Top 20 Text Analysis Tools and Software for 2024

Imagine a world where businesses decipher customer sentiments, researchers unveil hidden academic gems, and social media becomes an open book of insights. 

This is possible by using text analysis tools. They offer valuable insights from various data sources and have revolutionized how we understand and utilize textual data, providing a competitive edge in today's data-driven world. 

In this blog, we will uncover the best text analytics software based on different use cases, their top features, pros and cons, and pricing so you can choose the best text analysis tools for your requirements. But first, let’s understand what text analysis tools are before diving into the list of text tools that you can use to analyze your text data. 

TL;DR

• Text analytics tools use NLP and machine learning to analyze text data such as customer feedback, surveys, and reviews, for extracting insights on meaning, sentiment, and context.

• They turn unstructured data into actionable gold by identifying issues, trends, and sentiments to enhance products, services, customer experiences, monitor brands, conduct market research and create competitor strategies. 

• We have shortlisted the top 20 text analysis tools catering to diverse needs like feedback analysis, business intelligence, sentiment tracking, academic research and more.

• The list includes software such as Zonka Feedback's no-code AI survey analysis, Lexalytics' business intelligence prowess, Hootsuite's sentiment tracking among others.

• We have also highlighted the key steps to choose a text analysis software that includes defining goals, exploring options, and evaluating software based on features, usability, and cost. 
• Zonka Feedback offers a powerful AI-driven engine to fuel its text analysis software. You can schedule a free demo or sign up to avail a free 14-day trial of the tool.

Turn Customer Feedback Into Actionable Insights

With Text Analytics Software, extract insights from unstructured data and understand your customers better.

What Is Text Analysis?

Text analysis, often called text mining or text analytics, is the process of analyzing and extracting actionable insights from unstructured text data. Unstructured text data can come from a variety of sources, such as feedback, call logs, emails, social media, community discussions, customer reviews, and more. 

By using clever computer programs like Natural Language Processing and Machine Algorithms, text analysis can reveal patterns and connections that you might miss on your own. This lets you understand what people are saying, what they care about, and even how they're feeling. 

💡According to Gartner, "Text analytics is the process of deriving information from text sources. It is used for several purposes, such as: summarization (trying to find the key content across a larger body of information or a single document), sentiment analysis (what is the nature of commentary on an issue), explicative (what is driving that commentary), investigative (what are the particular cases of a specific issue) and classification (what subject or what key content pieces does the text talk about)." 

What are Text Analysis Tools and Software?

Gone are the days when businesses would sit in large groups, have the customer feedback on paper, and analyze what the reviewer meant. 

Now, several tools allow the automatic analysis of unstructured data and convert it into insights. These tools use the latest technologies like natural language processing and artificial intelligence to understand the hidden meaning or content of the words.

And that’s what text analysis tools and software do. 

💡Text analytics analyze open text and drive crucial information to offer actionable insights. These insights showcase the customer’s sentiments, intent, emotions, and many more drivers that can help businesses make data-driven decisions and improve business processes. 

Text analytics tools come in various forms, from cloud-based platforms to desktop applications, catering to different needs and technical expertise. They generally offer a range of functionalities like:

These tools come in various forms, from cloud-based platforms and solution-as-a-service to desktop applications, and more. They offer a range of functionalities like:

• Customer feedback analysis
• Market research
• Social media analysis
• Academic research
• Business Intelligence

Best Text Analytics Tools at a Glance

Here are the best text analysis tools based on different use cases that you can consider:

List of Best Text Analytics Tools for Different Use Cases

Based on the different functionalities that text analysis tools promise to fulfill, we have created a list of the top tools. 

For Customer Feedback & Survey Analysis 

Understanding and extracting insights from customer reviews, surveys, and comments to improve products and services is a crucial part of a text analysis tool. There are many survey software that are powered by text analytics engines to drive meaningful insights from open-ended feedback. 

