Predicting returns to cut reverse-logistics cost for a retailer
Online Retailer — a retail organisation — engaged Skillikz on returns prediction: Models that flag likely returns and cut their cost. This case study sets out the business challenge, the AI-led approach we took, the technologies involved and the measurable outcomes delivered over 5 months.
High return rates eroded margin and clogged reverse logistics, with no early signal of which orders would come back.
We built return-likelihood models and proactive interventions — fit guidance, packaging and routing — on an AI-ready data platform.
Reverse-logistics cost fell 17% as likely returns are flagged early and headed off with better guidance.
The AI services behind this outcome
A project like this draws on a focused set of Skillikz services — from first assessment to a working pilot and a clear path to scale.