Customer Purchase Latency is a metric that measures the number of day in-between orders.
If a customer comes in to buy a sandwich every day, their latency is 1 (day). If they come in every Tuesday, it's 7.
Alone, Customer Purchase Latency isn't very actionable because individual customer behavior varies wildly. It's rare to find someone who has a regular, consistent schedule outside of subscriptions.
In aggregate though, you can get a lot of solid information when you measure your entire customer base. By averaging the latency of all of your customers you can get one highly-actionable number (Average Customer Purchase Latency).
This is a measurement of how long it takes a customer to buy again. New customers making their second purchase. Repeat customers making their 10th purchase. It can track them all.
With this metric in mind, you can use it anywhere it's time to nudge a customer to make another purchase. Win-back campaigns are the most valuable use of latency. It can also work well with New Customer Welcome Campaigns or any other gradual re-engagement campaign.
The key is to build the campaign around the latency times. If your latency is 87 days, then around 87 days into your campaign you should be giving customers a reason to buy again.
Average Customer Purchase Latency was actually one of the first metrics I built into Repeat Customer Insights. No one I could find tracked it and still to this day it's under-used by analysis apps and stores. I wish more stores would use the metric instead of just relying on guesses when scheduling campaigns.