Monitoring conversations

The All conversations page provides visibility into all conversations that take place within Spark. It enables supervisors, administrators and support teams to analyze user interactions, understand conversation outcomes, and identify areas for improvement.

The dashboard lists all conversations that occur within Spark. It allows you to monitor ongoing interactions and review completed sessions.

Accessing the All conversations page

To access the Spark overview page, navigate to Spark > All conversations from the main menu.

Timeframe picker and filtering considerations

Use the timeframe picker in the upper-right corner to define the all conversations period.

All metrics, including total conversations, outcomes, and active conversations, reflect the selected timeframe. You can refine results using filters:

• State: In progress or Completed

• Outcome: Resolved, Escalated, Abandoned

• Type: Incident, Request, Question, Security concern, Non support

Filters apply to both the dashboard metrics and the conversation table.

Conversations are available for 30 days. After that, a summarized record is retained for 13 months, including the conversation state, outcome, and type.

Using the conversations dashboard

Use the conversations summary to assess overall outcomes, the timeline to identify trends, and the conversation list to investigate individual conversations.

Conversations summary

The conversations gauge and timeline provide an overview of conversation activity within Spark. They show the number of conversations with outcomes that are currently Resolved, Escalated, or Abandoned, as well as the number of Active conversations over the selected period.

Conversations table

View all recent conversations and access details for each by selecting an item in the table.

The table is organized by:

• State: Displays the current progress of the conversation, such as In progress or Completed.

• Outcome: Indicates the result of the conversation, such as Resolved, Escalated, or Abandoned.

• Intent: Shows the user intent associated with the conversation, when available.

• Type: Shows the conversation classification that may be Incident, Request, Question, or Security concern. Any conversations that are not asking for IT support, as well as testing, are classified as Non support.

• Last update: Displays the date and time of the most recent update to the conversation.

• Duration: Shows the total duration of the conversation, which is computed as the difference between the first and last message within the conversation.

• Conversation began: Shows when the conversation started.

• Message count: Displays the total number of messages exchanged between the employee and Spark.

• Employee UPN: Shows the employee unique identifier (User Principal Name).

Accessing conversation details

Select a conversation from the table to open a detailed view that includes messages, outcomes, and actions.

This detailed insight helps you understand how Spark managed each conversation and provides the foundation for troubleshooting and continuous improvement.

Search conversations

Use the search bar in the upper-right corner of the Conversations section to filter conversations by keywords. This helps you quickly narrow the list based on specific topics, employees, or concerns.

Reviewing conversation details

Select a conversation from the conversation list to review it in more detail.

The conversation details view allows you to review:

• The messages exchanged during the conversation

• How the conversation progressed over time

AI reasoning

When relevant, the conversation details include how Spark handled the conversation and which sources it analyzed to provide an answer or execute an action. This information helps you:

• Understand how Spark leverages existing knowledge and actions to resolve employee issues.

• Review the steps taken throughout the conversation.

Reviewing conversation details, including AI reasoning when present, supports transparency and helps teams assess Spark conversations and take actions to improve knowledge or actions available to Spark.

Click on the Reasoning tab to expand the widgets and learn how Spark handled the conversation.