What is Text Analytics ?Text analytics is a tool which applies sets of statistical, linguistic, and machine learning techniques to analyze the text data gathered from social and enterprise sources. Text analytics software solutions have an increased demand among business groups in order to automate the identification of entities, topics, events, concepts, and personal attributes, and streamline the decision-making and business optimization processes. Nowadays, text analytics has been finding the greatest use in Customer Experience Management (CEM), marketing management, governance, risk and compliance management, document management applications.
360Quadrants recognizes the below-listed companies as the best Text Analytics Software -
Top 10 Text Analytics Software in 2020:
- SAP SE
- IBM CORPORATION
- SAS INSTITUTE INC
- CLARABRIDGE INC
- EPAM SYSTEMS INC
- FAIR ISAAC CORPORATION (FICO)
The vendors are placed into 4 categories based on their performance in each criterion: “Vanguards,” “Innovators,” “Emerging,” and “Dynamic.” We have evaluated the top 25 vendors that include ai-one Inc., Ascribe, Averbis, Bitext, Clarabridge, Inc., EPAM Systems, Inc., Etuma Ltd., Expert System S.p.A., Fair Isaac Corporation (FICO), Fractal Analytics Inc., IBM Corporation, Infegy, Inc., KNIME.com AG, Knowliah, Lexalytics, Inc., Luminoso Technologies, Inc., MaritzCX Research LLC, MeaningCloud LLC, Megaputer Intelligence, Inc., OpenText Corp., RapidMiner, Inc., SAP SE, SAS Institute Inc., SpazioDati, and Squirro. The analysis has been carried out based on specific parameters and scores have been assigned accordingly.
Vendors who fall into this category receive high scores for most of the evaluation criterion. The vendors in this MicroQuadrant have a strong and established product portfolio and a very strong market presence. They provide mature and reputable text analytics software and services that cater to a wide range of verticals globally. They also have strong business strategies.
They are established vendors with very strong business strategies. However, they are low in product portfolio. They generally focus on a specific type of technology related to the product. The vendors included in this MicroQuadrant have a good customer base and are providers of software and services catering to other technologies as well.
Innovators in the MicroQuadrant are vendors that have demonstrated substantial product innovations as compared to their competitors. They have very focused product portfolio. However, they do not have very strong growth strategies for their overall business.
They are vendors with niche product offerings, who are starting to gain recognition in the market. They do not have very strong business strategies as compared to other established vendors. They might be new entrants in the market and require some more time before getting significant traction.
The text analytics software market is segmented on the basis of various application areas, such as CEM; marketing management; governance, risk, and compliance management; document management; and workforce management. Text analytics is being widely adopted by organizations across various industry verticals to manage their enterprise content better, improvise marketing efforts and brand reputation, and enhance the customer experience. Text analytics software aims at providing actionable insights from the unstructured data and is becoming an important part of the current predictive analytics landscape.
CUSTOMER EXPERIENCE MANAGEMENT
In recent years, understanding the customer experience has been determined as the most efficient way of retaining customers and improving businesses by acting on the gathered insights. Organizations are focusing on exceeding customer demands so that they are bound to interpret and act on the customer’s feedback. With the advent of big data and methods to analyze collected data, text analytics has emerged as a promising technique for extracting insights from the customer’s data, shelling enterprises through survey questing, social media, and reviews. Additionally, companies prefer to utilize structured data, as it is easier to collect, measure, and analyze text analytics solutions that have addressed the challenges of collection and identification from numerous data sources. The application of text analytics solutions in CEM involves improvising marketing efforts and augmenting the overall customer experience. Moreover, the organizations are using sentiment analysis and NLP, which are also contributing to the growth of the text analytics market.
Analyzing the text is not new to the industry, but with the development of technologies, substantial improvements have been observed in the ability to mine the text, such as content on the internet; this improved ability is used by the organizations, so as to understand the market trends and further assist these organizations in modifying their businesses with the help of the collected information. The text analytics software solutions enable organizations across the industries in improving the feedback mechanism, market research, social media analytics, voice of customer analysis, brand reputation monitoring, advertising performance measurement, and churn analysis. Furthermore, organizations nowadays have a plethora of unstructured data generated through emails, messages, claims, contracts, patents, call center notes, operational notes, trial records, and survey responses, along with various other text-based data sources, and this data can be used to improve the marketing strategies.
