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AI-driven behaviors and metrics for customer satisfaction.
Enlighten AI for Customer Satisfaction automatically analyzes agent soft-skill behaviors that drive customer sentiment on every interaction—objectively and consistently. The purpose-built customer satisfaction behavioral models are derived from 20+ years of industry experience, using the most expansive labeled CX dataset on the market.
Empower your agents to be their best by measuring the proven soft-skill behaviors that drive CSAT.
Instead of relying on a subjective behavioral analysis based on a small sample size, Enlighten AI for Customer Satisfaction delivers an objective measurement of customer sentiment and agent behaviors on all interactions using contact center behavioral AI analytics. Behavioral scores are operationalized in real time, and presented in an easy-to-read heatmap, enabling every team and individual to focus on the same organizational KPIs regardless of their location.
Aiming for best-in-class experience
Learn how Fifth Third Bank used Enlighten AI for Customer Satisfaction to improve agent performance with AI-driven analysis.
Customer satisfaction (CSAT) is critical to any company’s success, especially in today’s rapidly changing world. Consumers are increasingly demanding more from customer service, including increased transparency, more personalized experiences and proactive engagement. Contact centers often struggle with inadequate performance measures, as the agent soft skills proven to drive CSAT, like empathy and taking ownership, are subjective and often not measured.
Outdated quality methods further complicate the issue. Manual, subjective quality analyses are costly and inefficient, lead to only small samples being evaluated, and often result in inaccurate assessments. With 99% of interactions ignored in these types of assessments, agents often receive insufficient feedback, leading to disengagement and unpreparedness for complex customer queries.
Enlighten AI for CSAT tackles these challenges by leveraging comprehensive data from all channels and using purpose-built AI for CX models to measure 100% of interactions. This scalable solution focuses on agent soft skills and sentiment, embedded in customer experience (CX) applications, ensuring actionable insights and timely information for agents.
Enlighten AI for CSAT stands out because it leverages NICE's decades of experience and vast conversational data to deliver unparalleled insights. Think of Enlighten AI as the brain of CXone, comprising hundreds of AI models trained on extensive data to understand and predict human behaviors in customer interactions. This robust framework provides real-time feedback and guidance, integrates seamlessly across the CXone platform, including quality management, coaching, and analytics, and is ready to deliver value right out of the box.
What truly sets Enlighten AI apart is its ability to accurately measure nine specific agent behaviors that are proven to boost CSAT:
When agents consistently demonstrate these behaviors, they are more likely to make personal connections with customers, respond effectively to their needs, and deliver exceptional experiences. This focus on specific, actionable behaviors helps contact centers transform their customer service into a powerful competitive advantage.
Agent soft skills are essential for creating positive customer experiences. In fact, 94% of contact center executives in a recent survey by NICE believe that these skills impact overall satisfaction, but only 41% are currently using soft skills in assessments or coaching. Soft skills like empathy and effective questioning are crucial, especially in complex or emotionally charged interactions. Enlighten AI for CSAT measures these behaviors and provides real-time feedback, helping agents continuously improve and enhance customer satisfaction.
Enlighten AI for CSAT models are deeply integrated across the CXone platform, enhancing various solutions:
Sentiment analysis is used to measure customer satisfaction. Using machine learning models that are trained on a large CX dataset, sentiment analysis predicts the likelihood of a positive or negative response on an after-interaction survey. Sentiment scores are calculated for 100% of interactions—providing real-time and post-call insights. This comprehensive analysis helps businesses understand and improve customer experiences by addressing emotional aspects of service. It also provides a more accurate picture of overall customer satisfaction.
Customers utilizing Enlighten AI for CSAT are experiencing significant enhancements. The primary improvements include increased CSAT, reduced costs associated with manual listening, and enhanced coaching effectiveness, leading to better employee engagement and performance. Additionally, it increases the consistency and accuracy of quality scoring.
An analysis of three large enterprise customers, each handling millions to billions of interactions annually, highlights the transformative impact of Enlighten AI. By evaluating every agent interaction and focusing on soft-skill behaviors, these companies found a direct correlation between improved agent performance and positive business outcomes. Organizations can reduce AHT, improve sentiment, and increase FCR in tandem by focusing on these targeted behavioral soft skill coaching programs.
For instance, Solera, a global leader in vehicle lifecycle management, reported a 13% improvement in CSAT within 60 days after shifting their coaching focus to soft-skill behavioral performance for over 1,000 agents. Similarly, Republic Services, a major waste disposal company, achieved a 33% reduction in negative customer sentiment and a 30% decrease in repeat calls within six months of deploying Enlighten AI.
No expertise is required with purpose built out-of-the-box behavioral models.
Increase employee engagement
Motivate agents with real-time feedback and guidance on behaviors and skills needed for achieving their goals.
Improve coaching effectiveness
Equip supervisors with quality and coaching insights to deliver personalized coaching from an objective analysis of agent behaviors on 100% of all interactions.
Reduce manual listening
Automate the analysis to identify trends in customer satisfaction and agent behaviors before they negatively impact customers — or the bottom line.
Performance metrics on all interactions
Monitor performance using visual dashboards with heatmaps of sentiment and agents’ behavioral scores.
Objective agent behavioral analysis
All agents are scored objectively, on every interaction, using pre-built AI-driven behavioral models for customer satisfaction.
Data-driven coaching and evaluation
Pre-built supervisor and agent scorecards aggregate KPIs, identify coaching opportunities and link to evaluation and feedback workflows, so supervisors spend less time hunting for information.
Operationalized results
Behavioral scores are operationalized by a suite of quality, performance, and coaching applications, enabling all stakeholders to focus on the same organizational KPIs.
Inappropriate action
Demonstrate ownership
Effective questioning
Promote self-service
Active listening
Be empathetic
Acknowledge loyalty
Set expectations
Build rapport
Enlighten AI Routing: This solution combines AI with available data sources to intelligently match customers with the best-suited agents in real time, improving customer connections and key performance indicators.
Real-Time Interaction Guidance: Provides immediate feedback on agent performance and customer sentiment during interactions, offering actionable guidance to enhance the customer experience.
Supervisor Monitoring: Allows supervisors to monitor interactions in real time and intervene directly if needed to ensure seamless customer experiences.
Interaction Analytics: Analyzes 100% of interactions for sentiment and agent soft-skill behaviors and correlates them to important organizational processes and KPIs such as Average Handle Time (AHT), First Contact Resolution (FCR), and customer frustration.
Quality Management: Uses insights from agent behavioral scores for coaching, providing objective and consistent feedback that impacts their performance.
