Sentiment analysis is a machine learning (ML) model trained to measure emotion of interactions, such as if the interaction is positive, negative, or neutral. This analysis can helps businesses understand their customers' view of a product, person, topic, or event. Five common styles of sentiment are over time, channel, agent vs Customer, brand, and entity.
Components of Sentiment Analysis:
- Artificial Intelligence: Natural Language Understanding, Machine Learning, Artificial Intelligence, and large data sources.
- Language Understanding: AI for transcription, comprehension, linguistics, topic and key phrase engines, entities and specially developed software to determine sentiment.
- Business Context: Sentiment around Brand, Topic, Product blended with information from 3rd party systems
How can sentiment analysis be used?
Sentiment analytics gives insights into growing customer service issues. For example, organizations can identify frequently used phrases, terms, and concepts whenever customers call. Conducting sentiment analytics allows managers to identify problems and address them before they establish themselves. Here are some ways of how sentiment analysis can be used:
- Get insight into the effectiveness of call center agents and customer support representatives
- Gauge the overall sentiment about the products and services of a business
- Identify common problems and pain points in the delivery of customer support
- Monitor opinions and attitudes about services, products, and customer support
- Give organizations a unified view of the full customer journey
- Improve team performance by empowering managers to deliver personalized, targeted coaching
Questions that can be answered using sentiment analysis:
- Do agents improve, recover, or degrade over the course of a call or over a chat or SMS?
- Do customers prefer certain channels? Do they perceive the same information and the same communication in the same channel and with the same tone?
- How do the interplay of emotion and sentiment impact a team's delivery of customer experiences?
Sentiment analysis is essential if you want to fully understand and drive more value from interactions. The insights can improve customer retention and overall customer experience. See how SuccessKPI sentiment analytics can help you improve your customer experience.