The Customer Segmentation Analytics table provides performance and behavior metrics for customers within selected segment instances around a chosen pinned event date. It includes time-bounded revenue and AOV, purchase frequency, product/campaign/ad breakdowns, geographies, and 30-day list dynamics (growth, attrition, persistence, and loyalty). Query this table to measure how a segment performs before and after a snapshot, and to understand what products and channels drive that performance. Learn more about customer retention and customer segmentation.

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Key Concepts
Pinned Event Date

The anchor date used to compare “before” vs. “after” performance for segment instances.

Instance Event Dates

instance_event_date_start / instance_event_date_end → Filters the segment instances (runs/snapshots) used to build the customer list.

Secondary Event Dates

secondary_event_date_start / secondary_event_date_end → Filters joined activity pulled from other tables (currently Orders & Pixel Orders).

Window Lengths

Columns labeled 7_day_ or 30_day_ use default windows of 7 days or 30 days relative to pinned_event_date. To view default queries, click the column ID in the left panel of the SQL Builder.

To change the window size (e.g., 3 days, 14 days, 60 days), update the formula interval and rename the alias for clarity.

Performance Tips

Query one derived metric per request. Combining many derived metrics in a single query can lead to slower performance and heavier resource usage.

Use smaller date ranges to avoid heavy queries.

Parameters

Parameters can be used to customize and filter the data in the table, and are applied before aggregation

Title	ID	Type	Description
Instance Event Date End	`instance_event_date_end`	parameter	End of the segment instance window. Filters which segment instances (runs/snapshots) to include when building the customer list. Use with `instance_event_date_start`.
Instance Event Date Start	`instance_event_date_start`	parameter	Start of the segment instance window. Filters which segment instances (runs/snapshots) to include when building the customer list. Use with `instance_event_date_end`.
Pinned Event Date	`pinned_event_date`	parameter	The anchor date used to compare before/after segment instance windows.
Secondary Event Date End	`secondary_event_date_end`	parameter	End of the joined activity window. Filters joined activity pulled from tables other than the Customer Segmentation table (e.g. Orders, Pixel Orders). Use with `secondary_event_date_start`.
Secondary Event Date Start	`secondary_event_date_start`	parameter	Start of the joined activity window. Filters joined activity pulled from tables other than the Customer Segmentation table (e.g. Orders, Pixel Orders). Use with `secondary_event_date_end`.
Segment ID	`segment_id`	parameter	The unique identifier for a segment. Example value: `64b8f144256b30501b2ea1e0`

Dimensions

Dimensions are immutable properties that can be used for grouping data

Title	ID	Type	Description
Customer Identity	`customer_identity`	string	The identity of the customer in the segment (can be `email` or `customer_id`). Example values: `67b076c419252e53fbc0841g`, `[email protected]`
Customer Identity Type	`customer_identity_type`	string	The type of identity the segment uses for this customer. Example values: `email`, `customer_id`
Instance Event Date	`instance_event_date`	date	The event date used for data from tables other than the Customer Segmentation table (e.g., Orders table, Pixel Orders table). Used in membership/instance joins. Formatted according to the ISO 8601 international standard. Example value: `2025-01-19 22:21:04`
Segment Name	`segment_name`	string	The human-readable name of the segment. Example values: `Fourth of July Sale`, `At least 3 orders`, `Jan Non Recent Active`

Derived

Derived fields are metrics that are pre-calculated using multiple measures or advanced formulas

Title	ID	Type	Description
30-Day List Persistence	`30_day_list_persistence`	formula	Count of customers who remained in the segment for at least 30 days (were active both 30 days before the `pinned_event_date` and on the `pinned_event_date`).
30-Day Loyal Customers	`30_day_loyal_customers`	formula	Number of highly engaged customers who were active on both the start and end dates of a 31-day period and maintained 95% activity frequency (active on at least 29 out of 31 days)
30-Day List Attrition	`30_days_list_attrition`	formula	Number of customers who were not in the segment 30 days before the `pinned_event_date`, and joined the segment at the `pinned_event_date`.
30-Day List Growth	`30_days_list_growth`	formula	Number of customers who were in the segment 30 days before the `pinned_event_date`, and left the segment on the `pinned_event_date`.
30-Day Recent Joiners	`30_days_recent_joiners`	formula	Number of customers who were not in the segment 30 days before the `pinned_event_date` but joined the segment within the last 29 days leading up to the `pinned_event_date`.
Ad IDs (Last 7 Days)	`ad_ids_last_7_days`	formula	Ad IDs for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Ad IDs (Next 7 Days)	`ad_ids_next_7_days`	formula	Ad IDs for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
AOV (Last 7 Days)	`aov_last_7_days`	formula	Average order value for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
AOV (Next 7 Days)	`aov_next_7_days`	formula	Average order value for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Campaign IDs (Last 7 Days)	`campaign_ids_last_7_days`	formula	Campaign IDs for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Campaign IDs (Next 7 Days)	`campaign_ids_next_7_days`	formula	Campaign IDs for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Channels (Last 7 Days)	`channels_last_7_days`	formula	Pixel-attributed channels for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Channels (Next 7 Days)	`channels_next_7_days`	formula	Pixel-attributed channels for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Cities (Last 7 Days)	`cities_last_7_days`	formula	Shipping cities for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Cities (Next 7 Days)	`cities_next_7_days`	formula	Shipping cities for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Countries (Last 7 Days)	`countries_last_7_days`	formula	Shipping countries for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Countries (Next 7 Days)	`countries_next_7_days`	formula	Shipping countries for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Order Tags (Last 7 Days)	`order_tags_last_7_days`	formula	Order tags for customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Order Tags (Next 7 Days)	`order_tags_next_7_days`	formula	Order tags for customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Product IDs (Last 7 Days)	`product_ids_last_7_days`	formula	Product IDs purchased by customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Product IDs (Next 7 Days)	`product_ids_next_7_days`	formula	Product IDs purchased by customers from the selected segment instances in the 7 days after the `pinned_event_date`.
Purchase Frequency (Last 7 Days)	`purchase_frequency_last_7_days`	formula	Average number of orders per customer from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Purchase Frequency (Next 7 Days)	`purchase_frequency_next_7_days`	formula	Average number of orders per customer from the selected segment instances in the 7 days after the `pinned_event_date`.
Revenue (Last 7 Days)	`revenue_last_7_days`	formula	Total order revenue generated by customers from the selected segment instances in the 7 days prior to the `pinned_event_date`.
Revenue (Next 7 Days)	`revenue_next_7_days`	formula	Total order revenue generated by customers from the selected segment instances in the 7 days after the `pinned_event_date`.