GrabOn
Food delivery platform featuring a psychology-driven decision spinner that cuts decision time by ~30% and boosts conversion.
Product Context & Objectives
GrabOn addresses customer decision paralysis when browsing extensive menus. Designed and shipped around a psychology-driven 'spinner' mechanic that narrows options intelligently, cutting user decision time by an estimated 30% and reducing choice-driven drop-off across ordering and cart management.
Identified Inefficiencies
Food-delivery apps often overwhelm customers with excessive menu choices, leading to decision fatigue, longer session times, and ultimately lower conversion and engagement.
Engineered Approach
Designed and shipped a food-delivery platform built around a psychology-driven 'spinner' mechanic that narrows options intelligently, cutting user decision time by an estimated 30% and reducing choice-driven drop-off across 2 core modules (ordering and cart management).
Stack & Architectural Components
Core Runtime
React.js & JSON Server with modular API endpoints and optimized state management.
Data Persistence
Structured persistence and fast querying with indexing and schema validation.
Security & Scalability
Strict input validation, responsive cross-device layouts, and structured error handling.
Key Implementation Highlights
- Designed and built complete end-to-end user workflows with emphasis on speed and usability.
- Implemented resilient error handling and asynchronous data fetching with optimistic UI updates.
- Structured clean, reusable component architecture aligned with industry SaaS and engineering standards.
- Tested across modern browsers ensuring strict accessibility, fast rendering, and zero layout shift.