Using Average Latency for customer defection detection in Shopify

Recently a Repeat Customer Insights customer was asking about customer defection.

By default, RFM is used for detecting customer defections (specifically, low Recency scores) but other metrics can be used too.

Average Latency is a good next step for defection detection. It can add a finer view on if a customer is active or defected than RFM.

Average Latency is the average delay between purchases and is quoted in the number of days. It’s an average so some customers will have a lower latency (faster reorders) and some will have a higher one (slower).

For defection detection, pick a multiplier and use that as your cut-off. Double the Average Latency is probably a good starting point but you’ll adjust it as you gain experience. For example, if your Average Latency is 40 days then any customer who hasn’t ordered within 80 days of their last order would be considered defected.

The nice thing about metrics like RFM and Average Latency are that they’ll self-adjust. If customers start to order sooner, those metrics will change which will automatically adjust your defection cut-off.

If you’d like to have your Average Latency calculated for your Shopify store, Repeat Customer Insights includes it in its analyses.

Eric Davis

Use cohorts to find out who the best customers are in your Shopify store

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Repeat Customer Insights will automatically group your customers into cohorts based on when they first purchased. This will let you see how the date customers bought would impact their behavior.

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