Case Study: Allopneus achieves a 15% sales increase with Kameleoon's predictive targeting

Allopneus increases sales by 15% with predictive targeting

Allopneus, France’s online leader in tire sales (about 50% market share and over 1 million monthly visitors), wanted to grow average cart value and customer numbers within its high‑value "frequent driver" segment (drivers >24,000 km/year or multi‑vehicle owners). The challenge was to identify these visitors before purchase and target only the right users so an expensive free home‑mounting offer wouldn’t cannibalize margins.

Allopneus deployed Kameleoon’s machine‑learning predictive targeting, training models on clickstream, purchase history, geo, device and other signals, and ran a three‑week learning phase before showing the incentive to users with a 52–60% predicted probability (≈21% of scored visitors). The campaign delivered a 48.1% increase in the share of frequent drivers among buyers, a 15.7% rise in average cart value, no drop in overall conversion rate, and a 15% sales increase for the targeted segment.

Allopneus

Bruno Hétier

Head of Marketing