UX Case Study

Point B

The smartest way to get from A to B—anywhere in the world

Role UX Designer
Type Concept
Focus AI + Travel
01

The Problem

"When traveling internationally, how do I know the best way to get around?"

Every region has different transportation options—taxis, ride-shares, trains, buses, ferries, private drivers. But as a traveler, you're left guessing.

Searching online leads to outdated blog posts, misleading ads, and sometimes outright scams. There's no single source of truth that tells you: "Here's what's actually available around you, and here's what locals recommend."

The Confused Traveler faces:
Information Overload — too many sources, conflicting advice Trust Issues — scams, fake reviews, tourist traps Regional Complexity — each country has different options Time Pressure — need answers now, not hours of research
02

Research

I interviewed 8 frequent international travelers to understand their pain points, behaviors, and workarounds when navigating transportation in unfamiliar places.

User Interviews
8 Participants
45 Min Avg Duration
23 Countries Visited
Q1 How do you currently decide which transportation to use?
Q2 Tell me about a time you felt scammed or misled.
Q3 What would make you trust a transportation recommendation?

Observations → Insights

After synthesizing interview data, I identified patterns and transformed raw observations into actionable insights. Below are direct quotes from participants, organized by theme.

Information Sources

Where travelers currently look

"Google results are all ads"
"Hotel staff have partnerships"
"Reddit threads are outdated"
"TripAdvisor has 50+ replies"
"Friend tips are stale"
"YouTube lacks current prices"
"5 apps for one country"
"Airport desk misled me"
Trust & Safety

What creates uncertainty

"Overcharged by taxis"
"Can't tell if legit"
"Wrong car at airport"
"Wife triple-checks everything"
"Dropped at wrong place"
"Driver took longer route"
"Everyone selling something"
"Language barriers"
Decision Friction

What makes choices hard

"What do locals use?"
"Grab, Bolt, Careem..."
"30 min research for $5"
"Book ahead or show up?"
"Is the bus safe?"
"Every blog differs"
"Just tell me the best"
"2am, no energy left"
Affinity Mapping: Pattern Clusters

I grouped observations into thematic clusters to identify core problem areas.

Fragmented Information
12 observations
No single source of truth. Information scattered across outdated blogs, forums, and biased recommendations.
Trust Deficit
9 observations
Fear of scams, overcharging, and unsafe situations. No way to verify legitimacy in unfamiliar places.
Cognitive Overload
8 observations
Too many options, too little energy. Decision fatigue is highest at arrival when stress is already elevated.
Regional Fragmentation
7 observations
Each country has different apps, services, and norms. Knowledge doesn't transfer between destinations.
Synthesized Insights

From 36 observations across 8 interviews, I distilled 6 core insights that would drive design decisions.

01

Local Behavior = Trust

Travelers trust local behavior patterns over commercial recommendations. "What do locals use?" was the most common question. If an app could surface aggregate local behavior, it would instantly build credibility.

Evidence: "I always ask a local first if I can find one"
02

Speed Over Savings

When tired or stressed, decision speed trumps cost savings. Participants would pay more for certainty. The value isn't just finding the cheapest option—it's eliminating the anxiety of choosing wrong.

Evidence: "I'll pay $20 extra to not have to think"
03

Context Changes Everything

Same route, different context = different best option. Time of day, day of week, weather, luggage, group size—all affect the ideal choice. Static recommendations fail because they ignore dynamic context.

Evidence: "The metro is great until it's rush hour with suitcases"
04

Explanation Builds Confidence

Users don't just want to know what to do—they want to know why. Reasoning creates confidence. "Take the train because it's 30% cheaper and twice as reliable at this hour" is more compelling than "Take the train."

Evidence: "If you just tell me 'this is best' I don't believe it"
05

Arrival is the Critical Moment

The airport-to-destination journey is the highest-stress, highest-stakes transportation decision. This is when travelers are most tired, most overwhelmed, and most vulnerable to scams. Win this moment, win the user.

Evidence: "The first 30 minutes after landing are chaos"
06

One App for All Places

Travelers are exhausted by app fragmentation—Grab in Asia, Careem in Middle East, Bolt in Europe. They want a single interface that works everywhere, adapting to local options without requiring new downloads or learning curves.

Evidence: "I have 15 transportation apps I'll never use again"
03

Who We're Designing For

Three distinct traveler archetypes emerged from research—each with different priorities, pain points, and decision-making patterns when choosing transportation.

ES
Archetype 1

The Efficiency Seeker

"I just need to get there fast and reliably."

