Text Analytics Market is expected to reach US$ 27.63 billion by 2028


PRESS RELEASE BY The Insight Partners 05 Jan 2023

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The Text Analytics Market size is expected to reach USD 27.63 billion by 2028; registering at a CAGR of 20.4% from 2022 to 2028, according to a new research study conducted by The Insight Partners.

Significant Growth in Natural Language Processing (NLP) to Provide Growth Opportunities for Text Analytics Market During 2022–2028

The global text analytics market growth is primarily driven by an increase in the volume of unstructured data. This increase can be attributed to the growing use of social media platforms, consumer inclination toward online buying, and digitalization of different operations. The analysis of unstructured data can uncover key data patterns, which can be the bases of decision-making in organizations. The traditional methods of data analysis (mostly manual) are ineffective when the data volume increase. in such cases, text analytics software products are employed to handle huge volumes of data. Moreover, companies can utilize only 30% of data generated if it is unstructured; these stats represent a significant opportunity for vendors to develop analytical solutions featuring advanced capabilities that are supported by machine learning, NLP, and language. Countries such as the US, UK, South Africa, China, Japan, Canada, South Korea, India, Russia, and Singapore generate high demand for text analytics solutions owing to the generation of Big Data. High demand for text analytics in mentioned countries would have a positive impact in the text analytics market growth.

NLP is a branch of data science that enables automated analysis to obtain meaningful insights from human languages. It is used to supplement manual processing, eventually lowering the need for manual processing. When NLP is used properly, it lowers operational costs while enhancing the quality of outcomes. With the growing popularity of text analytics at an exponential rate, the number of companies offering these solutions is also increasing. Genesys, Bobble AI, TigerConnect, Clarabridge, Kira Systems, Sinequa, Talkwalker, Seedlink, AYLIEN, and Take Blip are a few of the companies offering text analytics solutions. Growing inclination towards NLP is projected to create more opportunities for text analytics, and thus contributing to the text analytics market.

Europe is one of prominent regions adopting text analytics technology and therefore is a second largest region in text analytics market. The European countries are catching up with the adoption rates as those reported in North America, and the Nordic countries are also following this trend. Amongst the Nordic countries, Finland is a leading adopter of cloud computing technologies, followed by Sweden and Denmark. In Europe, the telecommunication industry is harnessing AI-driven text mining products. Moreover, with the prevalence of the work-from-home model during the COVID-19 pandemic, digital connectivity became a necessity. This urged telecom service providers to use text analytics solutions to provide a better customer experience. Wonderflow, an AI-based analytics platform that uses advanced NLP capabilities, has been a commonly used text analytics solution in Europe. Its capabilities allow it to source all correct data from the right channels.

The demand for NLP and cloud services surged at an exponential rate after the onset of the COVID-19 pandemic which positively impacted the text analytics market. The US government, in a partnership with research institutions and tech companies, aimed to develop novel text and data mining techniques to help researchers in fighting against COVID-19 using artificial intelligence. The pandemic situation resulted in an urgent need for the text mining techniques owing to the increased demand for competitive intelligence, predictive analysis, social media monitoring, and fraud/spam detection. The use of AI-enabled NLP increased amid the global crisis owing to the generation of enormous unstructured text from hospitals and remotely working employees. To simplify the unstructured data generated through social media platforms, sentimental indicators were used to obtain the pandemic-related updated from different countries, such as South Korea, the US, Germany, Italy, Spain, China, and Brazil. The Global Database of Events, Language and Tone (GDELT) used a few techniques to gather information on the fight put up by these countries against the COVID-19 pandemic. The onset of COVID-19 has resulted into use of more advanced technologies for analysis purpose including text analytics. This factor fueled the text analytics market during 2020.

Specifically, the NLP technology holds a massive potential when ample of text-based data are generated from published medical literature, health/hospital systems, and social media websites. Since, NLP is used for sentiment analysis, linguistic text analysis, and translations use cases. NLP will endure with proliferating the text analytics market globally.

Text Analytics Market – by Region, 2022

Text Analytics Market – by Region, 2022


Text Analytics Market Size and Forecasts (2021 - 2031), Global and Regional Share, Trends, and Growth Opportunity Analysis

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Text Analytics Market Size and Forecasts (2021 - 2031), Global and Regional Share, Trends, and Growth Opportunity Analysis Report Coverage: by Deployment Type (Cloud-Based and On-Premise), Technology (NLP, AML, and Hybrid), Application (Predictive Analysis, Competitive Intelligence, Fraud/Spam Detection, and Social Media Monitoring), and Vertical (BFSI, Telecom, FMCG, Government, Academia and Education, Legal & Intellectual Property, Healthcare, Pharmaceuticals, Chemistry & Materials, Retail, and Others), and Geography (North America, Europe, Asia Pacific, and South and Central America)

 Source: The Insight Partners Analysis

Based on vertical, the text analytics market size is segmented into BFSI, telecom, FMCG, government, academia and education, legal & intellectual property, healthcare, pharmaceuticals, chemistry & materials, retail, and others. The retail segment dominated the text analytics market in 2022. Retail players around the world rely on text analytics in all the stages of their retail process, such as sales and demand forecast, tracking popular and emerging products, and optimizing product placements. Text analytics also offers heatmaps of competitors. This helps in identifying customers who may be interested in certain products depending on their purchases in past, finding the most appropriate way to lure them by specific marketing strategies and to know what to sell next by implementing text analytics. Through text analytics, retail companies can achieve price optimization, future performance prediction, demand prediction, and trend forecasting, along with grabbing highest ROI opportunities. With continuous technological developments, the adoption of text analytics would continue to grow in the retail sector and will accelerate the text analytics market. AI-based analytics enables retailers to gather structured data and customer response, in the form of Net Promoter Scores and star ratings.

Rising retail industry is projected to create lucrative use of text analytics for processing customers’ reviews which would help in formulating necessary strategies for their business. This factor will contribute towards the rise of text analytics market size in retail.

Angoss Software Corporation; Averbis GmbH; Bitext Innovations S.L.; Cambridge Semantics, Inc.; Clarabridge; Clarivate Analytics; RapidMiner Inc.; (Altair); Expert System Group; Linguamatics, Basis Technology; SciBite; KNIME; IBM Corporation; Quertle Right Signature LLC; Semantria (Lexalytics); OpenText Corp; Thomson Reuters; Biomax Informatics AG; Elsevier; SAP SE; and SAS Institute Inc. are some of the key text analytics market players profiled in the study. Many other text analytics market players were also analyzed during the course of the study.

  • In November 2022, Microsoft Israel introduced an Azure Cognitive Services application – Text Analytics for Health (TAFH) to assist doctors read and organize the unstructured text. TAFH utilizes artificial intelligence to transform medical data. Using NLP, it identifies and detects medical terms in text, further classifying and relating them with a standard clinical coding system.
  • In May 2021, Oracle Corporation made an announcement of its Oracle Analytics Cloud innovations. The innovations include explainable machine learning, automated data preparation, affinity analysis, graph analytics, and custom map analytics. The innovation on text analytics would allow users to draw words from unstructured data, count and picture the results, and combine the analysis with original data.
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