Today, you come across texts everywhere- support tickets, emails, work chats, social media, documents, the list is long. However, these texts are all completely useless unless you can extract valuable insights from them. That’s where text analysis software solutions come in.
Text analysis tools use data mining to help you structure vast collections of raw, unstructured text data and discover actionable insights. These tools leverage AI-powered Natural Language Processing (NLP) to recognize patterns, trends, themes, key phrases, and sentiments.
Unstructured data makes up a whopping 80% of enterprise data and continues to grow at the rate of 55% to 65% every year. If your business is looking to unleash the power of unstructured data with text mining software, this article is for you.
Explore the top seven text analysis tools, their features, pros, cons, and use cases.
The top text analysis tools in 2022:
Levity: best no-code solution
Amazon Comprehend: best pre-trained models
Chattermill: best customer sentiment analysis
Microsoft Azure: best for key phrase extraction
Relative Insights: best for social listening
Lexalytics: best Cloud API
Thematic: best for customer feedback
Top features of text analysis software to look out for
Organizations should look for the following features while choosing text analysis software to find measurable insights and improve business decisions.
Interprets unstructured data: from emails, chats, social feeds, messages, and reviews.
Finds themes in open-ended texts and quantifies responses for insights.
Analyzes customer sentiment to discover terms that resonate better with the target audience.
Ensuring these features in your text analysis software helps you keep data safe and secure.
Benefits of using text analysis tools
Businesses use text analysis tools to analyze and visualize countless unstructured data for qualitative and quantitative insights. Text analysis can help your business to:
Discover pain points or satisfaction areas: analyze customers’ feedback to open-ended questions to optimize existing processes.
Identify trends and patterns: sort and visualize verbal feedback categories to resolve queries on time and create meaningful customer experiences.
Prioritize issues: use word pairing to identify problem areas and resolve issues quicker.
Sort requests: leverage AI to categorize incoming requests by urgency, geography, or work type.
Increase revenue: correctly convert data-as-is with text analytics to reduce manual work and operational costs.
Find new opportunities: develop better products and features with insights into customer preferences and needs.
Looking for the best text analysis software? Explore these top text analytics solutions to gain greater insights from structured and unstructured data.
The 7 best text analysis software solutions
1. Levity: best no-code solution
Categorize customer support tickets with Levity
Levity is a no-code workflow automation platform. It helps businesses create and train AI blocks to automate complex, repetitive processes. Levity's text analysis software lets you create and train custom AI models easily, regardless of whether your workflow contains text, images, or documents.
Levity helps you automate processes, boost employee productivity, and improve customer experience by implementing AI in business.
Features
Explore how Levity helps businesses of all sizes meet automation needs with these robust features.
AI blocks: that use pre-trained models or custom algorithms to perform manual tasks and make processes intelligent. Once you train these blocks with training data, you’ll be able to automate end-to-end workflows using Levity. These AI blocks can work autonomously as they learn and improve over time.
Integrations: help you to connect Levity AI blocks with apps you already have in your tech stack. Leverage Zapier, Inegromat, or Levity API for seamless integrations.
Levity pros
Easy-to-use platform for non-technical people
Super responsive customer support
Useful third-party integrations
Free trial available
Levity cons
Doesn’t support on-premise deployment
No in-person training available
Try it out yourself
Create your own AI for documents, images, or text to take daily, repetitive tasks off your shoulders.
Amazon Comprehend uses Natural Language Processing (NLP) to discover insights from texts across documents, support tickets, emails, social media feeds, and product reviews.
This text analysis software helps you mine unstructured data phrases to uncover text connections and insights. You can also train and customize models to classify texts suitable for your business.
Features
Amazon Comprehend offers the following features to help you integrate NLP into applications and find data-driven insights.
Custom entity extraction: identifies domain-specific terms using AutoML.
Entity recognition: categorizes entity names based on text input.
Sentiment analysis: analyzes customer feedback to recognize sentiments.
PII Identification and redaction: censors personally identifiable information (PII) from texts.
Keyphrase extraction provides key phrases from texts and offers a confidence score.
Topic modeling: identifies common topics and terms in a document collection.
Amazon Comprehend pros
High native language accuracy
Quick integration with AWS hosted services
Easy-to-use and intuitive product interface
Amazon Comprehend cons
Steep learning curve
Can be expensive
Offers generic models for specific use cases
3 Chattermill: best customer sentiment analysis
Chattermill
Chattermill is a unified customer feedback analytics software helping companies to uncover insights from support conversations and more. This easy-to-use collaborative platform uses them and sentiment AI to help companies interpret what customers feel and identify improvement opportunities.
Features
Chattermill offers the following features to help you unify, measure, and analyze customer feedback.
Feedback analysis: uncovers real-time insights from feedback, conversations, and reviews across channels.
Analytics: visualizes insights and customer experience metrics with powerful charts and graphs.
Workflows: automate repetitive tasks and helps you address customer needs by triggering actions based on custom conditions.
Dashboards: keep your team in sync with custom reports and dashboards.
