Case Study
Call center customer sentiments analysisThe detection of customer sentiments help companies to craft better customer experiences. In the assurance sector, within the customer interaction with call centers, the goal is to determine the emotional tone of the conversation, redirects to the right services & adapts the speech for the customers
IN BRIEF
KEY INFORMATION
VOICE ANALYSIS
By analyzing the tone of voice & detect the emotions of customers
EMOTION AI
Through interpretation techniques (audio, video, etc.)
TEXT INTERPRETATION
From speech-to-text to Natural Language Understanding
Challenges
- Capture sarcasm and intrinsic complex conversation
- Process of any size and length of dialogues
- Split the multiple emotions expressed during a conversation
Solution
- Creation of an automated search
- Classification of customers depending on their trends of emotions
- Definition of the reasons behind changes in customer’s emotion
Gains
- Decrease Churn rate while improving sales by changing the dynamics of a conversation with a customer
- Solution implementation: 3 weeks
- Increase Customer satisfaction
Testimonial
“We were able to quickly optimize how to improve customer satisfaction“