Demographics
Age 32-55
Travel Type Business / Corporate
Frequency 10-20 trips/year
Budget Expense account
Behaviors
  • Books transportation before landing
  • Prefers apps with saved payment methods
  • Values punctuality over cost savings
  • Often travels alone with carry-on only
  • Checks email during rides
Frustrations
  • Wasted time comparing options
  • Unreliable ETAs that make them late
  • Having to download new apps per country
  • Drivers who take "scenic routes"
  • Payment friction in foreign currencies
Needs from Point B
  • One-tap booking with saved preferences
  • Accurate, real-time arrival estimates
  • Clear "fastest option" recommendation
  • Receipt generation for expenses
  • Reliability ratings front and center
"

"I don't care if the taxi costs $20 more than the bus. I care that I make my 9am meeting. Just tell me the most reliable way to get there."

BE
Archetype 2

The Budget Explorer

"I want the local experience, not the tourist price."

Demographics
Age 22-35
Travel Type Backpacking / Gap year
Frequency Long trips, 3-12 months
Budget $30-50/day total
Behaviors
  • Researches extensively on Reddit/forums
  • Asks locals and hostel staff for tips
  • Willing to take longer routes to save money
  • Enjoys "figuring it out" as part of travel
  • Shares tips with other travelers
Frustrations
  • Tourist prices vs. local prices
  • Outdated blog posts with wrong info
  • Feeling like a target for scams
  • Language barriers at bus stations
  • Hidden fees revealed after booking
Needs from Point B
  • Show what locals actually use
  • Price transparency with no surprises
  • Budget-first sorting option
  • Offline access for areas without data
  • Community tips and recent experiences
"

"I took a $40 taxi from the airport in Bali before learning there's a $2 bus that all the locals use. That $38 could have been two nights at my hostel."

CP
Archetype 3

The Cautious Planner

"I need to know it's safe before I commit."

Demographics
Age 35-55
Travel Type Family vacation
Frequency 1-2 big trips/year
Budget Moderate, planned
Behaviors
  • Plans transportation weeks in advance
  • Reads reviews extensively before booking
  • Prefers pre-arranged airport transfers
  • Travels with children and/or elderly parents
  • Values comfort and air conditioning
Frustrations
  • Uncertainty about vehicle safety standards
  • Not knowing if car seats are available
  • Aggressive drivers at airports
  • Stories of tourists getting robbed
  • Spouse/family anxiety about choices
Needs from Point B
  • Safety ratings and verification badges
  • Family-friendly filters (car seats, space)
  • Photos of actual vehicles
  • Driver background check indicators
  • Ability to share trip details with family
"

"When I'm traveling with my kids, I'm not taking any chances. I need to see reviews, safety ratings, and know exactly who's picking us up before I book anything."

Journey Mapping by Archetype

Each archetype experiences the transportation decision journey differently. I mapped all three to identify where their pain points diverge and where Point B can provide the most value.

Journey Map: The Efficiency Seeker
ES Efficiency Seeker
Pre-Trip
Books car service in advance via email confirmation
"At least that's handled"
Arrival
Looks for driver with name sign
"Where is he? I'm wasting time"
In Transit
Watches GPS, notices driver not taking fastest route
"This is adding 15 minutes"
Arrival
Arrives slightly late, frustrated
"I should have taken the train"
Reflection
Wonders if there was a better option
"There has to be an easier way"
Opportunity: Surface real-time reliability data and fastest route predictions before booking
Journey Map: The Budget Explorer
BE Budget Explorer
Pre-Trip
Spends 2 hours on Reddit researching options
"Is this post still accurate?"
Arrival
Declines taxi offers, searches for bus station
"Everyone's trying to rip me off"
Decision
Wanders airport for 30 min finding cheap option
"Is this bus even going there?"
In Transit
Takes local bus, feels authentic
"This is the real experience"
Reflection
Saved $30 but trip took 2 hours longer
"Worth it... mostly"
Opportunity: Show "what locals use" with current prices and time tradeoffs upfront
Journey Map: The Cautious Planner
CP Cautious Planner
Pre-Trip
Reads reviews, asks Facebook group for advice
"Is this company reputable?"
Booking
Books expensive private transfer "just to be safe"
"Better safe than sorry"
Arrival
Anxiously looks for pre-booked driver
"What if they don't show up?"
In Transit
Kids are comfortable, AC works, feels safe
"Okay, this was worth it"
Reflection
Paid 3x more than needed but family is happy
"I wonder if cheaper was just as safe"
Opportunity: Provide safety verification and family-friendly filters to justify value, not just price
Cross-Archetype Analysis

Comparing the three journeys revealed where Point B can create the most impact.

Efficiency
Explorer
Planner
Primary Pain
Wasted time
Overpaying
Safety anxiety
Decision Trigger
Speed + Reliability
Price + Authenticity
Reviews + Safety
Research Time
5 minutes
2+ hours
1-2 hours
Willingness to Pay
Premium for speed
Minimum viable
Premium for safety
Point B Solution
"Fastest" filter + ETA accuracy
"Local favorite" badge + price transparency
Safety scores + verified drivers
04

Ideation

With research insights in hand, I explored multiple solution directions through structured ideation exercises before converging on the final concept.

