What it measures
% of customers lost in the period
The KPI only flags a customer as 'lost' after a 90-day inactivity window, confirming a revenue loss that has already occurred over the preceding quarter.
Business impact
- Increased 'chaos tax' from inefficient sales cycles, as onboarding new, smaller customers to replace established ones increases the administrative load on customer service and finance for lower returns.
- Erosion of weighted distribution and baseline volume, forcing the supply chain to hold a less predictable inventory position and increasing the risk of SLOB for delisted SKUs.
- Concentrated churn in a key channel or with a specific product line signals a value proposition failure, triggering a formal category review and putting the entire listing at risk.
Formula
(Lost clients / Total clients at start) x 100Grain
One row per customer sales order line — customer × product × site × date
Inside the Implementation Pack
A preview of what's actually built for this KPI — extracted from the real Implementation Pack, not a mockup.
This is the primary ratio the pack's other measures build on — trend, rank, and period-comparison variants, all on Fact_Customer_Order_Line. It uses VAR/RETURN to keep the logic readable instead of one giant nested expression.
Fact_Customer_Order_Line— 6 mandatory columns — qty ordered, customer key, ...Dim_Customer— key + nameDim_Product— key + nameDim_Site— key + nameDim_Date— Auto-generated calendar table — no customer data required
Full field-by-field data contract, in 4 SQL dialects (SQL Server, Snowflake, Databricks, BigQuery), ships in the pack.
| Target | 0.08 — performance considered compliant at or below this line |
| Warning | 0.16 — amber alert — triggers a review |
Both live in one Excel tab — change them, refresh the report, done. No DAX editing needed.
Everything you need to build Customer Churn Rate in Power BI — dimensional model, DAX measures, SQL views, and a food-industry demo dataset.