Here are some of the major tools:

1. Zonka Feedback

Zonka Feedback integrates advanced text analysis into its survey and feedback analysis, featuring a robust AI-driven engine. This engine converts unstructured open-ended feedback into structured insights. By leveraging NLP and ML, the tool extracts specific customer sentiments, identifies emerging trends, and enhances overall customer experience through structured analysis.

The sentiment analysis model analyzes text and derives sentiments, intent, emotion, entities, and statement-based sentiment from it. The information obtained can help you drive product improvements, perform market research, monitor public perception of your brand, understand customer sentiments and analyze large volumes of text for research purposes. 

It also offers automated themes and tagging that will automatically detect topics (either manually added by the user or AI-detected) to categorize and organize the data and make more sense of it. 

Key Features

• Text Analytics Reports: Generate comprehensive reports summarizing key findings, important keywords, topics, and sentiment distribution from your survey comments.
  
• Word Cloud: Visualize the most frequently used words in your feedback data with a visually appealing word cloud, highlighting key themes.
• Word Count Frequency: Identify frequently repeated words in comments, displayed in a Word Cloud Table with their frequencies and corresponding NPS, CES, and CSAT scores
• Keyword Extraction: Find the most frequently mentioned keywords and topics within your feedback to understand what truly matters to your customers.
  
• Sentiment Analysis: Gain a deeper understanding of customer sentiment by automatically classifying comments as positive, negative, or neutral. 
• Intent Identification: Categorize feedback based on customer intent, such as praise, complaint, suggestion, or recommendation and prioritize customer needs effectively.
  
• Trend Analysis: Track how customer sentiment and key topics evolve over time, enabling you to identify emerging issues and measure the impact of your actions.
• Key Driver Analysis: Identify the root causes of customer satisfaction (or dissatisfaction) by pinpointing the words and phrases that have the strongest correlation with your CX metrics (NPS, CES, CSAT).
• Cutting-edge AI Reports: Get detailed summaries of sentiments, response levels, emotions, key/negative factors, response intent, sentiment-based trends, themes, sub-themes, and tags.
• Automated Tag Generation: The AI Tagger not only suggests tags that match the responses but also generates new tags automatically, streamlining the tagging process.

2. Qualtrics

Qualtrics Text iQ empowers you to transcend mere statistics and delve into the rich tapestry of customer voices. This powerful AI-driven tool dissects open-ended feedback, uncovering hidden insights through sentiment analysis, keyword extraction, and thematic mapping. No longer are emotions and motivations a mystery.

Extract actionable intelligence to personalize experiences, predict churn, and optimize product development, all fueled by a deeper understanding of what truly resonates with your customers.

Key Features

• Text iQ: Unlock the hidden stories within your feedback with AI-powered sentiment analysis, keyword extraction, and theme uncovering.
• Go beyond statistics: Leave percentages and charts behind. Understand the emotions, opinions, and motivations behind your customers' words.
• Actionable insights: Turn your analysis into real-world results with visual reports, recommendations, and even automated actions triggered by key insights.
• Effortless integration: Connect Qualtrics seamlessly with your existing CRM, market reserach tools, and analytics platforms for a unified data hub.

3. SurveyMonkey

SurveyMonkey helps analyze open-ended responses with AI-powered sentiment analysis tools and keyword extraction. It enables businesses to go beyond basic stats and uncover actionable insights to improve customer satisfaction, product development, and marketing. Easy to use, even for non-techies, this text analysis tool is a key to turning words into results.

Key Features

• Sentiment Analysis: Shows positive, negative, and neutral sentiments and even filters by sentiment to identify pain points
• Word Cloud and Visualization: This text analysis software uses technology to identify the most frequently used words and phrases with a customized word cloud. 
• Tagging: This tool also lets you tag the responses and add sub-tags for subtext

4. QuestionPro

QuestionPro, a robust form builder software, helps transform your boring surveys into vibrant conversations, revealing the true voices and emotions behind the click-throughs. It's not just a survey platform; it's a whisper translator, bringing the nuances behind open-ended responses to life and amplifying them into actionable insights.