Value Proposition Canvas

Mapping user needs to potential product value.

Gain Creators
  • Instant confidence in transportation choices
  • Save money by avoiding tourist traps
  • Travel like a local, not a tourist
  • Avoid scams and overcharging
  • Reduce pre-trip anxiety
  • Discover options they didn't know existed
Pain Relievers
  • Eliminate information overload with curated rankings
  • Remove fear of scams with verified options
  • Bypass language barriers with visual UI
  • Save hours of research per trip
  • One app for all countries
  • Works offline after initial load
Jobs to be Done
  • Functional: Get from A to B safely and affordably
  • Emotional: Feel in control in unfamiliar places
  • Social: Not look like a clueless tourist
  • Functional: Make quick decisions under pressure
  • Emotional: Reduce travel anxiety for family
  • Functional: Stay within budget

How Might We

I reframed insights as opportunity questions to guide brainstorming.

HMW Statements
Trust & Credibility
HMW build trust in recommendations from an unknown app?
HMW verify the legitimacy of local transportation options?
Decision Speed
HMW reduce decision fatigue when options are overwhelming?
HMW help users make confident choices in under 30 seconds?
Local Knowledge
HMW surface local knowledge without requiring local contacts?
HMW show what transportation locals actually use vs. tourist options?
AI & Transparency
HMW make AI recommendations feel helpful, not creepy?

Concept Exploration

I sketched multiple directions before selecting the final approach. Each concept was evaluated against user needs and technical feasibility.

Concept Directions
Rejected
Concept A: Social Forum

Community-driven Q&A where travelers ask and locals answer.

Speed
Trust
Scalability

Too slow for real-time decisions. Relies on community growth.

Rejected
Concept B: Aggregator Only

Simple list of all transport options with links to book externally.

Speed
Trust
Scalability

Doesn't reduce cognitive load. No guidance = same problem.

Selected
Concept C: AI-Ranked + Explained

AI analyzes all options, ranks them, and explains the reasoning.

Speed
Trust
Scalability

Fast decisions + transparency builds trust. Works globally.

Feature Prioritization

Using an impact vs. effort matrix, I prioritized features for the MVP.

Prioritization Matrix
Do First
High Impact / Low Effort
AI Rankings Location Detection Explain "Why" Price Display
Plan For
High Impact / High Effort
Booking Integration Real-time ETAs Multi-language
Nice to Have
Low Impact / Low Effort
Trip History Share Route Dark Mode
Avoid
Low Impact / High Effort
Social Features Gamification
05

The Solution

Point B uses AI to analyze every transportation option in your area—then ranks them by reliability, safety, cost, and local preference. Here's how it all comes together.

Information Architecture

I structured the app around three core concepts: Search (where are you going?), Discover (what are your options?), and Decide (which one is best for you?).

App Structure
flowchart TD
    A[🎯 Point B] --> B[🔍 Search]
    A --> C[📋 Results]
    A --> D[📄 Detail]
    A --> E[👤 Profile]
    
    B --> B1[Destination Input]
    B --> B2[Map View]
    B --> B3[Recent Searches]
    
    C --> C1[Ranked List]
    C --> C2[Filter/Sort]
    C --> C3[AI Badges]
    
    D --> D1[Stats Overview]
    D --> D2[AI Insight]
    D --> D3[Reviews]
    D --> D4[Book/Navigate]
    
    E --> E1[Trip History]
    E --> E2[Preferences]
    E --> E3[Saved Places]
                        

Core Features

Each feature was designed to address a specific user pain point identified in research.

Feature Breakdown
AI-Powered Rankings

Machine learning analyzes multiple data sources—transit APIs, user reviews, local behavior patterns, real-time conditions—to rank options by a composite score.

Addresses: "Too many options, I don't know which to choose"
Explain "Why"

Every recommendation includes a human-readable explanation. "Recommended because it's 40% faster than alternatives at this hour, with 98% on-time rate."

Addresses: "I don't trust recommendations without reasoning"
Local Favorite Badge

Options used primarily by locals (vs. tourists) are flagged with a "Local Favorite" badge, based on usage pattern analysis.

Addresses: "I want to know what locals actually use"
Safety Verification

Options are vetted against safety databases. Verified operators display a trust badge with inspection history and driver background checks.

Addresses: "I need to know it's safe before I commit"
Price Transparency

All-in pricing with no hidden fees. Shows price range, typical fare, and flags when prices are higher than normal (surge, peak, tourist area).

Addresses: "I've been overcharged too many times"
One-Tap Decisions

For returning users, the app surfaces the best option for frequent routes immediately. One tap to confirm and start navigation.

