Testing whether defaulting checkout to a nearby pickup point — instead of home delivery — lowers delivery cost without hurting conversion.
A checkout delivery step that pre-selects the nearest pickup point instead of home delivery, used by an online shopper completing an order, with the single job of measuring whether the default changes what they pick.
The customer — landing on the delivery step of checkout after adding items to the basket. Sessions are randomised into one of two buckets on arrival; a product manager can also force a bucket from the demo screen to inspect each experience.
All sample/mock data, stated explicitly: a mocked geolocation (Nørrebro, Copenhagen), three nearby pickup points with distance, ready-by time, opening hours and saving; one saved home address with an ETA and a €3.50 delivery fee; a fixed €74.90 basket. Session results are stored in the browser only.
Matches this portfolio: light, high-contrast surfaces, rounded cards on a neutral palette, restrained accent colour, no illustration-heavy checkout chrome.
No auth, no payment processing, no real carrier or geolocation APIs, no backend persistence, no basket editing or address book management, no statistical significance engine — the results page reports observed rates only.
Default-to-pickup increases pickup-point adoption and lowers average delivery cost per order, while checkout completion holds within guardrail. Primary metric: delivery cost per order. Secondary: pickup-point adoption rate and time-to-checkout-complete. Randomised at session/customer level.
Control — Home delivery default
Home delivery is pre-selected. Pickup points are listed below it with no incentive copy — today's live behaviour.
Variant — Pickup point default
Nearest pickup point is pre-selected and framed with "Save €1.50 · Ready tomorrow". Home delivery stays one click away.
Built with Lovable from a structured prototype brief (screens, default-logic rules, mock data, explicit states) — the same brief format I use to scope any AI-assisted build.