Key Features

• Data Collection: Effortlessly collect feedback through conversational surveys. 
• Text Parsing and Transformation: Automatically clean and prepare text for accurate analysis.
• Data Segregation: Ensure high-quality data by identifying and managing incomplete or repetitive responses.
• Text Analysis: Uncover hidden patterns and insights using automated text mining algorithms.
• Ontology Management: Connect existing knowledge repositories for richer insights and faster analysis.
• Sentiment Analysis: Understand customer sentiment and brand perception through opinion classification.

5. MonkeyLearn

MonkeyLearn is a machine learning tool that provides businesses with pre-defined text analysis models and customizable classifiers and extractors for sentiment analysis, keyword extraction, intent analysis & classification, and language detection. MonkeyLearn is a powerful tool that enables businesses to analyze large amounts of textual data, including user feedback, reviews, social media interactions, chat conversations, and surveys.

It offers a variety of text analysis capabilities to help companies understand their customer base better.

Key Features

• Sentiment Analysis: Hear the true roar of your audience, understanding their emotions and opinions hidden within their words.
• Keyword Extractor: Discover the golden nuggets of meaning, identifying the most relevant keywords and phrases shaping your data.
• Topic Modeling: Uncover the hidden storylines, automatically clustering ideas and themes to reveal the narrative within your text.
• Entity Recognition: Spot the key players – names, locations, organizations – and unlock the relationships that matter.
• Customizable Workflows: Build your own text analysis adventure, chaining different tools together to unearth specific insights

6. SurveySensum

SurveySensum’s text analytics capability allows businesses to understand the top reason behind any type of customer complaint, their issues, and opinions. It leverages the power of machine learning to analyze sentiments and opinions from text data received from customers across channels like support tickets, chatbots, surveys, email, social media, etc. 

Key Features 

• Automated Tagging: No more manual tagging! Surveysensum uses AI to categorize feedback by sentiment, topics, and even specific product features, saving you valuable time and effort.
• Real-time Insights: Don't wait for the next report. Get instant alerts on emerging trends, negative sentiment, and key customer concerns, allowing you to respond quickly and effectively.
• Deeper Understanding: Go beyond surface-level sentiment. Uncover hidden patterns, identify root causes of dissatisfaction, and discover unexpected areas for improvement.
• Seamless Integration: Connect Surveysensum with your existing CRM, ticketing system, and analytics tools for a streamlined workflow and holistic view of customer data.

For Academic Research

Text analysis tools for academic research provide scholars with powerful capabilities to analyze vast volumes of textual data. These tools employ natural language processing techniques to uncover patterns, sentiments, and themes within academic literature, research papers, and other textual sources. 

By extracting valuable insights, researchers can gain a deeper understanding of trends, identify key concepts, and enhance their scholarly contributions across various disciplines.

Here are the top tools:

7. NLTK (Natural Language Toolkit)

NLTK, or the Natural Language Toolkit, is a powerful and comprehensive library in Python designed for natural language processing (NLP) and text analysis. Particularly in the context of academic research, NLTK serves as an invaluable tool for scholars and researchers looking to explore, analyze, and extract meaningful insights from textual data.

Key Features

• Text Preprocessing and Tokenization: Allows researchers to break down textual data into individual words or phrases, laying the foundation for more in-depth analysis.
• Part-of-Speech Tagging: Its pre-trained models for part-of-speech tagging enable researchers to understand the syntactic structure of sentences and extract valuable linguistic information.
• Collocation Analysis: NLTK facilitates the analysis of word concordances and collocations, helping researchers identify patterns and relationships between words in a text.
• Linguistic Capabilities: Whether you're delving into sentiment analysis, exploring lexical semantics, or crafting custom language models, NLTK provides the building blocks, from statistical algorithms to machine learning frameworks.

