Your business is sitting on a goldmine of unstructured data – from customer reviews to social media posts. But traditional tools can’t help you dig deeper.
Text analytics software, powered by advanced natural language processing (NLP), is your key to unlocking game-changing insights from a wide range of unstructured text documents, including emails, chat, and social media, in 2024.
We’ve handpicked the best text analytics tools that will help you:
Understand customer sentiment and opinions
Identify key themes and patterns
Make data-driven decisions with ease
Discover how industry leaders are already harnessing the power of text analytics to stay ahead of the curve.
Let’s explore the top solutions and find the perfect fit for your business.
Overcoming the Challenges of Unstructured Data Analysis
Unstructured data holds valuable insights but is difficult to analyze with traditional tools. Text analytics software uses natural language processing (NLP) to effectively process unstructured data. Choosing the right text analytics software is crucial for unlocking the full potential of your data. Analyzing customer data, including feedback, reviews, and surveys, is essential for unlocking valuable insights and improving customer experiences.
The Importance of Analyzing Unstructured Data
In today's digital age, businesses generate an enormous amount of unstructured data from various sources, including emails, social media posts, customer reviews, and support tickets. This data contains valuable insights that can help you make informed decisions, improve customer experience, and gain a competitive edge. However, traditional data analysis tools often struggle to process and analyze unstructured data effectively, leaving these insights untapped.
According to a study by IDC, unstructured data is growing at a compound annual growth rate (CAGR) of 21.2% per year, and by 2025, it will account for over 80% of all data generated worldwide. This rapid growth highlights the need for businesses to adopt advanced text analytics solutions that can handle the complexity and volume of unstructured data.
The Challenges of Unstructured Data Analysis
Unstructured data poses several challenges for organizations:
Lack of structure: Unlike structured data, which follows a predefined format and can be easily analyzed using traditional tools, unstructured data lacks a consistent structure, making it difficult to extract meaningful insights.
Volume and variety: The sheer volume and variety of unstructured data can be overwhelming for businesses to process and analyze manually or with basic tools.
Ambiguity and context: Unstructured data often contains ambiguous language, sarcasm, and context-specific information that can be challenging for machines to interpret accurately.
The Power of Sentiment Analysis in Text Analytics Software
Text analytics software, powered by natural language processing (NLP), offers a solution to the challenges of unstructured data analysis. NLP is a branch of artificial intelligence that enables machines to understand, interpret, and generate human language. By leveraging NLP techniques, text analytics software can automatically process and analyze large volumes of unstructured data, extracting valuable insights and patterns.
Some key capabilities of text analytics software include:
Sentiment analysis: Determining the overall sentiment (positive, negative, or neutral) expressed in a piece of text, helping businesses gauge customer opinions and emotions.
Topic extraction: Identifying the main topics and themes discussed in a collection of documents, enabling organizations to understand the key issues and trends.
Named entity recognition: Extracting and categorizing named entities, such as people, organizations, and locations, from unstructured text, allowing for more targeted analysis.
Text classification: Automatically categorizing documents into predefined categories or tags, streamlining content organization and analysis.
Choosing the Right Text Analytics Software
With numerous text analytics solutions available in the market, selecting the right one for your organization can be challenging.
To evaluate text analytics software, consider the following factors:
Accuracy and performance: Look for software that demonstrates high accuracy in processing and analyzing unstructured data, as well as the ability to handle large volumes of data efficiently.
Ease of use and integration: Choose a solution that offers a user-friendly interface and seamless integration with your existing data sources and business applications.
Customization and scalability: Ensure that the software can be customized to meet your specific business requirements and can scale as your data volume and analysis needs grow.
Support and resources: Consider the level of support, documentation, and resources provided by the vendor to help you successfully implement and utilize the software.
By selecting the right text analytics software, you can unlock the full potential of your unstructured data, drive informed decision-making, and improve overall performance.
Top Text Analytics Software for 2024
In 2024, businesses are faced with an ever-growing amount of unstructured data.
Everything from customer reviews, to social media, and emails are valuable data sources. To make sense of this data and gain valuable insights, you need to pick the right text analytics software.
Below we’ve pulled together a list of the top text analysis tools available. All offer powerful features to help you extract meaningful information from unstructured data.
By the end of this article, you’ll have a clear understanding of which text analytics software best suits your organization’s needs in 2024.
Additionally, for businesses seeking a more tailored approach, creating your own text analysis tools using open-source libraries or low-code platforms can be a viable option. This allows for customization to meet specific business needs, enhancing the accuracy and relevance of the insights gained.
1. Kapiche
Kapiche is a leading text analytics platform designed to help businesses make sense of unstructured data and gain actionable insights. It's ideal for organizations seeking to improve customer experience, enhance product development, and drive data-informed decision-making.
Key features:
Advanced sentiment analysis
Customizable analytics dashboards
AI-powered insights generation
Pros & Cons
Pros: Kapiche has robust sentiment analysis capabilities, a user-friendly interface, and customizable dashboards for tailored insights. Kapiche does not charge by volume, so you can analyze everything your customers are saying as your volume of data increases.