Addresses: "I don't have energy to research when I'm exhausted"

User Flows

I mapped out three core user journeys to ensure intuitive navigation through the app.

Core User Flows
01
First-Time Search

New user searches for transportation to their destination.

1
Open App Welcome screen, value prop
2
Grant Location Enable personalized results
3
Enter Destination Search or tap map
4
View Rankings AI-sorted options
5
Select & Go Confirm and navigate
Target Time: Under 30 seconds to decision
02
Deep Dive

Cautious user wants more details before committing.

1
View Rankings See top options
2
Tap Option Open detail view
3
Read AI Insight Understand "why"
4
Check Safety Reviews & verification
5
Confirm Trip Book with confidence
Target Time: Under 2 minutes with full confidence
03
Quick Action

Returning user takes a familiar route.

1
Open App See recent routes
2
Tap Recent Pre-loaded best option
3
One-Tap Go Instant navigation
Target Time: Under 5 seconds

Design Decisions

Key decisions that shaped the final product.

Design Rationale
Why show AI reasoning?
Research showed users distrust "black box" recommendations. By explaining why an option is ranked first, we convert skeptics into believers. Transparency = Trust.
Why not in-app booking?
MVP focuses on guidance, not transactions. Booking requires complex integrations with 100+ regional providers. Phase 2 will add booking for top partners.
Why the navy/orange palette?
Navy conveys trust and reliability (like financial apps). Orange adds energy and warmth—suggesting adventure without feeling unsafe. Together they say: "Trustworthy travel companion."
Why minimal text in the UI?
Point B is used in countries where users don't speak the language. Icon-heavy design with minimal text ensures usability across all markets without heavy localization.

Visual System

A cohesive design system ensures consistency and establishes the app's trustworthy, travel-forward personality.

Style Guide
Primary Colors
Navy #1E3A5F Headers, Trust elements
Orange #F97316 CTAs, Highlights, AI badges
Secondary Colors
Sky #E0F2FE Backgrounds, Cards
Success #10B981 Confirmations, Positive
Typography
Point B Inter Bold / 32px / -2% tracking
Section Header Inter SemiBold / 20px / -1% tracking
Body text for descriptions and explanations. Inter Regular / 16px / 160% line height
LABEL TEXT Inter Medium / 12px / 8% tracking / Uppercase
Components
JR Yamanote 7 min • ¥170
4.9
AI Pick
Local Favorite
Verified
06

The Experience

Five screens that take travelers from wondering to moving—with confidence.

9:41
POINT B
The smartest way to get around—anywhere in the world.
AI-Ranked Routes
180+ Countries
Real-Time Data
Get Started
Enable location to continue

Welcome

A simple onboarding that immediately communicates the app's value: smart, global transportation guidance. Location permission is requested upfront to enable personalized results.

9:41

Search

A friendly, map-centric interface invites users to enter their destination. The live location tag and detailed map create an immersive, context-aware experience.

9:41
Shinjuku Shibuya
Best Fastest Cheapest
3 options ranked by AI
#2
Taxi Pickup · 2 min away
4.7
12 minDuration
¥1,800Cost
Direct
#3
City Bus #01 Next bus · 8 min
4.2
22 minDuration
¥210Cost
Scenic

Ranked Results

AI-powered rankings show the best options first. Filter chips let users toggle between priorities, while numbered rankings and detailed stats build immediate confidence.

9:41

JR Yamanote Line

Train · Tokyo Metro

Recommended
7 min
Duration
¥170
Cost
4.9
Rating
Why We Recommend This
AI
The Yamanote Line is Tokyo's most reliable transit. Trains run every 2-3 min during peak hours with 99.7% on-time rate.
Reliability Score
97%
View Directions

Transport Detail

A deep dive into the selected option with key stats at a glance. The AI insight explains exactly why this option is recommended—building user trust through transparency.

9:41
Preview Directions
JR Yamanote Train · Platform 3
¥170
Shinjuku
Shibuya
Duration ~7 min
Departs 9:48 AM
Route Steps
1
Walk to Shinjuku Station 2 min · 180m north
2
Board JR Yamanote Line Platform 3 · toward Osaki
3
Ride 3 stops · ~7 min Harajuku → Ebisu → Shibuya
4
Arrive at Shibuya South Exit · 9:55 AM
Start
Share

Preview Directions

Step-by-step route preview before departure. Users review every leg of the journey and start navigation or share the trip with one tap.

07

Design Decisions

Point B is designed to feel trustworthy, fast, and universally accessible.

AI Transparency

Every recommendation includes an explanation. Users don't just see "what"—they understand "why."

Universal Design

Clean iconography and minimal text means the app works across language barriers.

Trust Through Data

Ratings, reliability stats, and local insights build confidence in unfamiliar territory.

Speed First

Travelers are often in a hurry. The UI prioritizes quick decisions over endless options.