8. Canvs AI

Canvs AI is a powerful text analysis tool that is loved by researchers to discover valuable insights from open-ended text. Powered by artificial intelligence and natural language processing, it provides an accurate analysis of unstructured data and organizes the same based on emotions, themes, and topics. 

Key Features

• Advanced AI automation: The tool analyzes text to classify and categorize its sentiments and meaning.
• Generative AI Story Assist Co-pilot: Not only does it help in finding connections between words and text, it also has generative AI that can help researchers complete their reports. 

9. Forsta

Employing Genius Text Analytics, Forsta is an advanced text analysis tool for academic research. It comprehensively analyzes chat logs, call records, emails, social media, and survey responses. Featuring 12-emotion segmentation and AI-powered categorization, Forsta combines AI and Human NLP techniques to efficiently organize, structure, and categorize text across various sources, enhancing research insights.

Key Features

• AI-powered text analysis: Leverage cutting-edge machine learning to extract themes, entities, and emotions, uncovering hidden connections and shedding light on previously elusive nuances.
• Sentiment and Opinion Mining: Delve into the emotional tapestry of your data, understanding attitudes, beliefs, and motivations with precision and depth with sentiment and opinion mining.
• Automatic Data Cleaning and Organization: No more drowning in unstructured data! Forsta streamlines your workflow by automatically parsing, categorizing, and cleaning your text, minimizing tedious manual work.

10. Voyant Tools: Free Text Analysis Tool

Voyant Tools is widely used by academicians and researchers to read through their text and get a better understanding of what it means and conveys. It reads all types of text data fed into it and gives a summary with vocabulary density, readability index, frequently used words, context, key phrases, bubbliness of the text, and collocates. 

Key Features

• Visual Storytelling: Transform dry data into captivating visualizations, from word clouds that swirl with thematic weight to scatter plots that reveal hidden connections
• Interactive Exploration: Drill down, pivot, and filter your data with ease, crafting a personalized journey through your text. No coding is required, just curiosity and a click!
• Linguistic Playground: Delve into the heart of language with tools like stemming, lemmatization, and part-of-speech tagging, unlocking the deeper meaning within your text.

For Social Media Analysis

Text analysis tools for social media analysis empower businesses to extract meaningful insights from the vast amount of textual data generated on platforms like Twitter, Facebook, and Instagram. These tools employ sentiment analysis, keyword extraction, and trend identification to gauge public sentiment, track brand mentions, and uncover valuable market insights.

Businesses can make data-driven decisions, enhance brand perception, and engage effectively with their target audience.

Here are some of the major tools in this category:

11. Sprout Social

Sprout Social is a powerful social listening tool that helps you understand what people are saying about your brand online. It can help you track brand sentiment, identify trends, and measure the effectiveness of your social media campaigns. Sprout Social also provides tools for community management, campaign optimization, and crisis management.

Key Features

• Sentiment Analysis: Delve deeper than surface emotions. Understand the true feelings behind every tweet, post, and comment, pinpointing areas of praise, frustration, and everything in between.
• Brand Tracking: See how your brand fares in the social sphere. Gauge brand sentiment, monitor competitor activity, and identify influential voices shaping the conversation.
• Industry Trends: Tap into the pulse of your industry. Discover emerging trends, track conversations around key topics, and stay ahead of the curve.

12. Hootsuite

Hootsuite is a popular social media monitoring software that allows businesses to analyze the text information offered in any mention. Powered by Brandwatch, this tool automatically monitors social media sentiments. 

Key Features

• Sentiments Revealed: Hootsuite's advanced sentiment analysis pinpoints areas of praise, frustration, and everything in between, helping you nurture positive feelings and address concerns proactively.
• Brand Resonance Amplified: Track how your brand echoes in the social sphere. Monitor brand mentions, analyze competitor activity, and identify influential voices shaping the conversation. Stay ahead of the curve and ensure your brand resonates with the right audience.
• AI Analytics: Detects the reason behind sudden change in any emotion or sentiments towards your brand

13. Brand24

Brand24 is a leading AI social listening tool that analyzes all types of textual data received from social media. It ensures that brands are always up-to-date with every mention they’ve received and know the exact sentiment behind that mention. Its AI-powered reports offer personalized suggestions and crucial insights for decision-making. 

