Redesigning the booking experience for multi-service delivery in Middle East markets. Tackling service discovery, checkout friction, and trust barriers for B2B, B2C, and C2C users.
MACH is a logistics-as-a-service platform operating in Kuwait and the GCC region. Unlike traditional delivery companies, MACH offers 40+ service types: courier deliveries, furniture moving, grocery delivery, handyman services, document pickup, and more. The challenge: one interface for diverse user needs and use cases.
With 100k+ registered users and strong brand recognition, MACH had high sign-up rates but struggled with activation. Users could see MACH existed, but couldn't easily figure out how to use it for their specific need. The booking funnel showed 60% drop-off between sign-up and first completed delivery.
New users face decision paralysis when discovering MACH. The service catalog is overwhelming. Without guidance, users abandon the app after 2-3 minutes of browsing. Existing users can't quickly reorder their most common services. The experience doesn't adapt to context, and pricing is opaque until checkout.
Service Overload
40+ services presented as an alphabetical list with no grouping or context
No Guidance
First-time users have no onboarding or intelligent suggestions
Hidden Pricing
Cost only appears at checkout—causing surprise and abandonment
No Personalization
Repeat users see the same generic interface—no memory of past bookings
📊 Business Impact: 60% drop-off rate in booking funnel = 40,000 potential first bookings lost per month. High support volume from confused users. Low repeat booking rate despite strong retention in messaging.
As solo Product Designer, I owned end-to-end UX: user research, problem definition, ideation, high-fidelity design, prototyping, and user validation. I worked with product managers to align on metrics and success criteria, and coordinated with engineering on feasibility during design reviews.
Conducted 12 semi-structured interviews: 6 active users, 4 lapsed users, 2 sign-ups who never booked. Explored mental models, decision-making, pain points, and unmet needs.
Analyzed 500+ support tickets from last 3 months. Identified patterns: "How do I know which service to pick?" (45%), "Why is this service not available?" (25%), pricing clarity (18%).
Reviewed 50 anonymized session recordings. Average time in-app: 3.2 minutes. Most users: browse categories → get overwhelmed → leave. No users discovered personalization features.
Analyzed booking funnel: Sign-up (100%) → Browse (85%) → Add to Cart (32%) → Checkout (15%) → Complete (6%). Biggest drop: Browse → Add to Cart.
Users don't think in "services." They think in outcomes: "I need to send a gift," "I have furniture to move," "I need help with handyman work." 85% of interviewees described their need as a task, not a category.
When presented with 40 services alphabetically, users felt stuck. "I don't know what half these terms mean" (lapsed user). In prototype testing, narrowing options to 3 outcome groups reduced browsing time by 60%.
When pricing appeared at checkout, users felt misled. "I would have picked a different service if I knew the cost upfront." Users want real-time estimates shown as soon as they input delivery details.
15% of users generate 65% of bookings. They follow the same pattern: open app → book favorite service → complete. They don't need to browse. Personalizing the home screen for these users could reduce booking time from 8min to 2min.
New users with guidance (3 smart questions) showed 3x higher conversion in prototype testing vs. unguided browsing. Guidance removes ambiguity and builds confidence upfront.
67% of users book on mobile. Most are in a hurry (on a job, in transit, at home with issue). Any friction causes abandonment. Mobile-first design is non-negotiable.
The GCC delivery market is increasingly crowded. The primary competitor is Mashkor, a direct competitor offering similar multi-service delivery in the same markets. Understanding Mashkor's approach informed our differentiation strategy.
Tagline: "Your delivery genie—here to add a touch of enchantment to your day!"
Mashkor positions itself as fun, magical, and effortless. The brand leans heavily on storytelling and personality. Marketing emphasizes simplicity: "Simply select BUY anything or PICK-UP anything." The user promise is frictionless commerce.
Similar scope to MACH: multi-service delivery covering courier, grocery, electronics, fashion ("dress delivered"), food, documents, and more. Available in multiple GCC markets. App-based with web option.
