Most important features for selecting the best text analytics API

To make the right buying decision, you need to understand the most important text analytics features to consider when selecting the best solution for your business. Choosing the right solution for conducting text analytics is a decision that every company has to make for itself based on its unique requirements and industry vertical. It also depends on whether you are a local business, international, or based in a multi-cultural metropolitan region. Whereby, you will need to conduct sentiment analysis of data across geographies and demographics, in multiple languages. Taking into account all of these factors, by the end of this article, you will have a fair understanding of critical text analytics features you need to look out for when purchasing a text mining tool best suited to you.

How Do You Select The Best Text Analytics API?

The best text analytics API has several important aspects that give it high-precision results and uncompromised processing speed, even with multilingual data. The API should also be simple, scalable, and have an effective visualization dashboard. Here are key text analytics features you must review when choosing one for your business.

Top 10 Text Analytics Features

  1. Accuracy:

It goes without saying that you must choose a text analysis platform that gives you the most accurate results. This is not only important for trend analysis in the financial industry or healthcare, but also for analysing voice of the customer (VoC) data or even voice of the employee (VoE) information.

A text analytics API can give accurate results only when it has a massive bank of data, or corpus, that can be used to train it with. And if text analysis is to be done in multiple languages, then the corpus and the machine-learned training needs to be in those many languages. Only then, can the algorithm understand the text natively and not resort to translations, or else it will give inaccurate results.

  1. Feature & Aspect Classification:

In order to be able to do a comparative analysis of business results, it is important that the text analytics API performs aspect-based sentiment analysis (ABSA) to identify the aspects in the topics that are identified in your particular industry. It’s the only way you can truly unearth insights from product reviews, customer forums, surveys, social media, and other platforms of data.

Feature and aspect classification is especially useful in video content analysis (VCA) as well. The VCA engine analyses video content by converting it into text through speech-to-text transcription, and then runs the data through the text analytics API. Similarly, feature and aspect classification combined with comprehensive named entity recognition (NER) also enables the search inside video capability so you can search and discover insights across your entire video library by identifying all relevant topics, themes, and subject matters.

  1. Language detection & analysis:

Automatic language detection and analysis is one of the many crucial text analytics features. A good text analysis solution should be able to detect, understand and analyse data in multiple languages since most businesses are international. This is quite essential in social media sentiment analysis especially because people tend to write in the language they are most comfortable with.

A step ahead, the best text analysis API analyses each language in its native tongue so that no nuances are lost in translation. Since languages differ in syntax, word structure, and vocabulary, when data is translated into another language, it leads to wrong insights.

See Repustate's Text Analytics API in action.

  1. Knowledge graph:

A knowledge graph is a graphical depiction of the relationship between entities (people, places, events). It puts data in semantic context and so provides a framework for data analytics and integration. The bigger the knowledge graph owned by the text analysis API, the more accurate its results will be. And so, the text mining solution you need must have a generous knowledge graph as one of its vital text analytics features.

  1. Speed:

company has terabytes of data that is generated non-stop in the form of emails, marketing material, advertising & sales collateral, presentations, videos, employee information, and more. Further, it needs insights from the data that is related to it, in the form of reviews, surveys, user-generated videos, news, and such. If this need is also in multiple languages, it means that the text analytics API needs to have an extremely efficient processing speed not only for this mammoth data but also for doing it multilingually, without mistakes.

  1. Reporting Dashboard:

Another one of the must-haves in text analytics features is the reporting customer dashboard. If a text analytics solution has no way of giving its analysis in an actionable manner, then it doesn’t really fulfill its purpose. Having a graphical representation of the insights not only helps in understanding the data better but also in knowing if a business decision made on the basis of that insight is showing the desired results or not.

With a visualization dashboard, these reports can be viewed in real-time as well as shared among departments and teammates. This way critical changes can be made in a timely manner to thwart brand reputation crisis or customer attrition.

  1. Ease-of-Use:

The challenge in adopting any technical solution is the degree to which it is user-friendly or difficult. Depending on who is going to be the end-user, the text analytics tool needs to be easy to understand and practical. Certain software may be more technical and complicated depending on the industry, and so will need additional staff training. But if it is going to be used in multiple departments simultaneously, the tool needs to be easy to grasp.

  1. Ease of installation:

The best text analytics API needs to seamlessly fit into your current platform without interfering with workflow. This is another one of the important text analytics features that must be taken into consideration. Does the API need a third-party supporting technology for implementation? Is there downtime during installation? These are questions that must be asked. The good thing is that most of these APIs are available on cloud as well as on-premise installations. So, really, it is up to you to decide, which option suits you better.

Let Repustate's Text Anlaytics uncover your hidden insights

What Are The Business Applications of Text Mining?

From detecting policy violations and cyberbullying, to client nurturing and predictive analysis with data patterns, text mining is vital in many industries. It is a catalyst behind stellar business intelligence for enterprises as well as small & medium companies.

Below is a gist of the many real-world applications of text mining.

  1. Electronic Health Records:

Text analytics in healthcare is instrumental in improved patient experience and healthcare.

  1. Client Nurturing:

Text mining gives businesses better insights into what their clients expect of them.

  1. Reputation Management:

Brands can better understand data captured from voice of the customer (VoC) programs by analysing comments, news, and other such content.

  1. Cyberbullying & Threat Detection:

A text analytics API lets you know if community standards are followed in tweets and comments on your social channels.

  1. Search Engine Optimization:

Search engine optimization can translate to text analytics to identifying spam in emails, or keyword stuffing in websites.

  1. Social Media Listening:

Brands can have direct engagement with customers, leading to more personalized interactions.

  1. Data Patterns:

It helps industries such as healthcare, finance, meteorology, etc. study patterns in historical and current data to predict trends.

  1. Returns & Warranty:

Thanks to intelligent text analytics features, understanding data from dealer service professionals across locations regarding warranty claims and returns has become easier.

  1. Surveys & Reviews:

Brands can understand complex data in open-ended responses in surveys through text analytics.

  1. Voice of Employee & Recruitment:

You can find the right candidate to hire, as well as reduce your employee attrition rate by drawing insights from social media listening and voice of the employee (VoE) data.

Learn more about Text Mining Applications

The best text analytics API at your fingertips

Armed with vital and intelligent AI-powered text analytics features, the best text mining solution can deliver results ensuring accuracy, speed, ease-of-use, and scalability. It will have a customer dashboard through which a company’s decision-makers can actually see and analyze the findings. Repustate’s text analytics API gives you all this and more, while reading languages natively. No translations are required because each language has its own speech tagger and lemmatizer. Additionally, you don’t need third-party technology under the hood to get it working. The API is self-served and available on cloud, as well as behind your firewall, so your data is secure and confidential.

Talk to us for more information.

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