fact_agent_status_changes

Each row is one change of an agent’s availability: going online (available to receive conversations) or offline. Reconstructing the sequence gives you each agent’s connected time and availability patterns.

What questions does it answer?

How many hours was each agent available per day?
When do agents connect and disconnect?
How does team availability align with conversation demand?

Columns

Column	Type	Description
`status_change_id`	Int32	Unique identifier of the change
`company_id`	Int32	Your company (filtered automatically)
`agent_id`	Int32	The agent
`agent_name`	String	The agent’s name
`created_at`	DateTime64	When the status changed
`old_status`	Bool	Availability before the change: `true` = available, `false` = unavailable
`new_status`	Bool	Availability after the change: `true` = available, `false` = unavailable
`synced_at`	DateTime64	When this row was last written/corrected

Example queries

Daily available minutes per agent (interval reconstruction)

SELECT
    agent_name,
    toDate(created_at) AS day,
    round(sum(
        dateDiff('second', created_at,
                 leadInFrame(created_at) OVER (
                     PARTITION BY agent_id, toDate(created_at)
                     ORDER BY created_at
                     ROWS BETWEEN CURRENT ROW AND 1 FOLLOWING))
        * if(new_status = true, 1, 0)
    ) / 60, 1) AS available_minutes
FROM fact_agent_status_changes
WHERE created_at >= today() - 7
GROUP BY agent_name, day
ORDER BY day, agent_name

For most reporting you don’t need to reconstruct intervals yourself — fact_agent_daily already exposes available_minutes per agent per day.

⌘I