From profile to recommendation
The initial step captures food type, hunger level, time of day and average spend. The home then prioritizes suggestions and allows refinement by proximity, price and delivery.
Case Study · Product Design
Weat — a delivery experience guided by context and preference.
A product concept designed to simplify meal discovery, using personal preferences to turn a broad search into more relevant suggestions and a direct ordering journey.
Context
Reduce the effort between feeling hungry and finding an option that fits.
In delivery experiences, more options do not always mean easier decisions. Weat starts with a simple profile to understand food preferences, hunger level, time of day and price range before presenting suggestions.
The challenge
Avoid an experience based only on long lists and filters while keeping onboarding lightweight.
The proposition
Use quick preference signals to make recommendations closer to user intent and guide the journey to checkout.
Personalization & discovery
Simple preferences to make discovery more relevant.
Order
Essential information when deciding and confirming.
Details, confirmation and tracking
The interface brings together image, price, quantity, restaurant, delivery estimate and notes before the primary action. After submission, a clear confirmation and status line support order tracking.
UX
Decisions for an everyday, recurring experience.
Progressive personalizationA few questions guide the experience without a long setup.
Fast comparisonImage, price, rating, time and distance stay close together.
Contextual CTAPrimary actions evolve with each stage of the journey.
Outcome
A delivery concept that puts user intent before the catalog.
Weat connects preferences, recommendations, dish details and order tracking in a visually consistent mobile journey.
