Identifying friction points and designing a streamlined journey that helps users move from need to booking more efficiently.
Mobile App | Regional Expansion (UAE, KSA, Qatar)
JustLife, a regional home services super app, was experiencing a critical leakage at the top of the funnel. New users were downloading and signing up, but 81% weren't completing their first booking. The onboarding experience was confusing, service discoverability was low, and users had no clear entry point into the marketplace.
My mandate: Redesign the onboarding and discovery experience to increase conversion, reduce time-to-booking, and create a scalable foundation for expansion into new markets.
Analysis of 50,000 user sessions revealed a systemic problem: users weren't making it through their first booking journey.
80 services listed alphabetically created cognitive overload. Users couldn't mentally map "AC Cleaning" to their need ("My AC is dirty").
User interviews revealed mental models were intent-driven: "I need cleaning," "I need repairs," not "I need to find AC cleaning."
30% of drop-offs happened before users tapped their first service. No guidance, no "here's what you can do" moment.
A guided 3-step onboarding showing Location → Top Services → Quick Recommendation could reduce friction by 30% minimum.
Every user saw the same 80-service list. No "For You," no booking history, no location-based recommendations.
Analytics showed "Most Booked in Your Area" had 3x higher engagement. Personalization was a lever we could pull.
Search was keyword-based, not contextual. Location, availability, and price filters were hard to find.
Competitors (TaskRabbit, Helpling) showed smart search with location + availability filters drove 4x higher conversion.
Based on reviewing the existing experience and evaluating the booking journey, I identified the following opportunities:
Users had to browse through multiple categories before finding the service they needed, increasing friction early in the journey.
Users often think in terms of problems they want solved ("My AC isn't cooling") rather than specific service names ("AC Cleaning").
The experience offered limited guidance for first-time users, making it difficult to understand available services and next steps.
The experience presented similar content to all users despite differences in location, preferences, and service needs.
Key information such as ratings, reviews, popularity, and service credibility could be surfaced more prominently to help users book with confidence.
Instead of incremental tweaks, I proposed a fundamental redesign of the discovery experience around three pillars. Each pillar addressed a specific leak point in the funnel.
30% of users drop-off before their first action. A guided experience that reduces cognitive load could unlock ~15% churn reduction.
-30% onboarding friction
Alphabetical service listing doesn't match user mental models. Reorganizing around intent could improve discovery by 50%+.
+78% services explored
Impersonal experience means high CAC for acquisition + low LTV. Personalization could multiply engagement by 2-3x.
+41% impressions, 3x CTR
50K session analysis, 15 user interviews, 5 competitive reviews → Problem hypothesis
5 design concepts, stakeholder alignment, 8-category taxonomy definition
60+ wireframes, interactive prototypes, design system with 50+ components
3 rounds of testing with 10 users each, 5 A/B tests, iterative refinement
Final specs, developer handoff, 4-week rollout (20% → 50% → 100%)
9/10 users completed onboarding without help (vs. struggling with old experience). Average time to first service tap: 28 seconds (down from 2+ minutes). Users reported clearer categories, less overwhelming.
8/10 users completed task without help (old design: 5/10). Category-based navigation was 60% faster than alphabetical. Users: "This makes sense. I can find what I need."
| Test | Variant A | Variant B (Winner) | Uplift | Decision |
|---|---|---|---|---|
| Home Layout | Carousel | Grid ✓ | +23% engagement | Grid allows more discovery at once |
| Service Cards | Small imagery + text | Large imagery ✓ | +18% CTR | Visual hierarchy wins in mobile |
| Onboarding | Mandatory | Skippable ✓ | +34% completion | Respect user agency |
| 'For You' Position | Below categories | Above categories ✓ | +41% impressions | Personalization is hero content |
| Filter Interface | Sidebar (tablet UX) | Bottom sheet ✓ | +28% filter usage | Mobile-first interaction model |
Design Principle: No decision was made on opinion. Every significant UX choice was validated through testing. This data-driven approach gave stakeholders confidence and proved the ROI of design.
The redesign launched 6 weeks after initial research and was rolled out to 100% of users over 4 weeks. Here are the results:
| KPI | Baseline | Post-Launch | Change | Business Value |
|---|---|---|---|---|
| Sign-up to 1st Booking | 19% | 25.4% | +34% | 6% lift = 2,700+ new monthly bookings |
| Services Explored/Session | 2.3 | 4.1 | +78% | Higher engagement, more discovery, more bookings |
| Time to First Booking | 8.2 min | 4.7 min | -43% | Reduced friction = lower abandonment |
| Booking Value (AOV) | $24.50 | $28.30 | +15.5% | Better service discovery = higher value orders |
| Category CTR | 14% | 32% | +128% | Categories > Alphabetical listing |
| 'For You' CTR | — | 38% | +3x baseline | Personalization is engagement gold |
💚 Insight: Retention improved across all cohorts. Better onboarding + discovery = users return more frequently.