The CS Tickets table tracks support ticket lifecycle events with agent, channel, tag, and satisfaction survey data. One row per ticket event (created, closed, reopened).

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Table Guide
What You Can Answer With This Table

How many tickets are being created vs. closed over time? — filter by event_type, group by event_date

How do satisfaction scores vary by agent or channel? — use survey_score, group by assignee_user_name or channel

What products drive the most support tickets? — use products_names, product_ids

What is the revenue at risk from open tickets? — use total_order_value, has_refund

Which support channels generate the most tickets? — group by channel

Before You Query

Required field: event_date

Event-driven grain: Each ticket lifecycle event (created, closed, reopened) generates a separate row. A single ticket may appear multiple times. Filter by event_type to isolate specific events (e.g., ticket-created for new ticket volume).

Order attribution window: The orders, products_names, skus, and related columns include orders placed up to 30 days before ticket creation. Tickets without a linked customer have empty order attribution.

Key Relationships
Table Join Key What the Join Enables
Customers customer_id Customer profile data (lifetime value, total orders, location, marketing consent)

When to Use a Different Table

Need individual message content → CS Messages table. CS Messages stores each message in a conversation; CS Tickets stores ticket-level metadata and lifecycle events.

Need a full event-level audit log → CS Events table. CS Events captures every event type (assigned, unassigned, updated, message-created); CS Tickets only surfaces created, closed, and reopened events.

Need aggregated daily support KPIs → Customer Support Agg Metrics table (BETA). Agg Metrics provides pre-calculated daily response and resolution times without ticket-level detail.

View the full Triple Whale Data Ontology →

Table	Join Key	What the Join Enables
Customers	`customer_id`	Customer profile data (lifetime value, total orders, location, marketing consent)

Dimensions

Dimensions are immutable properties that can be used for grouping data.

Title	ID	Type	Description
Event Date	`event_date`	date	The date the CS ticket event occurred (e.g. the creation date for `ticket-created` events, the closed date for `ticket-closed` events). Based on the shop time zone at the moment of the event (or the user time zone, if no sales platform is connected).
Event Day	`event_date.day`	date	The day the event occurred. Derived from `event_date`.
Event Week	`event_date.week`	date	The Sunday of the week during which the event occurred. Derived from `event_date`.
Event Month	`event_date.month`	date	The month during which the event occurred. Derived from `event_date`.
Event Quarter	`event_date.quarter`	date	The first month of the quarter during which the event occurred. Derived from `event_date`.
Event Year	`event_date.year`	date	The year during which the event occurred. Derived from `event_date`.
Assigned Agent ID	`assignee_user_id`	string	The unique identifier of the assigned support agent. Example value: `161343771`
Assigned Agent Name	`assignee_user_name`	string	The full name of the assigned support agent. Example value: `Jane Doe`
Channel	`channel`	string	The channel through which the ticket was created. Example values: `facebook-comment`, `instagram-mention`, `email`, `chat`
Ticket Closed Date	`closed_at`	timestamp	The time the ticket was closed. Formatted according to the ISO 8601 international standard. Example value: `2019-04-15 08:26:00`
Ticket Created Date	`created_at`	timestamp	The time the ticket was created. Formatted according to the ISO 8601 international standard. Example value: `2019-04-15 08:26:00`
Customer Email	`customer_email`	string	The email address of the customer. Example value: `[email protected]`
Customer ID	`customer_id`	string	The unique identifier assigned to the customer. Example value: `123456789`
Event Type	`event_type`	string	The type of event related to the ticket. Example values: `ticket-closed`, `ticket-reopened`
From Agent	`from_agent`	boolean	True if the event was initiated by a support agent. Possible values: `true`, `false`
Language	`language`	string	The language used in the ticket. Example values: `en`, `it`, `ru`
Ticket Priority	`priority`	string	The priority level of the ticket. Example values: `normal`, `high`
Ticket Status	`status`	string	The current status of the ticket. Example values: `open`, `closed`
Subject	`subject`	string	The subject line of the first message in the ticket. Example values: `4 native ways to sell on TikTok Shop`, `Re: Thanks For Reaching Out To Us!`
Survey Comment	`survey_comment`	string	The customer's feedback from the post-resolution survey. Example value: `Excellent and quick customer service!`
Survey Score	`survey_score`	string	The rating score given by the customer in a post-resolution survey. Example values: `1`, `3`, `5`
Survey Scored Date	`survey_scored_at`	timestamp	The time the survey was scored. Formatted according to the ISO 8601 international standard. Example value: `2019-04-15 08:26:00`
Survey Sent Date	`survey_sent_at`	timestamp	The time the survey was sent to the customer. Formatted according to the ISO 8601 international standard. Example value: `2019-04-15 08:26:00`
Tags	`tags`	record repeated	Tags associated with the ticket, used for categorization. Example value: `[{"id":"174296","name":"GMAIL-PROMOTIONS"},{"id":"585614","name":"auto-close"},{"id":"585616","name":"non-support-related"}]`
Ticket Updated Date	`updated_at`	timestamp	The time the ticket was last updated. Formatted according to the ISO 8601 international standard. Example value: `2019-04-15 08:26:00`