Where is retail customer churn concentrated by store?
The short answer
Retail customer churn concentrates in stores where many regular customers are slipping past their usual purchase gap. For each store, count customers past 1.5 times their usual gap and still inside your lapse window, then weigh them by annual spend. Ranking stores by at-risk value shows where next quarter's churn will cost most.
Why it matters
Network churn figures hide stores where a new competitor, a staffing change or a refit is quietly pushing regulars away. Ranking stores by at-risk customer value gives store and regional managers a list they can act on while those customers can still be won back.
The question to ask
Copy this into Lexi as written.
What the answer looks like
Illustrative output on sample data
Illustrative example: how Lexi answers this for a sporting goods retailer with 40 stores. It assigns each customer to their main store and flags those past 1.5 times their usual purchase gap.
- Includes customers with three or more purchases in two years.
- Values each at-risk customer at their past year of spend.
What the data shows
9% of active customers are at risk across the network. Three stores sit above 15% and hold $1.9 million in at-risk annual spend.
What it means
Each of the three has a local cause: a new competitor nearby, a store manager who left in the spring and a refit.
What to do
Give each store its own at-risk list and a local offer, starting with the store facing a new competitor.
Want me to push each store's list to Klaviyo?
Frequently asked questions
What is a customer lapse rate?
A customer lapse rate is the share of active customers who pass your lapse window without buying during a period. Measure it each quarter, by store, channel or segment, to see where customers are slipping, and compare it with the same quarter a year earlier to separate trend from seasonality.
Why assign customers to a single home store?
Customers who visit several stores would otherwise count in each one, which inflates at-risk totals and blurs who is responsible. Assigning each customer to the store with most of their spend gives every store a clean list it can act on, while still counting online purchases in the customer's activity.
How do I build a customer churn forecast for next quarter?
Start with customers already past their usual purchase gap, since they are the most likely to lapse next. Apply the share of similar customers who lapsed in the matching quarter last year, and add expected losses from stores with known changes. Check the forecast against actual lapses each month and adjust.