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// blindspot.ai — production AI

Large Czech E-Shop

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

>€100K
Annual cost savings
Per-product
Quantile regression models
The Challenge

High-Return Products Stayed on Sale Long Enough to Accumulate Significant Return Costs

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.

Our Approach

Quantile Regression Model Predicts the Return Rate of Every Individual Product

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

Results

Over €100,000 Saved Annually by Removing Problematic Products Before Returns Pile Up

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.

Next Steps

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Our team of AI engineers and domain experts will work with you to understand your challenge, design a solution, and deploy it to production.