Top 9 Text Mining and Analytics Tools Businesses Should Try – SamaGame (2023)

Top 9 Text Mining and Analytics Tools Businesses Should Try.

For any business to sustain itself in this era, it is imperative to obtain vital data about its customers and other stakeholders through text analytics.

When there is no shortage of structured and unstructured data about an organization, it is of no use unless you can analyze it to gain insights for decision making.

This is where mining and text analysis tools come into play. Text analysis software can locate patterns and trends from raw text data and provide you with statistical patterns.

Before going into details about text analytics tools, let’s understand text analytics technology and its uses.

What is text analysis and mining?

Text analysis refers to the process of gathering meaningful information from raw text data. It means extracting user sentiment and valuable data from customer reviews and feedback to make informed decisions.

Text analysis is a general term used to refer to actions that include text extraction, identification, categorization, analysis, entity-relationship modeling, and grouping.

Although data analysis and data extraction come from different streams of studies, these terms are used interchangeably today, as both refer to the collection of data using various statistical approaches.

Text analytics provides qualitative insights into customer feedback by identifying sentiment in any free-form text. On the other hand, you will see the uses of Machine Learning and NLP technology in text mining to gather insights from structured data.

Mining and Text Analysis Software Use Cases

You will find the use of text analysis tools in the following cases:

1. Quick Interpretation of Large Documents

These tools are typically used to interpret unstructured data from documents such as emails, chats, social media, messages, and reviews. While manual analysis can take months to analyze a large volume of documents, text analysis software can do it in an hour.

2. Real-time customer review monitor

Customer comments and reviews can appear anywhere on the Internet. Text analytics software can monitor comments 24/7 and take necessary action against negative reviews and posts.

3. Understand employee feedback

Companies also use text mining tools to improve organizational strategy by checking employee feedback and understanding their complaints.

Take a look at the list of the best text analysis tools:

Amazon understands

is a text analysis tool that can get valuable information from documents through mining and analysis. It uses machine learning technology to discover valuable information and connections in the text.

Some of the main attributes of this platform are language detection, keyword extraction, sentiment analysis, topic modeling, and syntax analysis. You can use it to analyze documents, product reviews, customer support tickets, emails, and social platforms.

Using this platform will simplify your document processing workflows. It tightly regulates access to your documents through Personally Identifiable Information.

Running this tool is very easy: even without previous experience, you can start using it in a few minutes. Organizations using different AWS services can seamlessly integrate this tool into their workflow.

Thematic

For any customer-facing business, analyzing customer feedback and support data is crucial. is text analytics software that provides a central, collaborative space to connect and understand customer feedback.

It allows you to check the value of feedback and get valuable information in near real time. Using the word processing AI of this tool, fast-growing businesses can locate recurring themes in customer feedback data.

Thematic uses cutting-edge sentiment analysis technology to turn unstructured customer feedback into valuable insights.

Apart from these, the software also analyzes the impact of the data on your metrics and presents the analysis report through simple infographics.

Supports one-click integration with popular customer surveys and support apps like SurveyMonkey, Discourse, Zendesk, Trustpilot, and Medallia to collect data from online reviews, support chat, and surveys.

google cloud

is the ideal text analysis platform for companies looking for a service that is compatible with Google Cloud Storage. It also supports integration with Google Workspace apps.

This tool uses Google’s machine learning technology to get plain text information. Organizations can use it for content classification, sentiment analysis, entity extraction, and syntax analysis.

You can search and tag fields in documents like chats, emails, and social media posts with this software through entity analysis. It also allows you to understand customer opinions through sentiment analysis.

In addition to information extraction, the app also offers features like parsing and storing text. You can also locate domain-specific entities within documents by extracting custom entities.

quackery

is a text analysis tool that uses artificial intelligence to ensure the growth of your company and the loyalty of your customers. Collect data from multiple sources of customer feedback and interaction in an easy-to-use collaborative platform.

To ensure that, Chattermill supports integration with Trustpilot, Typeform, Google Play, App Store, SurveyMonkey, Slack, Ask Nicely, Survey Gizmo, Reviews.io, Zendesk, and many more apps.

It uses theme and sentiment AI to understand customer sentiment about your product and brand while finding the reason behind recurring themes. After signal analysis, you can perfectly identify and predict ways to generate revenue and retain customers from each touch point.

Businesses can use this tool to process content in all major languages, including English, French, Spanish, German, Russian, Arabic, and Mandarin.

it is mainly popular among researchers in the humanities stream. However, you can also use it as a website text analysis tool. This platform has an easy interface and performs different analytical tasks.

You can use its functions to visualize the data that arises from the analysis of the website. But, it is not possible to use it for in-depth text analysis.

MonkeyLearn

Do you want to use some highly customizable SaaS text analytics software that you can easily integrate with your existing tools? If yes, it should be your go-to platform for quantitative content analysis.

It is robust text mining software that can analyze any type of unstructured text data, including text documents, online reviews, survey responses, customer feedback, and social media conversations.

Thanks to sophisticated Machine Learning algorithms and Natural Language Processing (NLP), this platform will offer you accurate text analysis.

If you use MonkeyLearn for text mining, you can integrate it with applications like Google Sheets, Microsoft Excel, Zendesk, Google Forms, Airtable, HelpScout, and Zapier.

This web-based software comes with useful attributes like sentiment analysis, keyword extraction, NPS comment analysis, and email response ranking.

Keatext

When it comes to choosing a customer experience tool to analyze unstructured data from numerous sources, it’s the tool for you. If you are part of a non-profit organization or university, it even offers you a free version.

Whether you have social media conversations, emails, or surveys to analyze, this cloud-based text analytics software can do it effectively using machine learning and artificial intelligence.

Now, you can get rid of the tedious task of manually analyzing data and let Keatext tell you where to put your attention if you want to improve your customer experience.

In addition to the features mentioned above, this tool also allows you to collect feedback in multiple languages ​​and visualize data in different ways.

WordStat

Are you looking for some text analysis software that can process a large amount of unstructured information with high precision? Use a text analysis tool that is simple and flexible.

It can process 25 million words per minute to extract themes and identify patterns. Examine documents to quickly extract themes and trends, and accurately perform quantitative content analysis.

Additionally, you can use this to analyze open responses, generate business intelligence data, examine news coverage, and detect fraud.

It is also compatible with other different tools. When you use them together through integration, you enjoy world-class flexibility in terms of parsing text and relating it to numeric and categorical data.

RapidMiner

If you think data is just numbers and figures, you’re here to prove you wrong. It is an advanced text mining tool with which you can perform operations and model deployments. It uses artificial intelligence to perform text analysis and text analysis to gather information that will benefit your business.

This insight you’ll gain from qualitative and textual content will help you improve in various industries, including product development, marketing, and risk management.

Some of the rich sources of plain text are online reviews, patent applications, research journals, social media, call center transcripts, and claim forms.

RapidMiner informs you about the attitude of customers towards your products and services, so that your business can advance and achieve the organizational mission.

conclusion

Text analysis tools can help you analyze text data from emails, social platforms, online reviews, and large online documents. Businesses can also use these apps to get an accurate idea about public sentiment and perception of their brand or product.

Since the insights gathered from text mining software are essential for making better business decisions, more and more organizations are taking an interest in it.

Whether you want to extract keywords, analyze sentiment, or perform entity extraction, you’ll find several text analysis tools on the market for these tasks.

In this article, we have discussed some of the best text analysis tools in the text analysis and mining software industry. You can choose one or more from the list according to your needs.

If you want to build your own text analysis software, you might want to try any of these low-code or no-code platforms.

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