Prototypes
Small, working experiments I build to test product ideas — mostly around automation, AI assistance and the Physical-Digital bridge.
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Loyalty essentials that reorder themselves
Customers reorder the same basics — socks, boxers, gym tees — on a predictable cycle, but start from scratch every time. This prototype lets loyalty members opt in per item, defaults every item to a 6-month replenishment cadence, and lets the customer change the account default or override any single item. A one-tap confirm, skip, pause or cancel keeps control effortless. Eligibility is gated to true basics with proven repeat intent, a size-drift guardrail holds the order when a recent return suggests the size changed, and bundling essentials into planned shipments lowers delivery cost.
Pick-Up Point Delivery
Profile-aware next-day last mile via nearby PUDO points
A checkout-style flow that resolves the delivery mode from the customer's saved preference, falling back to the market-level default and finally to home delivery. When pick-up wins, the customer compares nearby parcel shops and lockers on distance, capacity and cut-off time, then books a next-day window — lowering cost per drop while raising first-attempt success.
Instant Return Refund
Loyal customers get instant refund at hand-over scan; others wait for hub check
Returns used to pay out only after the parcel reached the hub and passed QC. This flow refunds loyalty customers the moment the drop-off is scanned; non-loyal or higher-risk returns still wait until the item arrives at the hub and is checked. Gated by loyalty tier caps, return-abuse risk score, item value and return reason.
Checkout Delivery-Option Selector
A/B testing pickup-point defaults at checkout
Home delivery is almost always the default at checkout, even when a cheaper, faster pickup point sits around the corner — so the business absorbs a higher cost per order by default, not by customer preference. This prototype runs two buckets (control with home delivery pre-selected, variant with the nearest pickup point pre-selected), records each session and rolls the outcomes up into a results dashboard: delivery cost per order and pickup adoption against a hard checkout-completion guardrail.