Racing suits are safety-critical garments. Fit isn't just a comfort preference — it affects range of motion, harness compatibility, and FIA compliance. For a small manufacturer selling direct, a wrong size means an expensive remake and a customer who can't get on track.
Existing solutions are static size charts. They required buyers to self-measure across 15+ dimensions, cross-reference an unfamiliar UK sizing system, and make a judgment call with no guidance on which measurements were most constraining.
I designed and built a guided measurement wizard that walks buyers through six body regions — chest, waist and hips, legs, arms and shoulders, and neck and torso — collecting precise inputs one region at a time. Each step pairs the measurement prompt with annotated photography of the actual garment, with numbered callouts keyed to the measurement being taken. An imperial/metric toggle persists throughout. Early exit is available at any step for buyers who have enough data to act.
On completion, a weighted scoring algorithm I wrote ranks every size in the DRVR catalog against the user's full measurement profile. Each input is evaluated against a scaled tolerance range derived from the base size data; any value outside that range accumulates a distance penalty, scaled by a per-measurement weight that reflects how much that dimension constrains fit in practice. The result is a ranked grid of compatibility percentages across the full size run. The selected size view breaks each measurement down individually against its accepted range, making it immediately clear which dimensions are centered, which are at tolerance, and which would be a problem.
The buyer selects a size, submits their order number and contact info, and the fitting record is persisted to Supabase and routed to the LVRY team via SendGrid.
Built with Next.js 14, TypeScript, Tailwind, Radix UI, and Supabase.