Cons: It may have higher pricing for advanced features, depending on your needs. For beginners to text analysis tools, it may be a steeper learning curve.
Pricing
Business Plan: $2,650/month for up to 500,000 data rows
Enterprise Plan: Custom pricing for larger volumes and additional features
2. MonkeyLearn
MonkeyLearn offers a range of text analysis tools powered by machine learning to extract meaningful data from text sources. It's well-suited for businesses looking to automate repetitive tasks such as categorizing customer feedback, analyzing social media sentiment, and processing emails.
Key features:
Text classification
Named entity recognition
Sentiment analysis APIs
Pros & Cons
Pros: It has easy-to-use API integrations, is scalable for large datasets, and offers seamless integration with existing workflows.
Cons: Limited customization options, and advanced features are available only in higher tiers. It operates with volume-based pricing, so you'll have to pay more in analyzing more data.
Pricing
MonkeyLearn API: $299/month with 10k queries/month.
MonkeyLearn Studio: contact MonkeyLearn for pricing.
A free Academic plan is available for educational use.
3. Lexalytics
Lexalytics provides cloud-based text analytics solutions leveraging natural language processing (NLP) and machine learning capabilities. It's ideal for enterprises requiring deep text analysis for social media monitoring, market research, and voice of customer (VoC) analytics.
Key features:
Entity extraction
Intent analysis
Multi-language support
Pros & Cons
Pros: It has comprehensive NLP capabilities, accurate sentiment analysis, and robust multi-language support.
Cons: Higher pricing tiers for advanced features, deeply technical and limited customization in basic plans.
Pricing
Enterprise: Contact for pricing
4. IBM Watson Natural Language Understanding
IBM Watson NLU is an AI-powered text analytics tool that offers advanced NLP capabilities for extracting insights from unstructured data. It's well-suited for enterprises requiring deep linguistic analysis, entity recognition, and sentiment analysis across multiple languages.
Key features:
Language detection
Syntax analysis
Concept extraction
Pros & Cons
Pros: It has strong language support and accuracy, scalable for very large-scale data processing, and a seamless integration with IBM Cloud ecosystem.
Cons: It is on the more costly side for advanced features, and requires technical expertise for set up and customization and in many cases, day-to-day use.
Pricing
Standard: supports more than 5M items/month starting at USD 0.003 per item.
Enterprise: Contact for pricing.
5. RapidMiner
RapidMiner offers a comprehensive data science platform with text analytics capabilities for extracting insights from textual data sources. Ideal for data scientists and analysts seeking a unified platform for data preparation, modeling, and analysis, including text data.
Key features:
Text mining workflows
Predictive modeling
Visual analytics
Pros & Cons
Pros: It has an intuitive visual interface, end-to-end data science capabilities, and is scalable for big data environments.
Cons: more of a learning curve for beginners.
Pricing
Professional: $7,500 per user per month
Enterprise: $15,000 per user per month
AI Hub: $54,000 per user per month
6. Twinword Text Analysis
Twinword offers text analysis APIs and tools powered by AI and machine learning algorithms for extracting insights from text data. Suited for developers and businesses needing customizable text analysis solutions for sentiment analysis, keyword extraction, and topic categorization.
Key features:
Sentiment analysis API
Keyword extractor
Topic tagger
Pros & Cons
Pros: Developer-friendly APIs, pre-trained models for quick deployment, and customizable for specific use cases.
Cons: Limited advanced analytics in basic plans, API rate limits in lower tiers.
Pricing
Pro: $19 monthly on select plans
Ultra: $99 monthly on select plans
Mega: $450 monthly on select plans
7. Luminoso
Luminoso offers AI-powered text analytics solutions for understanding customer feedback, market trends, and user sentiments across various channels. Ideal for businesses seeking real-time insights from customer interactions, social media data, and survey responses to drive decision-making.
Key features:
Interactive dashboards
Trend analysis
Multilingual support
Pros & Cons
Pros: Real-time analytics capabilities, intuitive visualization tools, multilingual sentiment analysis.
Cons: Pricing may be prohibitive for small businesses, customization options limited in lower tiers.
Pricing
Standard: $1,200 per month
8. MeaningCloud
MeaningCloud offers text analytics APIs and tools with a focus on semantic analysis, categorization, and entity recognition for diverse text data sources. Suited for enterprises requiring multilingual text analytics capabilities with industry-specific customization for compliance and regulatory analysis.
Key features:
Semantic analysis APIs
Compliance analysis
Vertical packs for industry-specific insights
Pros & Cons
Pros: Industry-specific text analytics solutions, compliance and regulatory analysis tools, and multilingual support with customizable APIs.
Cons: Higher pricing for industry-specific packs, limited advanced features in basic plans.