GOVERNANCE, RISK, AND COMPLIANCE MANAGEMENT
Companies today are looking forward to dealing not only with well-understood challenges, such as market competition, stringent regulations, and sustained volatility but also upholding the profitability and progress in an era defined by the dynamically evolving technologies. The importance of next-generation governance, risk, and compliance management are accelerating the growth of the text analytics market by transforming the business value, while integrating technologies, such as risk modeling and governance, with business intelligence and text analytics, thus offering organizations the potential for increased profitability and competitive advantages over competitors. Additionally, the changing regulatory environment across industries is enforcing organizations to adapt text analytics, to mitigate the impact of risk and compliance over businesses.
Organizations gather huge amounts of unstructured data from various sources, namely, through emails and other documents, which contain vital information about business opportunities, risks, and challenges. Text analytics enables organizations with a variety of benefits, such as entity extraction, information retrieval, records retention, document clustering/categorization, document summary, and concept extraction. The document clustering and classification play an important role in document management. Text analytics for document management has been recognized as one of the secure methods to classify and sort the information in an organization. It helps organizations in controlling the risk, managing compliance issues, monitoring and protecting the intellectual property, and assisting in elevating the overall business operations, thus enhancing the customer experience.
The proliferation of big data has necessitated the usage of analytics in effective decision-making and organizations are looking for real-time data analysis for workforce-related business decisions. The goal of text analytics software is to deliver organizations with insights to manage employees so that the organization can reach their business goals. Text analytics in workforce management helps improve recruitment methods, which are the necessity of every organization. With the evolving customer expectations, organizations are changing their methods in delivering services to meet these expectations. Through proper customer interactions with customers across various textual communications channels, such as emails, webchats, social media, online surveys, and customer forums, organizations can discover insights. Text analytics helps organizations in reducing the cost through efficient workforce optimization and managing extensive customer interactions for accurate insights.
Frequently Asked Questions
What are the current trends that are driving the text analytics market?The current and on going trends in text analytics are growing awareness, surge in data and increasing demand for real time analytics
In which vertical most of the industrial companies are deploying text analytics solutions?Text analytics is segmented on the basis of verticals. The industry verticals include BFSI, telecommunication & IT, retail and ecommerce, healthcare and life sciences, manufacturing, government and defense, energy and utilities, media and entertainment, travel and hospitality, and others (education, research, construction & outsourcing). The healthcare and life sciences segment is the fastest growing segment in the text analytics market due to the growing demand to tackle big data and deliver valuable insights from it.
Where will all these developments take the industry in the mid- to long-term?The text analytics market is projected to grow from $3.2 billion in 2016 To $8.8 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 17.2% during the forecast period.
Who are the top vendors in the market, and what is their competitive analysis?Major vendors in the global text analytics market include SAP SE (Walldorf, Germany), International Business Machines Corporation (New York, U.S.), SAS Institute, Inc. (North Carolina, U.S.), OpenText Corporation (Ontario, Canada), Clarabridge, Inc. (Virginia, U.S.), Megaputer Intelligence, Inc. (Indiana, U.S.), Luminoso Technologies, Inc. (Massachusetts, U.S.), MeaningCloud LLC (New York, U.S.), KNIME.com AG (Zurich, Switzerland), Infegy, Inc. (Missouri, U.S.), Lexalytics, Inc. (Massachusetts, U.S.), and Averbis (Freiburg Germany). These vendors have adopted various organic and inorganic growth strategies, such as new product launches, partnerships and collaborations, and mergers and acquisitions, to expand their presence in the global text analytics market further.
What are the drivers and challenges of the text analytics market?The major growth drivers of the market include the growing need for social media analytics, and increasing need of predictive analytics for businesses. The challenges faced are Lack of awareness, skilled workforce, and other operational challenges.
InfoNgen is EPAM’s text analytics and sentiment analytics solution which is used to provide actionable insights from the big data automatically. The solution is used to search, share, and analyze critical information from both, organized and amorphous data which, in turn, will help teams to focus on strategic decisions which are backed by sufficient statistics. InfoNgen offers customers freedom to uncover patterns, trends, and anomalies hidden deep within data.
