Once a monitor is created, it begins collecting data automatically from selected sources. This data can then be explored and analyzed to understand conversations, track performance, and generate insights that support business decisions.

Collected conversations can be explored through dashboards and analytics tools to monitor performance, identify trends, and evaluate audience engagement. These insights help teams understand how conversations evolve over time and how audiences respond to different topics or content.

Filters help refine results and focus on the most relevant insights. They can be applied to authors, posts, or engagement metrics, allowing users to analyze conversations from different perspectives. For recurring analysis, filters can be saved and reused to quickly apply the same conditions across different datasets.

Monitors can be updated to reflect changing monitoring needs. Users can modify configurations such as tracked accounts, keywords, or conditions to ensure the collected data remains relevant and aligned with their objectives. Monitors can also be paused or removed when they are no longer needed.

In addition, monitors can be used to create dashboards or live dashboards, allowing teams to track conversations, engagement, and key insights in real time and maintain continuous visibility into performance.

For supported data sources, users can request historical data to retrieve conversations from before the monitor was created and include them in the results. The availability and coverage of historical data depend on the selected data source. This allows organizations to extend their analysis beyond newly collected conversations and incorporate past data when available.

Collected conversations can be summarized using Summary by Luci, which highlights key themes and trends within the data. This helps teams quickly understand large volumes of conversations and focus on the most important insights.