Your Guide to User-Friendly Text Analysis Software

Text analysis, or text mining, uses natural language processing (NLP) to analyze, process, and sort unstructured information. Powered by machine learning, text analysis software can scan text to pull simple data points, like names and phone numbers, as well as sort data into categories. It can save huge amounts of time by automatically analyzing data in minutes that would normally require dozens of employees.

Text analysis can be useful to classify emails in order of urgency, organize social media comments by  sentiment, sort customer support tickets by topic, and much more. 

Take Twitter data, for example. Five-hundred million tweets are sent every day – imagine having access to all that data! With text mining tools, you can pull tweets relevant to your company on a regular basis (in real time), and classify each one in a matter of minutes. You might discover locations where you’re trending, how users are reacting to new products, if customers are happy with your customer service, and many other insights. 

There are a number of powerful text analysis tools on the market. Read on to learn more about popular software that brands are already using to transform their business.

Best Text Analysis Software

There are endless open-source and software as a service options that use natural language processing (NLP) to analyze and classify your text.

Open-source tools, like Keatext, KNIME, and Refinitiv, can be very useful for seasoned coders. But SaaS options are often better for companies that don’t want to build infrastructures from scratch, something that can require whole teams of devs. The tools we’ve listed below can be used with little to no coding.

MonkeyLearn

Best for: Medium and large SaaS, software, and E-commerce companies who want to turn customer data into actionable insights.

MonkeyLearn allows customers to train and customize text analysis models in a matter of minutes and is easily integrated with the applications and software you already use: Excel, Google Sheets, Zapier, Zendesk, and more.

MonkeyLearn offers pre-trained models for text extraction and text classification that you can try for free. And if you need a model tailored directly to your needs, you can train your own text analysis model. No coding necessary. The more you train your model, the more accurately it will analyze text and  detect emotions, topics, irony, intents, and more.

MonkeyLearn also offers APIs in all major programming languages, so you can seamlessly connect MonkeyLearn’s models to the tools you already use. 

Pricing: MonkeyLearn offers a free plan with up to 300 queries/month, and paid plans start at $299 USD per month.

RapidMiner

Best for: Small to large companies that want to break down structured or unstructured data to create predictive models.

RapidMiner’s Turbo Prep allows users to easily prepare data and evaluate it for quality, soundness, and depth. Common defects, like missing values and anomalies, can be fixed easily and multiple data sets blended for more thorough analysis. 

Once the data is prepped, use RapidMiner Studio and Auto Model to create predictive models, or you can simply export to third-party apps, like Excel.

Pricing: RapidMiner Studio plans start at $7,500 per year.

Google Cloud NLP

Best for: Companies looking for a managed service for advanced model building and easy integration with Google Cloud Storage.

Google Cloud NLP offers both AutoML Natural Language and Natural Language API, so you can choose what’s best for you. And with many companies and individuals using Google Cloud Storage to some degree, it can be super easy to integrate with existing data and texts.

Google’s AutoML technology has proven to be one of the most advanced for producing high-quality models that you can train for unique use cases, using your own data and with relative ease and limited ML expertise.

Pricing: Google Cloud NLP offers a free plan, and prices vary depending on the number of features you use. 

Amazon Comprehend

Best for: Companies that require advanced text extraction and sometimes lower-level analysis of huge amounts of data with a user-friendly interface – some programming required.

Amazon Comprehend presents pre-trained APIs that integrate smoothly and efficiently into your existing applications to perform keyphrase extraction, sentiment analysis, entity recognition, topic modeling, and language detection. 

Amazon Comprehend is administered and supervised by Amazon, so there is no need for in-house servers and no need to build and train models. However, if you’re in need of a more tailored model, you can use AutoML to build custom models and extractors.

Pricing: Amazon Comprehend is a pay-for-what-you-use platform that charges based on the amount of text processed.

Microsoft Azure

Best for: Multinational companies. Although also available on premise, Microsoft Azure’s strength is their worldwide regional cloud coverage.

Microsoft Azure’s Stream Analytics is a serverless, real-time processing service designed for huge workloads and custom-built analytics.

