Sessions

Sessions in the OuterBox AI Observability platform allow you to track and analyze multi-step conversations between users and your P3 AI Web Assistant. Unlike traces which focus on individual interactions, sessions group related interactions together to provide a complete picture of the user's journey.

What Are Sessions?

A session represents a series of related interactions between a user and your AI assistant. Sessions are particularly valuable for understanding:

• How users progress through multi-step inquiries
• The complete context of a conversation over time
• User satisfaction across an entire interaction journey
• Patterns in how conversations evolve

Think of sessions as the complete customer journey, while traces are the individual steps along that journey.

How to Use Sessions Effectively

Accessing Sessions

1. Navigate to the "Sessions" section in the left sidebar of the OuterBox AI Observability platform
2. You'll see a list of recent sessions, typically organized by user and timestamp
3. Use filters to narrow down sessions by date, duration, or user characteristics

Analyzing Individual Sessions

When you click on a specific session, you'll see:

• All the traces (individual interactions) that occurred within that session
• The chronological flow of the conversation
• Session duration and engagement metrics
• Overall session outcomes and quality indicators

Common Use Cases for Sessions

• Conversation Flow Analysis: Understand how users navigate from initial questions to specific product inquiries
• User Journey Mapping: See the complete path users take when researching P3 products
• Satisfaction Tracking: Measure how user satisfaction evolves throughout a multi-step conversation
• Abandonment Analysis: Identify where users tend to drop off in longer conversations

Best Practices for Working with Sessions

• Focus on Complete Journeys: Use sessions to understand the full user experience rather than isolated interactions
• Identify Conversion Patterns: Look for session patterns that lead to successful outcomes (like quote requests)
• Optimize Multi-Step Processes: Use session data to streamline common conversation flows
• Compare Session Types: Analyze differences between short, focused sessions and longer, exploratory ones

Session Metrics to Monitor

The platform provides several key metrics for sessions:

• Session Duration: How long users engage with your assistant
• Interaction Count: The number of back-and-forth exchanges in a session
• Topic Progression: How conversation topics evolve within a session
• Resolution Rate: Whether sessions end with user needs being met

Connecting Sessions to Business Outcomes

To maximize the value of session data:

1. Tag sessions based on outcomes (e.g., "Quote Requested," "Product Information Provided")
2. Correlate session patterns with business metrics like quote requests or contact form submissions
3. Identify the most effective conversation paths for different user needs
4. Use these insights to optimize your assistant's responses for better outcomes

Sessions provide crucial context for understanding how users interact with your P3 AI Web Assistant over time, helping you optimize the complete customer experience rather than just individual responses.