Monitoring Spark

The Spark dashboards in Nexthink Infinity provide full visibility into how Spark is used, how conversations progress, and how issues are resolved or escalated across your organization.

By combining live usage metrics, outcome tracking and message-level insights, these dashboards help support teams, administrators and supervisors continuously monitor how Spark performs, and drive improvement. Quickly assess adoption, measure self-resolution success, and identify where further actions or escalations occurred.

The Spark overview and All conversations dashboards support a closed-loop optimization process, enabling data-driven decisions to improve the employee experience and scale Spark confidently.

• Using Spark overview

• Monitoring conversations

Understanding conversation state and outcome

Each conversation includes:

• A State

• An Outcome

These attributes represent different aspects of the interaction.

Conversation state

The state indicates whether the conversation is active or closed.

A conversation can be:

• In progress: The interaction between the employee and Spark continues.

• Completed: Spark closes the conversation.

Spark marks a conversation as Completed when:

• The employee confirms the issue is resolved.

• Spark creates a ticket automatically.

• After six hours of inactivity following the last Spark message.

Conversation outcome

When Spark closes a conversation, it assigns one of the following outcomes based on the final interaction.

• Resolved

• Escalated

• Abandoned

Resolved

Spark assigns the Resolved outcome when a conversation results in any of the following:

• an automated remediation, action, or workflow;

• guidance, instructions, point of contact or a knowledge article;

• determination, following automated diagnosis or triage, that the appropriate next step is to issue a request (including for hardware, software, or access to applications and/or systems).

No express confirmation is required to classify a conversation as a Resolution.

Escalated

Spark assigns the Escalated outcome in one of the following scenarios:

• Spark creates a ticket automatically.

• Spark recommends escalation.

Abandoned

Spark assigns the Abandoned outcome when the conversation closes without resolution or escalation. For example:

• A clarification question remains unanswered.

• An action is proposed but not approved.

• An action fails or does not complete.

After automatic closure, Spark evaluates the conversation outcome and assigns Abandoned or Resolved.