Looker Explore – Customers

Field Picker

CUSTOMERS

Dimensions

Segment DIM

Name DIM

CLV Tier DIM

Region DIM

Tenure Band DIM

Is High Value DIM

Measures

Customer Count MEAS

Avg CLV MEAS

Avg Order Frequency MEAS

High Value Count MEAS

INTERACTIONS

Dimensions

Channel DIM

Interaction Date Month DIM

Measures

NPS Score (Avg) MEAS

Promoter Rate MEAS

Detractor Rate MEAS

SEGMENTS

Dimensions

Segment Name DIM

Tier DIM

Measures

Churn Rate MEAS

Avg Revenue Per Segment MEAS

Visualization

Data

SQL

Bar

Line

Scatter

Table

Query ran in 1.1s — 4 rows

Last run: just now

Avg CLV & NPS by Customer Segment

Results — 4 rows

Segment	Customer Count	Avg CLV	Avg Order Freq.	NPS Score	Churn Rate
Enterprise	842	$112,400	9.4 / yr	74	1.2%
Mid-Market	1,530	$54,800	6.8 / yr	68	3.1%
Growth	1,904	$28,600	4.9 / yr	61	5.4%
At-Risk	545	$11,200	2.1 / yr	38	14.7%
Total / Avg	4,821	$48,200	6.2 / yr	67	3.8%

Show SQL

-- Generated by Looker · bigquery_prod · Explore: customers SELECT customers.segment AS `customers.segment`, COUNT(DISTINCT customers.customer_id) AS `customers.customer_count`, AVG(customers.lifetime_value) AS `customers.avg_clv`, AVG(customers.order_frequency_annual) AS `customers.avg_order_frequency`, AVG(interactions.nps_score) AS `interactions.nps_score_avg`, SAFE_DIVIDE( COUNTIF(customers.is_churned), COUNT(customers.customer_id) ) AS `segments.churn_rate` FROM `customers_prod.customers` AS customers LEFT JOIN `customers_prod.interactions` AS interactions ON interactions.customer_id = customers.customer_id LEFT JOIN `customers_prod.segments` AS segments ON segments.segment_id = customers.segment_id WHERE customers.created_year = 2025 AND (/* RLS filter */ customers.region IN ( SELECT region FROM `customers_prod.user_region_access` WHERE user_email = SESSION_USER() )) GROUP BY 1 ORDER BY 3 DESC LIMIT 500