Text Analytics

The Resonate CX Text Analytics module is a sophisticated AI-driven tool capable of processing and analysing unstructured customer feedback. It uses natural language processing (NLP) and machine learning (ML) to quickly detect key patterns, themes, sentiments, and emotions present within text feedback.

The use of NLP permits Resonate CX’s Text Analytics solution to understand nuance the same way a human does. This enables it to lift heavy workloads off of human analysts, keeping them from being bogged down in data and permitting them to look at big-picture customer experience issues. In addition, features named masking and profanity filtering protect customer privacy and create a respectful, distraction-free environment for accurate analysis. They ensure compliance and enhance data quality, focusing insights on real issues.

Resonate CX’s TA module includes advanced features like name entity recognition and profanity filtering, which enhance the quality and integrity of insights. As the term suggests, name entity recognition automatically identifies and categorises entities such as names, locations, and products within the feedback. This helps organisations understand the context and identify recurring issues around key areas of interest that are unique to them.

Meanwhile, profanity filtering is another unique feature that removes or masks offensive language. This maintains professionalism and ensures that insights remain focused on real issues and remain respectful.

Together, these features enable organisations to understand positive, negative, and neutral feedback with clarity. The TA module continuously learns from the data, enhancing its accuracy and predictive capabilities over time, allowing businesses to stay in tune with evolving customer needs.