Natural Language Understanding (NLU) enables you to extract meaningful insights from texts sent by your customers, which can be useful for many aspects of your business. For example, these insights can provide support for the decision-making process to engage even more of your customers and help identify which service and/or product is negatively or positively affecting the NPS score.
NLU works by recognizing intents, entities, sentiments, and emotions, in natural language texts. These terms are described in more detail below:
Natural language text (or "Expression"): refers to the ways in which humans communicate naturally in a text conversation. More specifically, natural language text refers to the way humans communicate without using any predefined texts.
Intent: refers to the goal that a customer has in mind when talking to a bot. It's all about what the user wants to get out of the interaction.
Entity: entities are important pieces of information that can be found in expressions. These include date, email, monetary value, and other important pieces of information.
Sentiment: refers to the sentiment polarity (positive, negative, and neutral) in a given expression.
Emotion: like the sentiment but provides more specific information on how users are feeling in terms of the following emotions: happy, sad, angry, fear, surprise, or disgust.
NLU replaces the slow and difficult process of manual review of text messages. It provides accurate insights extracted from conversations, which can be used to feed dashboards, helping you to better understand your data and, therefore, help make your business more data driven.