What to Look For In a Text Analytics Platform?

What to Look For In a Text Analytics Platform?

What to Look For In a Text Analytics Platform?

Data analysis is a godsend miracle in the world of technology that delivers rich insights into the perceptions and experiences of the customers. It also showcases the root causes of the issues that encounter in their interactions with an organization. But it totally relies on using the right kind of tools to harness the power of text in the right ways. Nowadays, the landscape of tools and platforms are quickly changing. This article discusses some of the most useful criteria for ascertaining commercial text analytics platforms on the basis of recent experiences.

  1. Look for the analytics methods that deliver accurate topic identification and sentiment analysis.

The most top-notch platforms like Provalis Research implement a combination of ways to analyze text, which includes machine learning techniques—supervised or unsupervised methods, semantic or natural language processing (NLP), topic identification and business rules.

Platforms equipped with machine learning methods use advanced algorithms. However, they deliver limited customization and tend to be black-box models that do not display the combination of algorithms of the vendors, so sometimes you won’t be able to explain results. These platforms can output results quickly, but lack in small data sets, short phrases and comments with technical terms or sarcasm.

  1. Look for the analytics methods that have the ability to use metadata to complement text data.

Although being easy to implement, many platforms and models do not have this capability. Structured data can complement text results and often act as a tie breaker for statements with ambiguous sentiment.

  1. Look for the analytics methods flexible in reporting dashboards that help visualize text insights.

Almost every platform deliver reporting on results with basic charts. Some deliver customizable reports to better learn the results and improvise analytics models, or have an enhanced dashboard. And some improvise the visual aspects of insights through integration with tools. Another aspect, frequency charts, lets data sorting on the basis of sentiment, topics and subtopics, in order to get a high-level overview of results. Also, look for the ability to export results in flexible formats and to add or remove variables.

  1. The data analytics method should have a fast and easy-to-use interface.

A data analysis with a simple interface makes it simple to learn and use the platform, navigate through the various functions and deliver outputs. Users desire a fast upload and download of data, and the ability to handle multiple file formats.

  1. The data analytics method should support multiple languages

Almost every platform works well only with English. Some do not support other languages at all. Good platforms support multiple languages, with the help of algorithms that take into consideration every aspect of the language’s grammar, rather than having to translate into English, which gets rid of the valuable nuances embedded in a language. Platforms built by regional vendors handle their main local language (mostly Spanish, French, German, Dutch and Chinese), but nonetheless, most are restricted when it comes to sentiment identification.