Alterna CX’s text analysis software automatically classifies the topic of a text so as to achieve high accuracy for identifying the root causes of customer comment.  This automated efficiency removes the need for human effort and creates a single source for all customer experience feedback. Alterna CX’s ready-to-use text analytics model works with a strong machine learning algorithm to automatically identify and categorize the polarity, urgency, or topic of the customer issues.

This online sentiment analysis model ensures that customer experience professionals can see comments, then use that informative feedback as a basis for appropriate action. Moreover, along with open-end text responses and general satisfaction driver criteria, the model is used for the creation of its own predictive analytics model. It has been trained by multiple source data from complaints and review sites such as Amazon.com and Trustpilot.com. We update all of our models continuously with best practices. What is more, a new emotion and sentiment model with a new annotation set can be created and updated with new data sets.

There are a few different ways to approach this type of analysis, but they can all essentially be reduced to two categories: positive or negative. Alterna CX’s current sentiment model has three categories: Positive, Negative, Neutral.  Moreover, inspired by Dr. Robert Plutchik’s emotional wheel study of the seven most frequently felt human emotions (joy, trust, fear, surprise, sadness, anger, and disgust), our engineering team developed this AI-based advanced text analytics technology.

The process is straightforward. Simply provide us with the names of your competitors, your brand, and the relevant platforms such as Google Play, Reddit, Instagram, etc. Once we have this information, we'll grant you access to the Alterna CX platform within 3 days. To get started, please complete the form on this page.

Machine learning, statistics, and natural language processing (NLP) are some of the tools that Alterna CX’s text analytics tool uses to identify customers’ feelings and thoughts in the broadest sense possible.

Additionally, unlike general aspect-based sentiment analysis systems, the Alterna CX’s text analysis tool is able to apply emotion, sentiment, or intent to each topic and subtopics.

Alterna CX's solution also deploys contextual, action oriented models that can assess and triage urgency of improvement actions at touchpoint level.

Yes, it is possible to add new topics to text analytics models and it is very easy to do so. You can add new topics to already existing text analytics models on Alterna CX rapidly and efficiently.