FICO® Data Orchestrator is a cloud or on-premises data recovery and plotting solution that can access, gather, and transform data from unstructured information services, such as credit reference agencies, media talks, etc. Organizations can join and convert multiple sources of data to advance operational intelligence, risk management, and usability.
teX.ai is a SaaS product solution from Indium Software. teX.ai helps organizations to solve text data problems by providing faster and scalable solutions to obtain results such as document summarization which leads to saving time, lower the costs by automating text extraction, text classification to reduce search complexity and to enhance the customer experience. teX.ai offers a variety of solutions across six major domains or industries.
Dandelion API converts text to actionable data. It extracts meaning from unstructured text and puts it in context with a simple API. Dandelion API controls its underlying Knowledge Graph, without trusting traditional NLP channels. This makes it faster, extra-scalable, easier to customize, and natively language independent.
Cogito Discover provides complete understanding of written text at gauge to guarantee that the insight and knowledge implanted in unstructured information is accessible for tactical and operative analysis and effortlessly usable by process automation robots. Cogito Discover’s Natural Language Understanding engine delivers influential multilingual classification, entity and association mining, and text analytics that detects unseen relevant information in business papers.
Text meta-analysis is among the most critical business actions in modern database systems and business information systems. However due to its complex nature, it is not often incorporated. RapidMiner provides creative text analytics solutions that meet all the data needs of businesses where textual descriptions are present and need to be stored or examined.
In the age of data and analytics, each and every organization has its own unique definitions, idioms, and language trends. MaritzCX Text Analytics ensures the capture of all the trends along with specific customizations that integrate words and phrases that apply specifically to products and industries across multiple languages. Users can instantaneously tap into all the investigation, skills, and knowledgeable capital.
Ascribe comes with a wide range of products for text analytics. Ascribe Coder is used to categorize the verbatim comments faster and efficiently. CX Snapshot is used to disclose insights from Customer Experience (CX) comment. CX Inspector is used to uncover customer insights automatically and efficiently. Lastly, Ascribe illustrator is used to prepare reports and dashboards from the data received through customer comments and feedback.
The Analyst Toolbox is the platform built by analytic experts to derive smarter and better results from unstructured data. The BrainDocs tool can scan through a significant number of documents, databases, and websites to regain the data that directly relates to business. BrainDocs uses AI agents to analyze unstructured data. The agents can classify, organize, filter, and make the data search possible with keyword search, NLP, LSI, or any other statistical tool.
Etuma text analysis service converts all open-ended client feedback into reliable and actionable data. Etuma has current connectors to dozens of surveys, customer experience management, and contact center platforms. Users can also connect any spontaneous feedback channel such as email or webforms. Etuma has connectors to most common social media sites.
The text analytics solution from Fractal Analytics solves organizational challenges by converting unstructured data into actionable insights with the help of machine learning algorithms and natural language processing.
Squirro is an AI-based platform which uses machine learning to update users about the data and the next challenge. This platform helps a company to build better relationships with clients, partners, and predict the anomalies in the system and data automatically. This platform makes use of the 99% inactive data to offer insight-driven analytics.
Knowliah provides a software solution that handles amorphous information and data, based on extremely innovative algorithms to clean intelligence and for the automatic enhancement of text through meta-data. Scripts, documents, and e-mails are repeatedly analyzed, augmented, and classified. The automation has helped users by enabling minimal manual intervention.
Data Cataloging is the solution provided by Alteryx INC to cut the time spent searching the data and making it more meaningful. The powerful data cataloging provided by Alteryx Connect unifies business relationships and meanings, metrics, and information assets for supreme consistency, discoverability, and teamwork.
Angoss Software Corporation (Angoss) and Lexalytics Inc. are in partnership to give advanced capabilities to Angoss’ big data analytics and rallies the accuracy of predictive analytics modelling by growing the types and volume of data that can be analyzed to include unstructured, text-based data.
TIBCO Spotfire provides a unique and leading solution of data wrangling which is used to prepare the smart and impressive data from raw data sources such as customer feedbacks and comments about the product. Spotfire generates automagical dataflows that records steps on the data canvas, creating an auditable data lineage for easy editing, reuse, sharing, and scaling of analytics across organization.