Chattermill pros
Easy to share reports with non-Chattermill users
Intuitive platform for programmatic text analysis
Holistic reporting data filters
Chattermill cons
Lacks report customization options
Needs to develop impact-related analytics
Inaccurate message interpretation at times
4. Microsoft Azure:best for key phrase extraction
Microsoft Azure
Microsoft Azure uses NLP to help you analyze customer sentiment and extract key phrases or entities. You can also use this text analysis software to use pre-trained models to classify medical terminology. Companies leverage Azure’s web-based language studio, client libraries, and REST APIs to build intelligent applications.
Features
Microsoft Azure extracts and classifies text documents with the following features.
Broad entity recognition: identifies key phrases and entities such as events, organizations, people, PII, and protected health information (PHI).
Sentiment analysis: mines opinions to discover what customers are saying about your brand.
Document summarization: conveys collective sentiments in a document.
Medical text processing: offers real-time insights from unstructured medical text.
Workflow automation: uses domain-specific labels to categorize unstructured text and improve decision-making.
Microsoft Azure pros
Responsive APIs
Seamless data structuring and collection process
User-friendly and scalable solution
Microsoft Azure cons
Old-fashioned filters
Confusing client libraries
Steep learning curve
5. Relative Insights: best for social listening
Relative Insights
Relative Insights is a text analysis solution that helps marketing, sales, and HR teams discover objective and actionable insights. This AI-powered platform leverages NLP and comparative linguistics to analyze text data and offer contextual understandings.
Companies use this tool to derive insights from social conversations and make informed decisions.
You can also use Relative Insights to analyze market research data, voice of customer surveys, and gain competitive intelligence. This software supports different languages such as Danish, German, English, Finnish, French, Hungarian, Italian, Dutch, Norwegian, Portuguese, Romanian, Spanish, and Swedish.
Features
Relative Insights offers the following features to ease how you analyze texts and visualize insights.
AI-powered text analysis: helps you dive deep into unstructured feedback and target audience conversations.
Trendspotting: shows the impact of strategic initiatives with powerful charts.
Custom themes: reveal topical themes of social conversations.
Audience intelligence: tracks customer feedback in real-time and offers insights.
Relative Insight pros
Well-organized data comparison
Easy-to-use and intuitive platform
Responsive customer support
Relative Insight cons
Longer learning curve
Difficult to capture and export insights
Limited linguistic comparison abilities
6. Lexalytics: best Cloud API
Lexalytics
Lexalytics uses Machine Learning and NLP technologies to analyze high volumes of text data on-premise, via cloud API, or cloud-based platform. The Lexalytics Intelligence platform offers end-to-end text analytics solutions for the voice of customer data, social media listening, process automation, and regulatory compliance.
Their on-premise NLP platform Salience is ideal for companies looking to deploy text analytics and NLP software libraries on-premise for security reasons. The NLP cloud API Semantria caters to those looking to integrate cloud-based enterprise data analytics infrastructure into their platform.
Features
Below are the features that make Lexalytics the best cloud API solution for text analysis.
Configuration: offers intuitive tools to help you build custom entities, create new topics, and category taxonomies.
Industry packs: offers pre-built industry configurations to improve categorization, sentiment accuracy, and topic detection.
Deployment: allows you to combine on-premise, private cloud, hybrid cloud, or public cloud infrastructure to analyze data.
Interoperability: eases how you integrate NLP into enterprise analytics infrastructure.
Lexalytics pros
Customizable features
Reliable insights
Strong integration options
Lexalytics cons
Interface reporting lacks ease of use
Scope of development in entity engine
Exports data to Excel only
7. Thematic: best for customer feedback
Thematic
Thematic is a collaborative customer feedback analysis platform. It uses AI-driven thematic and sentiment analysis to help you understand and analyze customer feedback. This software solution is ideal for insights analysts, researchers, and product managers looking to transform unstructured feedback into actionable insights.
Features
Thematic offers the following features to help you unify data analytics for better decision-making.
Connect & combine: helps you connect online review sources and automate data redaction.
Tag & theme: quantifies repeated themes across sentiments for better insights.
Slice & dice: refines and analyzes structured data to help you discover and address major customer pain points.
Thematic Pros
Real-time signals on customer issues
Granular verbatim theme for insights
Responsive customer support
Thematic cons
Longer learning curve
Lacks instant data analysis
Lacks robust integrations
Make better decisions with Levity
Manual text analysis can take hours. Furthermore, manual text processing can be inefficient for thousands of support tickets, social conversations, and text in general. That’s why companies use text analysis tools to analyze unstructured or semi-structured data.
Levity is a leader in the text analysis space, helping companies to gain actionable insights and grow faster. With Levity, you can build and train AI models to work smarter and boost ROI.
Text analysis software uses Natural Language Processing (NLP) to help users gain insights from unstructured, structured, or semi-structured data. Companies can use text analysis tools to draw meaningful insights like phrases, key themes, patterns, and entities from reviews, social conversations, and support tickets. Explore best-in-class text analysis with Levity.
2. What are the functions of text analysis?
Key functions of text analysis are:
Language identification
Tokenization
Sentence breaking
Part of speech tagging
Chunking
Syntax parsing
Sentence chaining
Text analysis involves extracting insights by parsing texts. Text analysis tools use machine learning and Natural Language Processing (NLP) to slice and interpret data.
Now that you're here
Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.If you liked this blog post, you'll love Levity.
Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.If you liked this blog post, you'll love Levity.
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