Redesigning Jumia’s Empty Cart to Increase Average Order Value (AOV)
Transforming a static technical dead-end into an adaptive recovery hook for Africa’s largest e-commerce marketplace—designed, coded, and deployed as a live prototype.
Product Designer
Role
2 Weeks
Duration
Figma, Jitter, ChatGPT, Cursor, Vercel
Tools
Background
Across e-commerce, an empty cart is not just a status message; it is a critical re-engagement touchpoint for high-intent shoppers. However, Jumia, Africa’s largest online marketplace treats its empty cart as an operational dead end, leading to abandoned session drop-offs, hence, lost revenue. The objective of this project was to convert this zero-state drop-off into an automated shopping guide that sustains browsing momentum, increases recovery rate, and lifts Average Order Value (AOV).
WHY FOCUS ON THE MOBILE APP AS AGAINST THE WEB APP?
The vast majority of transactions occur on mobile devices across emerging markets where network speed and session momentum are paramount.
Problem
Generic Homepage Redirects
Jumia’s legacy architecture reduced the empty cart to a bare status check and a generic “Start Shopping” button that dumped users back to the root homepage, stripping away all shopping context.
Blank Guest States
Unauthenticated visitors were met with a blank screen devoid of localized discovery hooks (e.g., “Trending in Lagos”, “First-Time Buyer Favorites”), forfeiting instant intent capture.
Passive Logged-In Wishlist
While the app displays basic “recently viewed” or “wishlist” items for logged-in users, it lacks a deep personalized discovery engine. It fails to leverage high-conversion context clues—such as localized market data (“Trending in Lagos”) or behavioral segmentation (“What first-time buyers purchased”)—to effectively re-engage users.
Research
Competitive & Preference Validation
Benchmarked against global e-commerce leaders (AliExpress, Amazon, Shein, Temu) operating in the region and validated through preference testing with 4 high-frequency e-commerce shoppers, proved that users favor contextual recovery blocks over static system feedback. Secondary data corroborates this approach: dynamic recovery hooks drive documented conversion lifts of +9.5% and ARPU gains of up to +88%.
Research
Secondary Market Research
In addition, secondary market research corroborates this approach: implementing behavior-driven recommendations was proven to lift mobile conversions by +9.5% for Ecosa, boost average revenue per user by +88% for ISZI, and transform dead ends into high-converting channels yielding a 25% cart conversion rate for Balparmak.
Proposed Solution
Personalized Page Routing
Split the layout strategy based on user type. Returning users see personalized Wishlist and Recently Viewed items to recover their session, while new visitors see Trending Deals to kickstart discovery.
Smooth In-Page Navigation
Replaced the generic “Start Shopping” button with a “Shop Deals” primary CTA. Instead of kicking users back to the homepage, it acts as an anchor link that smoothly jumps them down to the active product filters on the same page.
High-Urgency Badges
Added behavioral micro-tags like PRICE DROP, LIMITED STOCK, and HOT DEAL to catalog recommendations. This creates instant urgency and encourages users to checkout items they previously showed interest in.
Polished UI
This solution was developed and deployed as a dual-state interactive web application using Cursor, Figma MCP, and Vercel.
Impact
Transforming Dead Ends into Growth Hubs
By pairing anchor-link navigation with behavioral urgency tags, the design preserves browsing momentum, recaptures lost checkout intent, and directly defends Customer Acquisition Cost (CAC).
Zero-Tech-Debt Implementation Feasibility
Solved the drop-off bottleneck strictly within Jumia’s existing merchant parameters and technical foundations—eliminating the need for database migrations, backend refactors, or catalog asset restructuring.
Key Takeaways
The easiest thing to do in an unsolicited redesign is tear everything down, chase visual trends from apps like Shein or Temu, and produce flashy dribbble-style shots that could never survive real-world production. The harder—and far more valuable—exercise was practicing restraint. By intentionally restricting myself to Jumia’s existing catalog rules and visual foundations, I had to rely entirely on information hierarchy, cognitive load reduction, and behavioral urgency to drive conversion, rather than relying on cosmetic overhauls.