Azure Resource Manager allows you to tailor models and move existing models to Azure Analysis Services to make full use of the scale, flexibility, and organization perks of the cloud. 

Microsoft Azure is extremely fast and responsive. It provides for end-to-end analytics that can be configured in minutes with custom code.

Pricing: Microsoft Azure’s standard plan starts at $99 a month.

Lexalytics

Best for: Companies that require secure, on-premise NLP analysis of sensitive data.

Lexalytics offers their flagship software, Salience, on Microsoft Windows and Linux servers for customers that require the extra security of retaining all of their data in-house.

Salience allows for full customization, so that customers can run analytics on a variety of data structures, while offering native compliance with most data security and privacy regulations. 

Salience’s analytics libraries can integrate simply with a number of applications to perform sentiment analysis, named entity extraction, theme extraction, categorization, intent analysis, summarization, tokenization, part-of-speech tagging, and language recognition.

Pricing: Variable. Schedule a demo to find out more.

AYLIEN

Best for: Small to large companies that want to analyze news data and create custom analytic frameworks.

Although coding is necessary, AYLIEN offers three APIs that can be set up in minutes with their SDKs offered in seven major programming languages.

AYLIEN’s News API allows users to search and analyze news content in real time from around the globe. Thousands of news sources are indexed and analyzed daily.

Their Text Analysis API performs numerous NLP processing duties on documents, online reviews, social media comments, and other forms of text.

Finally, AYLIEN’s Text Analysis Platform (TAP) allows users to build custom NLP models in minutes. Create, train, and use your model directly from your browser.

Pricing: Aylien offers a 14-day free trial for each plan, and premium plans start at $199 a month.

IBM Watson

Best for: Larger companies, with the ability to write code, that require advanced text and speech-to-text analytics.

IBM Watson offers a fleet of tools for text analysis across a multitude of industries. IBM Watson Studio assists analysts with data preparation and model building at scale across any cloud. 

With Natural Language Classifier, developers can build advanced models by simply uploading training data from a CSV file – no data science or machine learning background required.

Watson Personality Insights and Watson Tone Analyzer provide powerful tools for understanding complex human feelings and reactions that may otherwise be missed.

And with Watson Speech-to-Text you can start listening to the voice of customer (VoC) by converting audio conversations to text for quick analysis.

Pricing: Includes a free plan. Premium plans depend on the number of predictions needed. 

QDA Miner

Best for: Coding researchers who need to organize, annotate, and retrieve data from large collections of documents.

QDA Miner from Provalis Research is used by healthcare and law professionals, librarians, business analysts, and fraud detection experts who need to classify and organize books, documents, and images to perform qualitative data analysis.

QDA Miner offers on-screen coding and text and image annotation with interactive code searching and code splitting and merging.

Pricing: QDA Miner 5 commercial software package is $2,595 with a $1,063 annual lease.

Chattermill

Best for: Businesses that want to track and analyze customer feedback for actionable insights.

Chattermill offers AI-driven evaluations of customer feedback within every aspect of the customer experience, to give a thorough view “of the entire customer journey.” Their overall goal is to anticipate your customers’ needs.

Analyze feedback in real time; set custom alerts, so you won’t miss important changes in metrics. Chattermill helps you understand the meanings of your KPIs with themes and sentiment analysis, all demonstrated visually to give a holistic view of what your data actually means. 

Pricing: Based on individual use. Contact for more info.

What Software Works for Your Business?

Text analysis can help any business increase productivity, saving hundreds of employee hours, and help you focus on the things that matter to your company.

There are many ready-to-use tools that you can take advantage of to get started with text analysis right away. 

Do you need an extremely user-friendly version that you can simply plug in, with no coding required? Do you need to create highly advanced models that may take some time to train? Is data security crucial to your company? Now that you’ve learned a bit about the different kinds of text analysis software, it’s time to decide which is best for you. 

Want to give text analysis software a try for free? Sign up now to MonkeyLearn and get started right away – no coding required (but you certainly can use it if you’d like).

Rachel Wolff

Rachel Wolff

BA in journalism and French from Sheffield University. Interested in human-machine collaboration and Google's ever-changing algorithms.

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