Pricing
Personal: $9 per month
Startup: $99 per month
Professional: $399
Business: $999
Enterprise: custom
9. AYLIEN
AYLIEN offers text analysis APIs and tools powered by deep learning for sentiment analysis, entity recognition, and summarization of textual data. Ideal for developers and data scientists needing scalable and customizable text analysis solutions for media monitoring, content analysis, and customer feedback analysis.
Key features:
Summarization API
Entity recognition
Text classification
Pros & Cons
Pros: Deep learning-based text analysis, scalable API infrastructure, customizable for industry-specific use cases.
Cons: Advanced features limited to higher tiers, API rate limits in lower plans.
Pricing
Free trial
Contact for pricing
10. Amazon Comprehend
Amazon Comprehend is a cloud-based text analytics service by AWS offering NLP capabilities for sentiment analysis, key phrase extraction, and language detection. Suited for businesses leveraging AWS cloud infrastructure and seeking scalable and cost-effective text analysis solutions for various use cases.
Key features:
Key phrase extraction
Language detection
Named entity recognition
Pros & Cons
Pros: Scalability with AWS cloud infrastructure, pre-trained models for quick deployment, integration with other AWS services.
Cons: Requires familiarity with AWS ecosystem, pay-per-usage model may be complex for some users to forecast cost accurately.
Pricing
$3 per hour for model training (billed by the second) and $0.50 per month for custom model management
Pay as you go pricing model based on usage
The Verdict
After evaluating each alternative, we found that each has its strengths and is suited for different use cases.
However, for most organizations, Kapiche is a top choice, particularly within the VoC and Customer Experience space, due to its comprehensive feature set, user-friendly interface, and competitive pricing. Its ability to cater to a wide range of industries and use cases makes it the most versatile text analytics solution on the market.
Case Study: Successful Text Analytics Implementation
Discover how real businesses have leveraged text analytics with Kapiche to drive growth
Learn from their challenges and see how text analytics helped them succeed
Improving Customer Satisfaction at RAC WA
Royal Automobile Club of Western Australia (RAC), a leading auto services company, faced challenges with processing their member feedback. They had troves of customer feedback data from reviews, surveys and social media, but struggled to derive actionable insights manually.
Implementing text analysis software allowed them to process vast amounts of unstructured data at scale. Kapiche surfaced trending topics, common phrases, and complaints about specific aspects of their service products. One unexpected discovery was that many customers noted the final wave goodbye after receiving roadside assistance was a moment of delight, leading to highly positive experience scores.
RAC WA used these insights to adjust their service delivery to be even more customer-centric. They are processing data much faster, and are getting to a much more accurate level of insights. They also fast-tracked development of highly requested items identified by the analysis. The change in their data processing approach resulted in generating insights 30x faster, leading to quicker, more impartial decision-making across the business.
Lessons from RAC WA's Journey
Unstructured customer feedback contains a goldmine of insights, but is difficult to analyze manually at scale
Text analytics can surface both known issues and uncover "unknown unknowns"
Acting on insights derived from customer feedback data leads to measurable business impact
From improving customer satisfaction, to optimizing product development and streamlining research, text analysis tools are incredibly powerful for harnessing insights hidden within unstructured data.
Unlock Insights with Kapiche: The Leading Text Analytics Solution
Kapiche is the top choice for text analytics in 2024. It addresses the challenges of unstructured data analysis with its user-friendly interface and powerful features.
Key Features of Kapiche
Advanced natural language processing (NLP) capabilities
Sentiment analysis for understanding customer opinions and emotions
Entity recognition for identifying key people, places, and things
Topic modelling for discovering hidden themes and patterns
Integration with popular data sources and business tools
Benefits of Using Kapiche
Gain valuable insights from unstructured text data
Improve customer understanding and satisfaction
Enhance decision-making with data-driven insights
Save time and resources with automated text analysis
Scale text analysis efforts to handle large volumes of data
Pricing and Plans
Kapiche offers flexible pricing plans to suit businesses of all sizes:
Business Plan: $2,650/month for up to 500,000 data rows
Enterprise Plan: Custom pricing for larger volumes and additional features
Next Steps: Harnessing the Power of Text Analytics
A text analysis tool like Kapiche transforms unstructured data into actionable insights.
By leveraging advanced NLP techniques, you can better understand their customers, improve decision-making, and drive growth.
Is Text Analytics Right for Your Business?
Consider the following questions:
Do you have a significant amount of unstructured text data, such as customer reviews, social media posts, or support tickets?
Are you looking to gain deeper insights into customer sentiment, preferences, and behaviour?
Do you want to automate and scale your text analysis efforts to handle large volumes of data?
If you answered yes to any of these questions, text analytics software could be a valuable addition to your data analysis toolkit.
Getting Started with Kapiche
To experience the benefits of text analytics firsthand, sign up for an on-demand demo of Kapiche. You'll get clarity on all the features available to help your business unlock valuable insights.
Our team of experts is also available to provide guidance and support throughout your text analytics journey. Schedule a call to discuss your specific needs and learn how Kapiche can be tailored to your goals.
