**GenAI4CSM** combines **Relationship Analysis** —evaluating interactions at both message and case levels—and **Sentiment Analysis** , which aggregates these insights to infer overall customer sentiment. With AI-driven analysis, organizations can improve customer satisfaction, enhance operational efficiency, and proactively manage relationships.

**Relationship Analysis:**

- Analyzes customer-agent interactions at the **message level** and **case level**.
- Provides relationship scores to measure sense of belonging, communication quality, tone, and responsiveness.
- Developed in collaboration with academic reasearchers and customers, to validate the value in practice and the theoretical underpinning.

**Sentiment Analysis:**

- Aggregates relationship scores to determine **overall sentiment trends** for customers or accounts.
- Provides actionable insights to identify dissatisfied customers and intervene proactively.
- Includes prediction of CSAT before case closure, which allows for proactive CSAT improvement

**Visual Dashboards and Reporting:**

- Presents sentiment trends and relationship scores in **intuitive, actionable dashboards**.
- Enables filtering and analysis across agents, teams, and customer segments.

**Automation and Proactive Alerts:**

- Real-time monitoring of sentiment changes to identify risks early.
- Automates follow-up actions for customer retention or agent performance improvements.

**Key Benefits**

- **Enhance Customer Experience:**
Strengthen customer relationships by identifying and addressing dissatisfaction early.
- **Improve Agent Performance:**
Train and coach agents effectively with data-driven insights into communication quality.
- **Reduce Churn and Drive Loyalty:**
Retain customers by proactively managing relationships and improving satisfaction metrics.
- **Boost Operational Efficiency:**
Automate sentiment tracking and follow-up actions, reducing manual workload.