# Using Spark overview

The Spark overview page provides insights into how employees are using Spark across your environment. It displays live metrics on user activity, conversation flow and overall engagement, helping you monitor performance and responsiveness.

## Accessing the Spark overview page

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

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## Using the timeframe picker

Use the timeframe picker in the top-right corner of the page to select a preset timeframe or define a custom time period. The system applies the chosen timeframe to all widgets on the page. If you do not specify a timeframe, the default is the last 30 days.

## Using the Spark overview page

The Spark overview page includes the following widgets:

* Usage summary
* Outcome distribution
* Conversations and resolutions overview
* Conversation type performance

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#### Usage summary

The **Usage summary** KPIs give you a high-level snapshot of Spark activity:

* **Active users**: Displays the number of users who interacted with Spark during the selected timeframe.
* **Total conversations**: Shows the total number of interactions or sessions initiated.
* **Active conversations**: Indicates ongoing sessions that are not yet closed or resolved.
* **Average resolution time**: Measures how long it takes, on average, to resolve a conversation — in this example, *5 minutes and 13 seconds*.

This section helps you assess adoption rates and response efficiency over the last 30 days or any selected timeframe.

#### Outcome distribution

The **Outcome distribution** widget summarizes the status of all conversations. It includes:

* **Resolved**: Conversations successfully solved by Spark.
* **Escalated**: Conversations handed off to a human agent.
* **Non-support:** Conversations with non-actionable messages or questions not related to IT support.
* **Abandoned**: Conversations where the user stopped responding or exited before resolution.

This widget provides a quick view of service quality and self-resolution capability.

#### Conversations and resolutions overview

The **Conversations and resolutions overview** chart visualizes trends in Spark activity and outcomes over time. Use this chart to:

* Identify resolved issues when many users interact with Spark.
* Monitor resolution efficiency by tracking resolved conversations.
* Detect patterns of inactivity that might indicate adoption challenges.

#### Conversations type performance

The **Conversations type performance** widget shows Spark performance by conversation classification, such as:

* Incident
* Question
* Non-support

For each classification, the widget displays:

* Number of conversations
* Resolution outcomes
* Average resolution time

Use **Search for issue type** to filter conversations by issue type. This widget helps you understand why users contact Spark, identify areas for improvement, and assess effectiveness by interaction type.

### Using dashboard widgets

Right-click on any item or value within a dashboard widget to access a set of options. The available options depend on both the widget type and the data type of the selected item.

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* **View investigation** opens the Investigations page for the original NQL of the widget, plus any applied filters to the Dashboard page.
* **Drill down to …** opens the Investigations page with the results of the NQL query listing items from one of the following alternatives:

  * The **root table** of the original query, for example, `agent.conversations`.
  * **Associated object tables**, such as `devices` or `users`.

  The NQL query from the drill-down retains the context of the original query.
* **Copy** copies the formatted value visible on the widget.
* **Copy raw value** copies the full underlying value.

Access Investigations from Spark overview. Refer to the [Managing Investigations](https://docs.nexthink.com/platform/user-guide/investigations/managing-investigations) documentation for more information.

#### Spark KPI widget NQL examples

Refer to the [Spark NQL capabilities](https://docs.nexthink.com/platform/user-guide/spark/spark-nql-capabilities) documentation for more information.