There’s a lot of valuable data buried in social media posts, product reviews, customer support tickets, and online surveys. With text analytics, you can transform all this unstructured text into quantitative data, and visualize the results to reveal insights, trends, and patterns.
How is this different from text analysis (or text mining)? While text analysis helps you process raw data to gain qualitative insights, text analytics goes one step further and translates this into numbers that can tell a story.
More and more companies are adopting text analytics tools to automate routine tasks, get relevant information about customers, and make data-driven decisions. And combining them with data visualization tools to showcase results in a more attractive way
The simplest way to get started with text analytics is by using a SaaS tool like MonkeyLearn. Request a demo to learn more about MonkeyLearn or try out ready-made machine models like this online sentiment analyzer.
Want to find a tool that best suits your needs, available time, budget, and technical expertise? To help you decide, we’ve compiled a list of some of the best text analysis software online, as well as a few visualization tools.
Let’s get started!
MonkeyLearn is a machine learning platform that can help you analyze text easily and quickly. Combining powerful algorithms with a user-friendly interface, this cloud-based solution makes it really simple to gain insights from data.
You can use MonkeyLearn to classify texts by sentiment, topic, intent, and urgency, and to extract relevant information from text, like keywords and entities. If you’d like to start right away, try one of the many pre-trained models available. For a sneak peek, paste some text into this free sentiment classifier and click “Classify text!”.
If you want to improve the accuracy of your model or get predictions tailored to your business’ needs, you’ll need to build a customized model. With MonkeyLearn, you can build, train, and integrate your model in just a few steps – code-free, and no machine learning knowledge necessary.
Easily connect your customized models with third-party apps like Google Sheets, Zendesk, and Zapier via our one-click integrations, or MonkeyLearn’s API (available in all major programming languages).
Aylien is an AI platform offering different solutions to help companies understand large volumes of text. Using its collection of text analysis APIs (with SDKs available in seven languages), developers can easily access ready-made models for tasks like sentiment analysis, text categorization, and entity extraction. No expertise in Natural Language Processing (NLP) is required.
Aylien also offers a text analysis platform to build custom models with NLP and train them with domain-specific data, with access to datasets and a knowledge base.
Finally, Aylien’s News API allows you to track and analyze news articles and information at scale.
IBM Watson offers text analytics tools for different industries, as well as pre-built apps and software for building AI models from scratch.
Watson Natural Language Understanding, for example, comes with a series of pre-built features to find entities, keywords, and concepts in text, as well as to identify sentiment and emotions (like sadness, joy, or fear).
On the other hand, developers can use different Watson APIs to build custom models and integrate them into their existing apps, without needing to have a machine learning background.
Watson Natural Language Classifier enables you to train custom classification models, while Watson Tone Analyzer uncovers emotions in online conversations, and Watson Personality Insights helps you segment customers.
Thematic provides AI-based solutions to gain insights from customer feedback.
The platform offers three different tools: Thematic Intelligence, which helps understand the meaning of texts by identifying topics; Thematic Insights, which examines trends, relationships, and patterns in data; and Thematic Catalyst, which allows you to create data visualizations.
You can easily integrate Thematic with the tools you use, to easily collect and process customer feedback like reviews, responses to NPS surveys, and employee feedback.
Google Cloud NLP allows you to gain valuable insights from unstructured data, using machine learning.
With the Natural Language API, developers can access powerful pre-trained models to perform text analytics tasks like entity extraction, sentiment analysis, and content classification.
To create your own custom machine learning models, you can use AutoML Natural Language, an entire suite of products for training high-quality models with minimum effort, thanks to its easy-to-use interface. These tools are fully integrated with the rest of Google Cloud’s Services, providing a consistent experience.
Data visualization tools help you create graphs, charts, and dashboards to showcase your text analytics results in a way that’s engaging and easy to understand. Using visualization software, you can uncover trends and patterns, and see how they evolve over time.
Let’s take a look at two popular tools for data visualization:
Google Data Studio is a free and user-friendly tool that allows you to create interactive customized visualizations from your data. One of the best things about Google’s platform is that it enables you to connect with over 100 data sources.
Also, it has several ready-to-use templates to help you build reports and dashboards in just a few clicks. Once you’re done, you can easily share your visualizations with your coworkers, and even invite them to collaborate.
Tableau is a business intelligence platform aimed at individuals and organizations that want to leverage the power of data with visual analytics. The platform is robust, scalable, and supports integrations with a wide variety of data sources, allowing non-technical users to create beautiful and complex visualizations.
Tableau excels at handling big data and makes it easy to spot patterns and trends with different parameter settings which you can use to view your data.
With text analytics software you can transform unstructured text into quantifiable data, spot all kinds of trends and patterns, and provide your teams with powerful insights to create better customer experiences.
The best part is that you don’t need to invest in expensive infrastructure, or a team of machine learning experts to analyze your data. SaaS text analytics tools can power up the apps you already use, in a fast, entirely accessible, and cost-effective way.
Ready to get started? Request a demo from MonkeyLearn and start gaining meaningful insights from your data.
May 14th, 2020