User Engagement Metrics#

1. Conversation Metrics

   class ConversationMetrics:
       def __init__(self):
           self.conversation_tracker = ConversationTracker()
           self.quality_analyzer = QualityAnalyzer()
           self.engagement_calculator = EngagementCalculator()
   
       def calculate_engagement_score(self, user_id, timeframe):
           conversations = self.conversation_tracker.get_user_conversations(
               user_id, timeframe
           )
   

Key engagement factors

       frequency = len(conversations) / timeframe.days
       avg_length = sum(conv.length for conv in conversations) / len(conversations)
       task_completion = self.calculate_task_completion(conversations)
       quality_score = self.quality_analyzer.average_quality(conversations)

       return {
           'frequency_score': min(frequency / 10, 1.0),

Normalize to 0-1

           'depth_score': min(avg_length / 20, 1.0),

Normalize to 0-1

           'completion_score': task_completion,
           'quality_score': quality_score,
           'overall_engagement': (
               frequency_score * 0.3 +
               depth_score * 0.2 +
               completion_score * 0.3 +
               quality_score * 0.2
           )
       }

2. **Retention Patterns**
- Cohort Analysis: Track user groups over time
- Usage Segmentation: Light, medium, heavy user patterns
- Churn Prediction: Identify at-risk users
- Reactivation Success: Measure return user effectiveness

### Quality and Satisfaction Metrics

1. **Task Completion Rate**

```python
class TaskCompletionTracker:
    def __init__(self):
        self.task_classifier = TaskClassifier()
        self.completion_detector = CompletionDetector()

    def track_completion(self, conversation):

# Identify user's intended task
        intended_task = self.task_classifier.identify_task(conversation)

# Determine if task was completed successfully
        completion_status = self.completion_detector.evaluate_completion(
            conversation, intended_task
        )

        return {
            'task_type': intended_task,
            'completed': completion_status.success,
            'confidence': completion_status.confidence,
            'time_to_completion': completion_status.duration,
            'user_satisfaction': completion_status.user_feedback
        }

2. User Satisfaction Index
   • Direct feedback collection
   • Implicit satisfaction signals
   • Net Promoter Score (NPS)
   • User sentiment analysis

Business Impact Metrics#

1. Value Realization

   • Time savings measurement
   • Productivity improvement tracking
   • Cost reduction quantification
   • Revenue impact assessment

2. Growth and Expansion

   • User acquisition efficiency
   • Viral coefficient measurement
   • Cross-selling opportunities
   • Market penetration analysis