Fairfield Market Research
Text Analytics Market

Text Analytics Market

Global Industry Analysis (2018 - 2021), Growth Trends, and Market Forecast (2022 - 2029)

Published Date: Upcoming | Format:

Industry: Information & Communications Technology | Author Name: Mohit

Data Science to Drive Innovations in Text Analytics

Pervasiveness of data science technology continues to drive innovations in text analytics. For customer experience (CX) professionals understanding qualitative feedback becomes extremely crucial, especially when it comes in huge volumes. It becomes extremely impractical to comb through the large data set and attend every comment. However, every comment present can uncover new insights and questions that can help businesses improve their CX quotient. To achieve this, text analytics algorithms work to come up with common themes alongside analyzing if the comment reflects a negative or a positive sentiment. With techniques such as machine learning and AI, data science can further innovate text analytics to get a continuous and fine-tuned sentiment analysis that can help businesses get quality insights from open ended comments. Developers are focusing on text analytics solutions that leverage algorithms of text mining along with NLP (Natural Language Processing) technology to get meaningful insights from huge volumes of unstructured data.

Acquiring and Integrating New Skills in Text Analytics Solutions Becomes Challenging – A Growth Pulling Factor

Software enterprises and integrators often experience confusion while procuring text analytics solutions as text analytics require varying skill set which is difficult to obtain. This skill set revolves around combining insights by scrutinizing unstructured data in a bid to optimize campaigns and achieve favorable results. Moreover, within industries there are different unique phrases, attributes, concepts, and entities. One word may have different meanings in different industries. For instance, considering the word “apple”, its perception becomes different – either from a consumer electronic device standpoint or from a food service company viewpoint. That said, a text analytics solution must be able to distinguish between the differences. It becomes tedious for developers to not only integrate horizontal and broad level capabilities in their text analytics solutions but also deep domain understanding of the unstructured text data.

North America to Slate Dominance in Global Text Analytics Market

Developed economies in North America are reflecting high growth potential for text analytics across various industries such as retail, Healthcare and BFSI. Moreover, strong economic environment has attracted several tech companies to establish their presence in the US. Companies in this region operating in the text analytics space are also focusing on integrating multilingual capabilities in their text analytics solutions. For instance, US based tech giant – Microsoft – has added “Hindi” language in its text analytics solution to support organizations and businesses with sentiment analysis. Additionally, academic institutions are getting involved in the text analytics initiative. For instance, in US, School of Information at University of California is developing BioText, a program that can assist researchers in analytics and text mining.

As market for CX (Customer Experience) solutions expands, need for latest NLP and text analytics solutions is likely to increase as it is not adequate for CX platforms to run with base level capabilities. CX platforms must include various non-English languages, better feature sets, deep vertical knowhow and NLP and text analytics across customer touchpoints and channels to gather good understanding of customer needs and wants.

Global Text Analytics Market: Competition Landscape

Tech companies are focusing on introducing new products and services circling the text analytics space, wherein few companies are integrating text analytics solutions in their legacy software and service. For instance, in June 2021 Calabridge introduced “Clara”, the intelligent search assistant that interacts with vast customer feedback and data sources to provide improved customer engagement, deliver visual results, and provide answers on critical experience in seconds. The company also announced that its text analytics solution has been integrated with Oracle Cloud CX platform, thus gaining better understanding on customer feedback from messages, surveys, social media, chats, emails, and calls.

Likewise, in May 2021, TCS and Vertica announced a strategic collaboration to accelerate modernization of data warehouses for organizations. In 2020, Microsoft integrated text analytics in its Azure Cognitive Services. This integration was mainly to facilitate processing of various tasks and data types in the healthcare domain.

Overall, the global text analytics market’s optimistic growth can be leveraged by companies that can expect potential opportunities in the coming years; as technology develops even further, so are the chances of witnessing innovations in the field of text analytics.

Few companies in the global text analytics market are SAP SE, Calabridge Inc., IBM Corporation, Microsoft Corporation, SAS Institute Inc., Megaputer Intelligence Inc., MeaningCloud LLC, Lexalytics Inc., and OpenText Corporation.

Key Elements Included In The Study: Global Text Analytics Market

  • Text Analytics Market by Product/Technology/Grade, Application/End-user, and Region
  • Executive Summary (Opportunity Analysis and Key Trends)
  • Historical Market Size and Estimates, Value, 2018 - 2021
  • Market Value at Regional and Country Level, 2022 - 2029
  • Market Dynamics and Economic Overview
  • Market Size in Value, Growth Rates, and Forecast Figures, 2022 - 2029
  • Competitive Intelligence with Financials, Key Developments, and Portfolio of Leading Companies 
  • Regional and Product/Grade/Application/End-user Price Trends Analysis
  • Value Chain and Five Force’s Analysis
  • Regional/Sub-region/Country Market Size and Trend Analysis
  • Company Market Share Analysis and Key Player Profiles

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