Careem (Uber) · Super App · Platform Growth · 2024
Twenty-two services. Eighty percent of customers using one. The problem wasn't the product, it was that nobody knew the rest of it existed. I built the business case from raw data, got buy-in across Food, Groceries, and Engineering, and designed a contextual cross-sell system embedded in the ride journey that shifted average service usage from 1.5 to 2.7 per user and doubled weekly food order frequency.
| Metric | A: Modal | B: Winner | C: Notification |
| Conversion Rate | 18% | 34% | 8% |
| Anxiety (0–10) | 8.2 | 2.1 | 3.5 |
| Browse Time (sec) | 12s | 48s | 6s |
| Engagement (NPS) | +24 | +72 | +8 |
"Users accepted interruption when ride status remained visible and immediate. Option B's persistent ride bar reduced cognitive load, enabling 4x longer browse time and 1.9x higher conversion than Option A, despite similar interruption level."
The Approach
I initiated this project from zero, no brief, no request. I saw the gap in the data, built the case, and brought the right people to the table.
Proactive opportunity identification, Analysed repeat journey data, location signals, and order timing patterns to identify the highest-leverage moment for cross-service exposure: the ride waiting screen.
Cross-functional coalition building, Built and sold the business case to stakeholders across Food, Groceries, and Engineering. Secured resource commitment before a single screen was designed.
Contextual cross-sell experience, Designed bottom-sheet surfaces that appeared once a ride was confirmed. Customers browsed food or grocery options during their wait, ordered on the way, and arrived home to their delivery. Timing and relevance were everything.
Minimised ride-status component, Solved the critical anxiety problem: interrupting a ride journey without losing ride context. I designed a new persistent ride-status bar for the design system that kept the customer's ride visible while they browsed other services. Testing confirmed it significantly reduced cognitive load.
Rapid prototype validation, Tested with 8–12 customers across multiple prototype iterations, identifying the optimal placement, timing, and content hierarchy for maximum conversion without disruption.
"The car waiting screen was dead time. Two minutes of a customer staring at a moving dot. I turned it into the highest-converting surface on the platform."
The Outcomes
The ride journey went from a single-service experience to the platform's most powerful discovery engine.
20% uplift in food orders within 3 days of first cross-sell exposure.
Weekly food order frequency doubled, a direct result of contextual cross-sell appearing at the highest-intent moment in the journey.
Platform breadth fundamentally shifted. Customers who previously used one service began exploring the super-app.
Direct revenue uplift across Food and Grocery verticals, proving the super-app model works when discovery is designed into the journey.
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