Mekova
From “Nothing to Wear” to Data-Driven Styling — ~50% Faster Outfit Selection
Problem Framing
“Users don’t lack clothes — they lack visibility, structure, and decision support.”
70% of wardrobe items remain underutilized. High cognitive load in daily outfit decisions. No system to track usage or value. Styling remains manual, inconsistent, and time-consuming. Existing apps felt cluttered with AI recommendations that felt random rather than personalized.
Solution Strategy
Instead of building just a wardrobe app, the approach was to design a “Closed-loop Styling Ecosystem” — shifting fashion from intuition to intelligence.
Digital Closet
Converts physical wardrobe into structured digital inventory. Enables instant recall and filtering. Reduces search time by ~60%.
Outfit Builder
Drag-and-drop outfit creation with real-time visual combinations. Reduces decision fatigue significantly.
Smart Insights
Tracks times worn, calculates cost per wear, identifies underused items. Drives smarter purchasing and reuse behavior.
Planner & Scheduler
Calendar-based outfit planning with occasion-aware styling. Reduces morning decision stress.
Lookbooks
Curated collections and shareable styling boards enabling social and stylist collaboration.
Stylist Marketplace
Connect users with professional stylists. Digital styling services enabling a marketplace revenue model.
Design Approach
Cognitive Load Reduction
Prioritized recognition over recall. Visual-first interactions. Image-first UI for faster cognition vs. text.
Action-Oriented UX
Every screen answers “What can I do next?” with clear CTAs and minimal friction. Progressive disclosure avoids overwhelm.
Data + Emotion
Analytical insights (cost per wear) combined with emotional satisfaction (styled looks). Premium dark theme for fashion-forward feel.
Impact & Outcomes
“His expertise in UX design is unparalleled. Clients and stakeholders loved his approach which is user centric and always easy to understand. Rajesh consistently delivers high-quality work with precision and creativity. He is an expert and global professional.”
— Srinivas Bharath Nalla, CSPO & HR Specialist
Key Decisions & Trade-offs
Chose image-first UI over text-heavy interfaces — faster cognition but higher data management complexity. Tag-driven filtering over hierarchical categories — more scalable but requires careful taxonomy governance. Designed for dual personas (users + stylists) simultaneously, increasing information architecture complexity but enabling the marketplace business model from day one.
Reflection
Mekova is not just a wardrobe app — it’s a behavioral transformation tool. By combining structured data, visual interaction, and personal styling, it enables users to move from confusion to control to confidence. Future opportunities include AI-based outfit recommendations, weather/occasion intelligence, AR try-on, and community-driven styling.