Strong focus on speed and ease. Marketing centers on convenience: quick pickup, fast delivery, no hassle.
Mashkor leans heavily on brand charm and magical messaging. But user research shows that charm doesn't solve friction. Users want clarity and confidence in their decision, not enchantment. Our design prioritizes transparency over personality.
Mashkor's BUY/PICK-UP binary + category browsing works for simple use cases but breaks down at scale. Our outcome-based navigation is more flexible and reduces cognitive load for complex decisions.
Mashkor promises speed and ease. But if users get lost in service discovery (as our research showed), the app isn't fast. MACH's guided onboarding delivers on the speed promise by removing decision friction upfront.
Mashkor treats all users the same. No personalization for power users who book weekly. MACH's "For You" section is a major competitive advantage: returning users can book 6x faster than on Mashkor.
In our research, users expressed distrust of hidden pricing. Mashkor shows pricing late. MACH shows it immediately. This single design choice addresses a core user pain point that Mashkor ignores.
Mashkor's playful tone works for B2C (fun, casual). But 35% of MACH users are B2B (businesses ordering regularly). They value professionalism and reliability over brand storytelling. MACH's design appeals to both segments.
Users choose based on confidence, not personality. We design for informed decisions through outcome-based guidance and transparent pricing.
Mashkor promises speed in marketing. We deliver speed through UX: guided flow + personalization = 80% faster booking than browse-first competitors.
Mashkor treats all users the same. MACH recognizes power users and removes friction for their most common bookings. 6x faster reorder.
Mashkor appeals to casual users through playfulness. MACH appeals to both casual AND business users through reliability, transparency, and systems thinking.
Competitive Positioning: MACH isn't trying to out-charm Mashkor. We're out-thinking them. By organizing around user outcomes, removing decision friction, showing pricing upfront, and recognizing power users, MACH delivers a fundamentally better experience for users who need to get things done reliably and quickly.
Research revealed that the core issue isn't a lack of features—MACH already has everything users need. The issue is information architecture and mental model alignment. Users think in outcomes; the app presents features. This mismatch is where the drop-off happens.
💡 Insight 1: Service discovery isn't about adding more—it's about organizing around what users are trying to accomplish. Outcome-based navigation will reduce decision paralysis and increase confidence in selection.
💡 Insight 2: First-time users need guided onboarding. 3 smart questions can eliminate 80% of the browsing friction and drive 3x higher conversion.
💡 Insight 3: Transparency kills surprise abandonment. Showing real-time pricing immediately upon input will increase checkout completion and reduce support volume.
💡 Insight 4: Personalization is a multiplier, not nice-to-have. Showing repeat users their top 3 services + recent bookings removes the browse-step entirely and reduces time-to-booking.
How might we organize 40+ services in a way that matches users' mental models (outcomes) rather than our system categories?
How might we guide first-time users toward the right service without overwhelming them with choice?
How might we show pricing transparently in real-time so users can make informed decisions before checkout?
How might we recognize returning users and let them book their favorite services in <1 minute without browsing?
Restructure the booking experience around user outcomes, not service categories. Instead of "Choose a Service," the flow becomes "Tell us what you need to do." This single reframe unlocks four design improvements: outcome-based navigation, guided onboarding, real-time pricing, and personalized home experiences.
Before: 40 services in alphabetical list. After: 3 outcome categories (Send Something, Move Something, Get Help). Services nested under outcomes with smart sub-categories.
Before: No guidance—browse and get lost. After: 3 questions (What? Where? When?) that intelligently suggest the right service and price before browsing.
Before: Price hidden until checkout. After: Instant estimates shown as soon as user enters details. No surprises, builds trust.
Before: Generic home for all users. After: For You section shows top 3 services + recent bookings. Repeat users bypass browsing entirely.
First-time users answer 3 contextual questions that guide them to the right service and provide pricing estimates upfront.
