Text Analytics Market study on key players, Industry Share and Regional Analysis

Text Analytics Market study on key players, Industry Share and Regional Analysis

What are the key factors accelerating global text analytics market size?

Analytics is slated to the potential to revolutionize the way organizations commence their businesses. With efficient analytics, companies can examine enormous amounts of data to uncover correlations, hidden patterns, and other business insights. Given to the growing need to streamline unstructured data, the text analytics market is projected to gain immense traction in the coming years.

The need to gain valuable business insights by analyzing customer behavior would act a primary growth enabler for its industry. Moreover, with growing significance, the Global Market Insights, Inc., predicts that the text analytics market may surpass USD 15 billion by 2026.

Why are governments agencies worldwide turning towards text analytics industry?

Governments across the world are transitioning from conventional public services to e-governance online services. These services require advanced analytics solutions to formulate new policies. Text analytics solutions help federal agencies to extract and evaluate information and attain key insights.

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Policymakers are leveraging text mining systems to compare and establish new policies under the existing framework. Moreover, government organizations are using text analytics to enhance policy analysis, analyze pubic feedback, and improve regulatory compliance for better decision making.

How is text analytics market gaining traction across insurance sector applications?

Enterprises worldwide are using text analytics to mitigate the risk of fraud. Text mining can help detect similar patterns misrepresent facts and fake claims which reduces risk and financial burden on insurance firms. Organizations are analyzing documents from unrelated claimants to uncover similarities in claim patterns and verify the authenticity of the claims.

Citing March 2017 instance, the United Service Automobile Association (USSA) collaborates with IBM Global Services to detect fake insurance claims using text analytics. With this technology, the could reduce fake claims cases and enhance customer experience by fueling the process of claim settlement.

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What are some of the key factors driving Latin America text analytics industry forecast?  

Latin American countries including Brazil and Mexico are actively adopting social media analytics. Organizations are leveraging text analytics solutions to understand customer preferences based on their social media behavior. They are utilizing text analytics to plan strategies and target-appropriate customer base depending on parameters like region, gender, and demography. In addition to this, significant investments in Neuro-Linguistic Programming (NLP) are supporting the regional market growth over recent years.

Latin American companies are also seen partnering with text analytics solutions providers to enhance their customer experience. In 2019, online media company, Universo Online (UOL) collaborated with Utopia Analytics for leveraging their AI-based moderation service to pre-moderate all the comments on its platform in real-time. This partnership would help UOL automate comment moderation on its platform to increase customer experience.

Which business strategies are being adopted by companies to capture text analytics industry share?

Companies operating in the text analytics industry are focusing on initiating strategic alliances with other market players, primarily to be at the forefront of this lucrative industry. New entrants in this market are commencing R&D activities to develop advanced services attain a significant market share.

In 2018, Unmetric, Inc. introduced custom content tagging that enable marketers to understand and identify the most engaging content categories across social media handles and modify their social media strategies.

Table Of Content

Chapter 1    Methodology & Scope

1.1   Methodology

1.1.1    Scope

1.1.2    Definitions

1.1.3    Methodology and forecast parameters

1.2   Data Sources

1.2.1    Secondary

1.2.2    Paid sources

1.2.3    Public sources

1.2.4    Primary

Chapter 2   Executive Summary

2.1   Text analytics industry 3600 synopsis, 2015 - 2026

2.2   Business trends

2.3   Regional trends

2.4   Component trends

2.5   Deployment trends

2.6   Application trends

Chapter 3   Text Analytics: Industry Insights

3.1   Introduction

3.2   Industry segmentation

3.3   Industry landscape

3.4   Global predictive analytics market landscape, (2018 – 2026)

3.5   Evolution of text analytics

3.6   Text analytics industry architecture

3.7   Text analytics industry ecosystem analysis

3.8   Technology & innovation landscape

3.8.1    Big data analytics

3.8.2    Artificial Intelligence

3.8.3    Natural Language Processing (NLP)

3.9   Regulatory landscape

3.9.1    North America

3.9.1.1    Standards on Privacy and Web Analytics (Canada)

3.9.1.2    Health Insurance Portability and Accountability Act (HIPAA) of 1996 (U.S.)

3.9.2    Europe

3.9.2.1    General Data Protection Regulation (EU)

3.9.2.2    Exception of Text & Data Mining (TDM) in Copyright in Digital Single Market (DSM Draft Directive - EU)

3.9.3    APAC

3.9.3.1    Information Security Technology- Personal Information Security Specification GB/T 35273-2017 (China)

3.9.4    Latin America

3.9.4.1    The General Data Protection Law (Brazil)

3.9.5    MEA

3.9.5.1    Federal Law No. 2 of 2019 on the use of ICT in Healthcare (UAE)

3.10 Industry impact forces

3.10.1    Growth drivers

3.10.1.1    Growing demand for social media analytics

3.10.1.2    Increasing use of business intelligence tools

3.10.1.3    Proliferation of cloud computing technology

3.10.1.4    Growing demand for sentiment analysis

3.10.2    Industry pitfalls and challenges

3.10.2.1    Lack of awareness

3.10.2.2    High cost of software

3.10.2.3    Risk of data theft and cyber attacks

3.11 Growth potential analysis

3.12 Porter’s analysis

3.13 PESTEL analysis

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