cloud_chat_agent_metrics, for a single team on a single day rather than a single agent.
One row is
one team, one day
Delivery
Rewritten daily
Columns
25
Where it lands
snapshot_date= partition only, and check for _SUCCESS before you do, as
described in bucket layout.
Columns
bigint
Internal warehouse key. Not stable between deliveries — the row is identified by
team_id plus metric_date.varchar(36)
Identifier of the workspace the team belongs to.
varchar(256)
Id of the tenant.
NULL for rows with no tenant mapping.varchar(256)
Name of the tenant.
NULL for rows with no tenant mapping.bigint
Join key. The team. Matches
team_id on cloud_chat_conversations.varchar(255)
Name of the team.
date
The day the metrics cover. Together with
team_id this is the grain of the table.bigint
Conversations created that day and assigned to this team.
bigint
Conversations this team resolved that day.
double precision
Total wall-clock minutes to resolution across
tickets_resolved_assigned. Divide by that count for an average.double precision
The same total, counting only working hours.
double precision
Total minutes conversations were actively handled.
double precision
The same total, within working hours.
double precision
Total minutes customers spent waiting on this team.
double precision
The same total, within working hours.
bigint
Of the conversations resolved that day, how many the customer came back about within 24 hours.
bigint
Survey responses received on this team’s conversations.
bigint
How many of those were positive. Divide by
csat_responses for a satisfaction rate.bigint
Conversations where this team sent the first reply.
numeric
Total minutes to first reply across those conversations.
bigint
Conversations where this team sent the first reply after an AI agent handed the conversation over.
numeric
Total minutes to first reply on those conversations.
numeric
The same total, within working hours.
timestamp
When the datamart last wrote this row.
date
Partition column. Date of the delivery that wrote this file, in
YYYY-MM-DD.