Assessing Customer Satisfaction
Sentiment analysis gives call center agents an instant snapshot of how a customer feels. Is the customer satisfied? Angry? Indifferent? Using natural language understanding by IBM Watson, our contact center solution quickly assesses the customer’s emotion and conveys it to agents with a visual aid, such as a happy face or an angry face. Seeing an angry face, for example, can help prompt an agent to escalate the priority of a conversation, or forward it to a supervisor for handling. Likewise, seeing a list of happy faces can help a supervisor know the team is performing at its best.
Proactively Address Changes in Customer Behavior
Customer behavior, such as the reason for a call or changing emotional responses to an agent’s reply, can be measured and studied. Sentiment analysis and tracking allows your call center to not only collect important data about changes in customer behavior, but to do something to fix it.
Using Content Analysis to Learn from Interactions
In addition, cognitive search, keyword extraction, and content analysis helps your team detect patterns in communication. Learn what customers are talking about, how they respond to your customer service agents, and what makes them happy (or upset). Quickly search conversation transcripts to understand your customers’ needs.
- Sentiment analysis provides at-a-glance data on customer happiness
- Escalate conversation priority based on the customer’s conveyed emotions
- Search and analyze transcripts
- Route customers to the correct agent based on the customer’s sentiments
- Understand patterns in customer behavior
We are happy to answer questions and discuss specific workflows and requirements on a live presentation online or set up a pilot project to trial the solution without paying any license fees