Case Study: Public Desire achieves zero manual reviews, 7% higher approval rate and 10% more international orders with Signifyd

Public Desire drives global expansion through order automation

Public Desire, a Manchester-based fast-fashion footwear brand worn by influencers and shipped to customers worldwide, faced rising fraud as it expanded internationally. Their legacy rules-based fraud tool required manual review on about 12% of orders, slowing fulfillment and still leaving the business exposed to chargebacks and lost revenue.

Partnering with Signifyd brought machine-learning decisioning and a guaranteed liability shift that removed static blockers and automated order review. Since implementation, manual review dropped to 0%, approval rates increased by 7%, international order traffic grew roughly 10% (GMV share rising from 50% to 60%), and peak-season approvals exceeded 99%, enabling safer, faster global growth.

Public Desire

Qasim Akhlaq

Managing Director