Key Features

• Identify Key Events: It analyzes online conversation around the brand in real-time and offers instant update on key trends, brand milestones, and even emergencies that requires instant action. 
• Personalized Recommendations: It is powered by GPT which gives personalized recommendations to help brands make impactful decisions. 
• Smart AI Reports: This text analysis tool offers insights into trends and correlations to help tackle any potential challenge.

For Business Intelligence

Text analysis tools for business intelligence transform unstructured textual data into actionable insights, providing a comprehensive understanding of market trends, customer sentiments, and competitive landscapes. Leveraging natural language processing, these tools extract valuable information from sources like customer feedback, reviews, and social media.

Businesses can make informed decisions, optimize strategies and gain a competitive edge in their industry by harnessing the power of text analysis for business intelligence. 

These are the major tools:

14. Lexalytics

Lexalytics is a leading text analysis tool that specializes in business intelligence, providing advanced natural language processing (NLP) capabilities to extract valuable insights from unstructured text data. Tailored for business applications, Lexalytics employs sophisticated algorithms and machine learning techniques to analyze vast amounts of textual information, transforming it into actionable intelligence.

Key Features

• Sentiment, Entity, and Theme Extraction: Lexalytics excels in sentiment analysis, entity extraction, and theme extraction. 
• Customizable Taxonomies: Users can create custom taxonomies and categorization models tailored to specific business domains.
• Integrations with BI Platforms: Lexalytics seamlessly integrates with various business intelligence (BI) platforms, enhancing data visualization and analytics workflows.

15. SAS Visual Text Analytics

SAS Visual Text Analytics is a powerful tool specializing in text analysis for business intelligence within the SAS suite of analytics solutions. It is designed to help organizations extract valuable insights and knowledge from unstructured text data, enabling informed decision-making. 

Key Features

• Unstructured Data Processing: SAS Visual Text Analytics specializes in processing unstructured text data, such as social media content, customer reviews, and news articles.
• Linguistic Analysis and Sentiment Detection: The text mining software employs advanced linguistic analysis to understand the meaning and context of words, phrases, and sentences.
• Integration with SAS Business Intelligence Solutions: SAS Visual Text Analytics seamlessly integrates with other SAS Business Intelligence solutions. This integration allows users to combine insights derived from text analysis with structured data analytics, providing a comprehensive view of business intelligence.

Other Text Analysis Tools For General Purposes

16. Talkwalker

Talkwalker is a powerful social media analytics platform with text analysis features. It excels in monitoring brand mentions, sentiment analysis, trend identification, and competitive intelligence across various social media platforms. Businesses leverage Talkwalker to extract actionable insights, manage online reputation, and stay informed about industry trends through advanced text analysis.

17. IBM Watson Natural Language Understanding

IBM Watson Natural Language Understanding is a robust tool that employs advanced natural language processing techniques. It can analyze text for sentiment, entities, concepts, emotions, and more. The tool is widely used for extracting valuable insights from unstructured text data, making it a versatile choice for various applications.

18. Google Cloud Natural Language API

Google Cloud Natural Language API is a cloud-based solution offering a suite of text analysis capabilities. It provides sentiment analysis, entity recognition, syntax analysis, and content classification. Leveraging Google's machine learning models, this API allows developers to integrate powerful text analysis features into their applications and services.

19. Microsoft Azure Text Analytics

Microsoft Azure Text Analytics is part of the Azure Cognitive Services, offering a range of text analysis functionalities. It includes sentiment analysis, key phrase extraction, entity recognition, language detection, and named entity recognition. The tool is designed to extract meaningful information from text data, making it suitable for applications in sentiment analysis, social media monitoring, and more.

