of the global text analytics market. In addition, rise in highly customized and industry-specific applications is positively impacting the growth of the market. However, lack of awareness regarding text analytics, skilled workforce, and other operational challenges and data privacy and security concerns hamper the market growth. On the contrary, enhanced customer service and competitive intelligence are expected to offer remunerative opportunities for expansion of the market during the forecast period.
Text analytics is the process of transforming unstructured text into a structured data which helps in identifying meaningful patterns and new insights. It works by breaking sentences and phrases into their components and then evaluating each component using complex software rules and machine learning algorithms. Furthermore, this involves text mining, which is the process of pulling text from a source into a data analysis model, and natural language processing (NLP), which is the machine learning method of processing written language into data.
In terms of component, the software segment holds the largest share of the text analytics market. This is attributed to the fact that developers are adopting text analytics software solutions that utilize text mining algorithms and natural language processing (NLP) technology to find meaning in huge amounts of unstructured textual data. However, the services segment is expected to grow at the highest rate during the forecast period, owing to rise in demand for advanced technologies, natural language processing, and visual data mining, which are developed text analytics algorithms techniques. Text analytics is further used in sentiment analysis, machine translation, bioinformatics and others.
Region wise, the text analytics market was dominated by North America in 2020, and is expected to retain its position during the forecast period. This is attributed to the growing adoption of text analytics solutions across end-user industries, such as BFSI, retail, and healthcare. However, Asia-Pacific is expected to witness significant growth during the forecast period, owing to increase in 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 feasible solution for the detection of fraudulent claims in the regional insurance industry, which is expected to drive the text analytics market in Asia-Pacific.
The report focuses on growth prospects, restraints, and trends of the global text analytics market analysis. The study provides Porter’s five forces analysis to understand impact of various factors, such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers, on the global text analytics market share.
Segment Review
The global text analytics market is segmented into component, deployment model, enterprise size, application, industry vertical, and region. By component, the market is bifurcated into software and services. On the basis of deployment model, it is categorized into on-premises and cloud. Depending ion enterprise size, the market divided into large enterprises and SMEs. The applications covered in the study include customer experience management, marketing management, governance, risk, and compliance management, document management, workforce management, and others. As per industry vertical, the market is fragmented into retail, BFSI, travel & hospitality, media & entertainment, healthcare, IT & telecom, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
By Component
Software segment is projected as one of the most lucrative segments.
The key players profiled in the text analytics market analysis are Clarabridge, Inc., IBM, Luminoso Technologies, Inc., Megaputer Intelligence, Inc., Microsoft Corporation, Micro Focus LLC, Open Text Corporation, Oracle Corporation, SAP SE, and SAS. These players have adopted various strategies to increase their market penetration and strengthen their position in the text analytics industry.
By Application
Customer Experience Management segment is projected as one of the most lucrative segments.
Top Impacting Factors
Surge Need for Social Media Analytics
The text analytics market growth is attributed to factors such as surge in penetration of mobile phones and tablets with access to internet coupled with ever-growing user volume on social media platforms. Social media analytics includes analysis of customer surveys and their feedbacks on various products, using natural language processing and sentiment analysis, helps provide much more meaningful insight to the organization. The social media platform helps companies to identify the latest market trends and to create a brand image, which would, in turn, help companies to increase their existing customer base. This helps the companies to understand customers in a better way by identifying their interests and demands. Multiple vendors provide social media as a monitoring platform with different degrees of sophistication in the analysis of the text due to which companies get an advantage to analyze their customer base.
In addition, consumer accessibility through social media platforms further reinforce the need for social media analytics tools for enterprises globally. For instance, according to Facebook, it had 1,562 million active users daily, as of the first quarter of 2019. Twitter stated that 500 million Tweets are sent each day and 9% more people are using Twitter every day, reinstating the growing penetration of social media networks at a global level.
Predictive Analytics for Businesses
Predictive analytics is helping companies to optimize their internal operations, improve customer satisfaction, manage budgets, identify new markets, and anticipate the impact of external events. Moreover, as technology becomes more accurate, easier to use, and cheaper, the benefits of this type of analytics will continue to increase. Furthermore, it uses standard statistical techniques, machine learning, deep learning, and other types of artificial intelligence technologies to predict future outcomes based on current and past data. In addition, various business organizations are adopting predictive analytics to solve difficult problems and gain advantage in the market, which is driving the growth of the text analytics market. It helps in resolving problems such as fraud detection, reducing risk, optimize operation, and improving market campaigns. Thus, all these factors act as the key driving forces of the text analytics industry.
By Region
Asia-Pacific would exhibit the highest CAGR of 19.3% during 2021-2030.
Key Benefits for Stakeholders
- The study provides an in-depth analysis of the global text analytics market forecast along with current & future trends to explain the imminent investment pockets.
- Information about key drivers, restraints, & opportunities and their impact analysis on global text analytics market trend is provided in the report.
- The Porter’s five forces analysis illustrates the potency of the buyers and suppliers operating in the industry.
- The quantitative analysis of the market from 2021 to 2030 is provided to determine the market potential.
Text Analytics Market Report Highlights
| Aspects | Details |
 By Component |
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 By Enterprise Model | |
 By On-premises | |
 By Cloud | |
 By Enterprise Size |
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 By Application |
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 By Industry Verticals |
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 By Region |
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 By Key Market Players |
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Analyst Review
Adoption of text analytics has increased owing to industries realizing the potential of text analytics and are incorporating it as a core technology for simplifying their complex decision capability. As a result, high amounts of unstructured data are generated every minute, which represents one of the key factors encouraging enterprises worldwide to integrate text analytics. Text analytics automatically analyze data from social media posts, emails, live chats and surveys and procure quantitative insights. It assists in identifying patterns, improving customer satisfaction, detecting product issues, conducting market research, and monitoring brand reputation.
Key providers of deep learning market such as SAS, Microsoft Corporation and OpenText account for a significant share in the market. With the larger requirement from the healthcare department various companies are launching net product to increase the text analytical capabilities. For instance, July 2020, Microsoft launched the inclusion of text analytics capabilities within its Azure Cognitive Services product. This text analytics for health feature can process a wide variety of data types and tasks, including extracting more than 100 types of personally identifiable information from unstructured text. This text analytics for health enables researchers, data analysts, medical professionals in the healthcare and biomedical space to unlock a wide range of scenarios such as producing analytics on historical medical data and creating prediction models, matching patients to clinical trials, or assisting in clinical quality reviews.
In addition, with the increasing demand for getting instance solution to the problem with all the resourceful insights companies such as OpenText have introduced a new product. For instance, in April 2021, OpenText AI & Analytics launched new features and enhancements across OpenText Magellan that help support instead delivers us with answers to our questions in the form of insights that are relevant and applicable. This help to improve accuracy with Composite AI, in understand Arabic in text analytics.
Moreover, market players are expanding their partnership term looking at the future growth and opportunity. For instance, in September 2021, SAS and Microsoft partner to further shape the future of text analytics and AI. This enables customers to easily run their SAS workloads in the cloud, expanding their business solutions and unlocking critical value from their digital transformation initiatives. This partnership helps the enterprises across India which are looking to move to cloud and this trend has accelerated due to disruption brought about by the COVID pandemic.
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