Return Rate Prediction Saves Czech E-Shop Over €100,000 Per Year

The client operated a substantial online store with an extensive product catalogue and needed to identify which items would experience higher return rates before costs accumulated.

Blindspot delivered a quantile regression model customised for each product, enabling prediction of individual item return rates across the full catalogue.

Annual cost savings of 2,500,000 CZK (approximately €100,000). The client gained the ability to detect problematic products early and remove them from the shelf before return costs accumulated.