Customers are increasingly shifting their day-to-day activities from offline to the digital world, accelerating the need for enterprises to use customer experience analytics to drive better decisions. For the telecom industry, this is particularly important as the industry is presently fighting an uphill battle against customer disengagement, low satisfaction rates and preconceptions of what to expect.

 

Opsis emotion-AI based solutions are suitable for contact centers across different industries — such as insurance/financial services and telecom sectors. Our solutions help enterprises achieve their CRM goals of building customer engagement and loyalty, thereby optimizing the spend per customer over the lifespan.

 

Our technology helps to create a more efficient, smoother and better customer experience for contact centers using video or voice calls. We use facial expression and/or voice-based emotion AI which leverages sentiment, intent, tonal and emotional analytics to guide agents in real-time. The result is a highly detailed map of a conversation that reveals the customer’s intention, emotional state, and likely next actions. Our solutions can be configured to be used in numerous contact center use cases, including customer satisfaction, fraud detection, agent performance and coaching, and stress-level monitoring. 

 

We use voice-based emotion detection and natural language technology (NLT)-based analysis to filter out context and meaning. Our model has been trained to recognize emotions in any type of language including tonal languages.

 

Our emotion AI helps to address the current challenges with call centre coaching. Coaching has been an important part of call centre success. However, with large organizations, higher call volume, more complex issues, rapid change, and remote work models – human coaching has its limits.  Supervisors can’t possibly monitor every interaction in real time, instantly ascertain the customer’s emotions and intent and offer every agent specific guidance to help them resolve customer issues quickly. However, machines can do all this and do it more accurately. Insights gained can also be used to identify ideal use cases to implement self-service automation, use agent resources more efficiently. This helps to lower the cost of service while maintaining a high-quality customer experience. 

 

Outcome is increase ROI – improved Customer Satisfaction Score, higher retention and conversion rates and fraud cases averted. Improvements to customer retention can have an outsized impact on profits, with just 5% resulting in an additional 25%-95%. (Bain and Company).

Customer Satisfaction - Emotion Mapping & Sentiment Analysis

  • Find key conversational moments, topics to reveal patterns in customer intents and sentiments
  • Reveal friction/pain points in customer service experience
  • Automate alerts and speed up response time to critical issues
  • Identify low satisfaction situations and their root cause
  • Measure customer satisfaction scores over time; cross-monitor with an increase or decrease in customer’s activities/product sales 
  • Identify products of high interest 
  • Identify customers with higher chance of buying 
  • Increase product sales: retention, new customer acquisition

Fraud Detection/Credibility analysis

  • Detect whether the customer’s emotional state is anxious, uneasy and suspicious
  • Voice markers and words semantics help draw a more detailed picture for credibility analysis
  • Detection of fraudulent behaviour leads to substantial cost savings

Call Centre Support/Coaching

  • Help agents to perform better and manage challenging calls
  • Generate reports to help agents with timely, targeted, objective, actionable guidance during every interaction with the customer 
  • Address agent’s well-being: assess stress level, read signals that indicate burn-out symptoms
  • Reduce agent attrition 
  • Help to inform how agents are trained to improve important soft skills and emotional intelligence on calls
  • Reduce operational costs with improved agent productivity, shorter average handle time
  • Identify ideal use cases to implement self-service automation, use agent resources more efficiently and lower cost of service

Agent’s Performance

  • Assess agent’s performance based not only on the outcome of the call but also the emotional response of the customers
  • Track agent’s emotions such as agreeableness, stress, anxiety, frustration
  • Help to identify agents whose dispositions are suitable for call centre work