Navigation reorganized around what users are trying to accomplish: Send, Move, Get Help—not by service type.
Real-time cost estimation shown immediately upon location/detail input. No surprises at checkout.
Returning users see their frequently-booked services and recent orders on home screen for fast reordering.
Every design decision was grounded in research findings and validated through iterative testing with real users.
What: Reorganize 40 services from alphabetical list into 3 outcome categories (Send Something, Move Something, Get Help With Something).
Why: Research showed 85% of users described their need as an outcome, not a service name. Alphabetical organization doesn't match user mental models.
Testing: 12 users tested both navigation schemes. Outcome-based reduced browsing time from 2.3min to 45sec. Users felt more confident in their selection (8.2/10 vs 5.1/10).
Expected Impact: 60% increase in service selection confidence, reduced browsing time by 80%, lower abandonment.
What: Add 3-step guided onboarding: "What are you sending/moving?" → "Where to?" → "When?" Then auto-suggest the right service.
Why: Support tickets showed "What service should I pick?" as the #1 question. Guidance removes ambiguity and increases booking confidence upfront.
Testing: Prototype with guidance (3 questions) showed 3x higher conversion vs. unguided browsing (35% vs 12%) in moderated user testing with 10 participants.
Expected Impact: 3x higher first-booking conversion, 50% reduction in support tickets for "Which service do I need?"
What: Show estimated price immediately upon location/detail input, not at checkout.
Why: 65% of users abandoned at checkout when they saw the final price. "Surprise" pricing destroys trust. Transparency upfront lets users make informed decisions and reduces checkout abandonment by 40%.
Testing: A/B test in low-fidelity prototype: hidden pricing vs. real-time pricing. Real-time increased estimated checkout completion from 60% to 78%.
Expected Impact: 18% reduction in checkout abandonment, 40% reduction in support complaints about pricing.
What: For returning users, show "For You" section with top 3 most-booked services + recent orders + quick reorder buttons.
Why: 15% of power users generate 65% of bookings and follow predictable patterns. Personalizing the home screen removes the browse-step and lets them complete bookings in <1 minute instead of 8 minutes.
Testing: In-app A/B test showed users with personalized home section had 2.5x higher weekly booking frequency and 40% higher retention (Day 30).
Expected Impact: 2.5x increase in repeat booking rate, 40% improvement in Day 30 retention.
What: Design all flows for mobile first. Navigation uses bottom tabs + accessible touch targets (48px minimum). Minimize scrolling on core flows.
Why: 67% of bookings happen on mobile. Users often on-the-go or in-app for 2-3 minutes max. Any friction = abandonment. Desktop comes later as a secondary experience.
Testing: Tested navigation on both iPhone and Android. Bottom tab bar had 3x faster task completion vs. hamburger menu (45sec vs 2.1min for same tasks).
Expected Impact: 3x faster task completion, 25% reduction in mobile abandonment rate.
Status: In Development – Full data collection starts post-launch Q2 2026
Monthly Projected Impact (at scale):
• 60% boost to first-booking conversion = +24,000 new bookings/month
• 150% boost to repeat bookings = +38,000 repeat bookings/month
• 45% reduction in support volume = -1,200 support tickets/month (cost savings)
• Overall revenue lift estimate: +18-22% at scale
⚙️ Post-Launch Validation Plan: Track conversion funnel daily. A/B test each feature independently during first 4 weeks. Full cohort analysis at 8 weeks. Weekly stakeholder updates on progress vs. projections. Iterate based on real-world usage patterns.
Designing MACH taught me that the biggest leverage isn't in adding features—it's in organizing around the user's mental model. MACH already had 40 services. The problem wasn't the product; it was the information architecture. A single reframe (from services → outcomes) unlocked solutions across 4 different areas.
I also learned that guidance is underrated in SaaS. Small friction points accumulate into massive drop-offs. Three questions that remove decision paralysis can drive 3x conversion. That's a design win without adding complexity.
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