20. Amazon Comprehend

Amazon Comprehend is a natural language processing service by Amazon Web Services. It provides a range of text analysis capabilities, including sentiment analysis, entity recognition, key phrase extraction, language detection, and topic modeling. With its easy-to-use API, developers can integrate Amazon Comprehend into applications for efficient text analysis tasks.

How to Choose a Text Analytics Tool for your Business?

When it comes to choosing a text analytics tool, there are several factors that one needs to keep in mind. What’s the main purpose of analyzing the text, the kind of data one wants to decipher, and 

Choosing the right text analytics tool for your business can feel overwhelming, but don't worry, this article is here for you. To navigate this process effectively, let's break it down into steps:

#Step 1. Define your Goals and Needs

The first step to choosing text analytics software is to define what specific business problems are you hoping to solve with text analytics.

• Are you aiming to improve customer sentiment, analyze market trends, optimize marketing campaigns, or something else?

Once you have the answer to this, you can shortlist the tools based on their use cases. 

Next, you need to assess the type of text data that you will be analyzing with the software.

• Will these be social media posts, customer reviews, survey responses, internal documents, or a combination of unstructured/structured data?

Further, you also need to know the level of technical expertise your team possesses in terms of NLP and AI. Based on this, it would be easier for you to choose a tool. 

#Step 2. Explore your options

Once you have defined your goals and understood the objective of choosing a text analysis software, the next step is to start exploring the options. 

• General-purpose tools: These offer a wide range of text analysis features like sentiment analysis, topic modeling, keyword extraction, and NER. Examples include MonkeyLearn, MeaningCloud, and Google Cloud Natural Language API.
• Specialized tools: These focus on specific use cases like social media analysis (Brand24, Sprout Social), customer feedback analysis (Qualtrics Text iQ, Lexalytics Semantria), or market intelligence (Aylien, Meltwater).
• BI integration tools: These seamlessly integrate with your existing BI platform and offer text analysis capabilities. Examples include Tableau Prep, Qlik Sense, and Microsoft Power BI.

#Step 3. Evaluate and compare tools

Once you have shortlisted the text analytics tools based on your goals and objectives, you should now consider:  

• Features and functionality: Does the tool offer the specific features you need for your use case?
• Ease of use and user interface: Is the tool user-friendly and accessible for your team?
• Data security and privacy: Does the tool meet your data security and privacy requirements?
• Scalability and cost: Choose a tool that can handle your current data volume and fits your budget.
• Free trials and demos: Take advantage of free trials and demos to test out the tools and see which one feels right.

#Step 4. Additional Tips

Here are some additional tips that you can consider while choosing your text analysis tools:

• Seek expert advice: Consult with data analysts or NLP specialists within your company or network for recommendations.
• Start small and scale up: Begin with a pilot project using a smaller dataset and gradually expand as you gain confidence and experience.
• Focus on data quality: Ensure your text data is clean and accurate before feeding it into your chosen tool.
• Monitor and iterate: Regularly evaluate the results of your text analysis and adjust your approach as needed.

Remember, there's no one-size-fits-all solution, and the best text analytics tool for your business is the one that aligns with your specific needs and goals.

By following these steps and considering the factors mentioned above, you can make an informed decision and unlock the valuable insights hidden within your text data.

Analyze your Text with Zonka Feedback

Zonka Feedback offers a powerful AI-driven text and sentiment analysis engine that helps you drive meaning from unstructured text data. It helps you capture customer feedback via different survey channels including emails, SMS, website, in-product, in-app, survey app, QR codes, offline surveys, kiosk surveys, and more. 

This AI survey tool offers advanced reporting features that provide a complete analysis of not just the scores for your CSAT surveys, NPS surveys, CES surveys, or analyze the responses to generate in-depth reports but also analyze the open-text feedback to gather insights from unstructured data. 

You can sign up with Zonka Feedback for a free 14-day trial or schedule a demo to understand the tool better.