Text Analytics Market By Component Type (Software, Services), By Deployment Model (Cloud Based Deployment, On-premise Deployment), By Application Type (Customer Relationship Management, Marketing Management, Competitive Intelligence, Predictive Analytics, Fraud Management, Workforce Management), By End-use Vertical (IT & Telecommunication, Government & Defense, Healthcare, Retail, Electronics, Media & Entertainment, Others) - Growth, Future Prospects And Competitive Analysis, 2019 - 2027

Steady Technology Development to Stimulate the Demand for Text Analytics Solutions

The text analytics market was worth US$ 4.63 billion in 2018 and is expected to grow at a CAGR of 14.35% from 2019 to 2027. Text analytics is the analysis of unstructured text data, extracting appropriate data, and transforming it into a structured format that can be leveraged in several ways. Extraction and analysis used in text analytics take advantage of techniques that originate in computational statistics, linguistics, and several other computer science disciplines. Social media analysis is primarily driving the adoption of text analytics across the world. Several market players provide social media monitoring solutions with a range of sophistication in terms of analysis. Such techniques have moved beyond search-based mechanisms and include text analytics to analyze sentiments. End users have realized the potential of insights from unstructured mining data, as it enables them to build superior predictive models. With rapid technological advancements and steady investment in the same, it is expected that the demand for text analytics will surge across the forecast period.

Market Synopsis

Healthcare Segment to Witness Significant Adoption for Text Analytics across the Forecast Period

Life science and healthcare industries are generating a tremendous amount of textual and numerical data pertaining to patients' records, such as medicines, diseases, symptoms, and treatments of diseases, among several others. A critical task is to filter relevant text for decision-making from a large biological repository. Medical records are dynamic, complex, and lengthy in nature. As well as the technical vocabulary used in documents, this makes the knowledge discovery process very crucial. Text mining tools in the biomedical field enable the extraction of valuable data, its rationalization, and the derivation of relationships among various species, diseases, and genes. The adoption of text analytics in healthcare offers a way to evaluate the potential of medical treatments that reflect effectiveness by comparing the number of symptoms, diseases, and their courses of treatment. With growing accuracy and efficiency, the penetration of text analytics in healthcare end-use is expected to surge at a significant rate in the following years.

Early Adoption for Text Analytics to Ensure Dominating Position in the North American Market

Presently, North America leads the overall text analytics market with a large share. In 2018, the region contributed more than 30% of the total market value generated worldwide. Europe was the second-largest contributor to the market, followed by Asia Pacific in the same year. The U.S. dominated the overall market with the presence of key text analytics companies. These organizations are steadily investing in text analytics, thereby driving the overall NLP market's growth here. Furthermore, Asia Pacific was the fastest-growing region for the text analytics market, owing to the rapid growth of end-use verticals. Asia Pacific encompasses more than 50% of the global population and is referred to as the hub for the retail sector. With the rapid penetration of text analytics across several end-use verticals, Asia Pacific is expected to retain its position throughout the forecast period.

Some of the major players profiled in the report include OpenText Corporation, RapidMiner, Inc., International Business Machines (IBM) Corporation, Lexalytics, Inc., Algolia, SAP SE, SAS Institute, Inc., Knime AG, Bitex Innovations S.I., Clarabridge, Inc., Averbis, Lavastorm Analytics, Infegy, Inc., Megaputer Intelligence, Inc., LuminosoTechnologies, Inc., Meaningcloud LLC, EpiAnalytics, and Medallia, Inc., among others.

Periods of History and Forecast

This research report presents the analysis of each segment from 2017 to 2027,considering 2018 as the base year for the research. The compound annual growth rate (CAGR) for each of the respective segments is calculated for the forecast period from 2019 to 2027

Report Scope by Segments

The text analytics market report provides market size and estimates based on market dynamics and key trends observed in the industry. The report provides a holistic view of the global text analytics market based on component, deployment model, application type, end-use vertical, and geography.

Key segments covered in the report are as follows:

Key questions are answered in this report.

  • What was the market size of text analytics in 2018 and the forecast up to 2027?
  • Which is the largest regional market for text analytics?
  • What are the key market trends observed in the text analytics market?
  • Which are the most promising components, deployment models, application types, and end-use verticals in the text analytics market?
  • Who are the key players leading the market?
  • What are the key strategies adopted by the leading players in the market?
  • What are the key trends across different geographies and sub-geographies?

 Frequently Asked Questions:

The market for Text Analytics Market is expected to reach in US$ 4.63 Bn in 2027.

The Text Analytics Market is expected to see significant CAGR growth over the coming years, at 14.35%.

The report is forecasted to 2019-2027.

The base year of this report is 2018.

Opentext Corporation,RapidMiner, Inc.,International Business Machines Corporation,Lexalytics, Inc.,Algolia are some of the major players in the global market.

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Published Date:  Jun 2019
Category:  Technology & Media
Report ID:   59730
Report Format:   PDF
Pages:   120
Rating:    4.4 (58)
Delivery Time: 24 Hours to 48 Hours   
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