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User Engagement History

This guide explains how to view and analyze customer interaction history in ConnectNow.

The User Engagement History section provides visibility into all customer calls and chats handled by AI assistants and human agents.

Accessing User Engagement History​

To view engagement history:

  1. Log in to the ConnectNow dashboard
  2. Navigate to Dashboard → History

The History page displays a complete record of customer interactions.

Types of Interactions Tracked​

ConnectNow tracks the following interaction types:

  • Incoming calls
  • Incoming chats
  • Missed calls
  • Missed chats
  • AI-handled interactions
  • Human-handled interactions

This helps you understand customer activity and response effectiveness.

Available Filters​

To quickly find specific interactions, you can apply the following filters.

Date Filter​

  • Filter interactions by a selected date range
  • Useful for daily, weekly, or monthly analysis

Interaction Status​

  • Missed calls or chats
  • Answered calls or chats

Interaction Type​

  • Incoming calls
  • Incoming chats

Filters can be combined to narrow down results.

Interaction Details​

For each call or chat entry, the following details are available:

  • Customer region
  • Date and time of interaction
  • Customer name (if available)
  • Interaction duration
  • Forwarded or escalation history

This information helps track how customer enquiries were handled.

Forwarding and Escalation Information​

When an interaction is forwarded:

  • The history shows whether the call or chat was handled by:
    • AI assistant
    • Human agent
  • Escalation timestamps are recorded
  • Forwarded agent or department details are visible (if applicable)

This provides full transparency into AI-to-human handoffs.

AI Conversation History and Summary​

If the AI assistant is enabled for an interaction:

  • The complete conversation transcript is available
  • An AI-generated summary is provided

AI Summary Benefits​

  • Quickly understand the context of the interaction
  • Identify customer intent and outcome
  • Reduce time spent reviewing long conversations

The summary is generated automatically by the AI assistant.

Use Cases for Engagement History​

User Engagement History can be used to:

  • Monitor customer response quality
  • Review missed interactions
  • Analyze agent performance
  • Improve AI assistant instructions
  • Identify common customer enquiries
  • Audit customer conversations

Best Practices​

  • Review missed calls and chats regularly
  • Use filters to analyze peak interaction times
  • Check AI summaries for quick insights
  • Use conversation history to refine AI behavior
  • Monitor escalation patterns to optimize staffing

Next Steps​

From the User Engagement History page, you can:

  • Review individual conversations
  • Identify follow-up or callback requirements
  • Improve AI assistant configuration
  • Optimize human agent availability

Additional feature guides provide deeper insights into analytics and performance optimization.