Prettypath
Re-imagining Pedestrian Navigation:
Making walking safer and more accessible for everyone
01 Discovery
03 Validation
04 Refine
Early Stage Prototype
Grade Summary
Grades paired with teacher context and recommended resources.
Dashboard with priority alerts.
Centralized dashboard surfaces urgent tasks parents can’t miss.
App integration.
Unified hub reduces platform switching with connected APIs.
Strengthening Usability & Trust
Dashboard
Simplified the layout and removed confusing elements in the second iteration.
Identified most important elements and elements causing confusion or overwhelm.
Redesigned notifications using familiar list-style cards and labeled sections to support quick scanning.”
KEY CHANGES
Primary CTA moved up.
Improves visibility and quick access.
Removed connected apps.
Reduces clutter, focuses on core tasks.
Removed confusing icons and badges.
Simplifies scanning and navigation.
Naly introduces itself from the dashboard.
Builds trust and user awareness.
Notification redesign.
Matches familiar UI patterns for faster recognition.
Titles added.
Clarifies content structure.
New sections added.
Aligns with user priorities.
Naly AI Iteration
Bottom sheet visually separates AI replies, making them more prominent and accessible.
The first iteration revealed that Naly’s role and presence within the interface were not immediately clear to users.
Used color contrast to differentiate between the AI and messaging interactions.
KEY CHANGES
Sheet overlay.
Creates contrast and focus
Color-coded interactions.
Differentiates AI from user messages.
Multiple response options.
Supports user control.
AI labeled clearly.
Reinforces role transparency.
Greyed-out background.
Directs attention to active interaction.
Retrospective
Designing for trust in an AI assistant was a key challenge. Parents were wary of automated interactions, fearing they might undermine human connections. This led me to focus on transparency—clearly explaining data sources, reasoning, and giving users control. I learned that trust in AI requires more than accuracy; it demands clarity, user agency, and alignment with real-world values.
Problem
Urban pedestrians navigate environments that are often blocked, unsafe, or unpredictable, yet existing navigation tools fail to account for real-time pedestrian conditions. As a result, people are forced to react in the moment by rerouting, taking risks, or losing time without reliable guidance.
At the same time, there is no seamless way for users to contribute on-the-ground insights, creating a gap between lived experience and available navigation data.
Navigation tools lack nuanced real-time, pedestrian-level visibility
Users rely on reactive, inefficient decision-making
Solution
I designed Prettypath from the ground up as a community-powered navigation tool that helps pedestrians avoid obstacles through real-time, user-generated data.
Result: a friction-less, single-screen reporting flow to enable quick, in-the-moment contributions
Executive Summary
These tests revealed that while parents valued consolidation, poor hierarchy and unclear AI roles undermined confidence guiding our next iteration toward simplicity, clarity, and trust.
Objective
We ran usability testing to ensure the prototype effectively addressed parents’ pain points: simplifying communication, reducing overload, and clarifying AI’s role.
Test Group
7 of our original interview participants returned
Methodology
Moderated remote sessions with 7 returning participants (via Google Meet + Maze prototype).
Parents completed core tasks while we observed interactions in real time.
Follow-up questions probed pain points, expectations, and perceptions of AI support.
Icons lacked meaning, forcing parents to guess their function.
Primary CTA didn’t stand out. Users overlooked the next step.
Users were unsure of which of the suggested options to proceed with
Messages sent to AI felt directionless, reducing trust.
Users desired a variety of generated reply options
Meaning of number badges was unclear
Layout Simplification
Notification Redesign
Prioritization
Clarifying Naly’s Role
Enhancing Visual Differentiation
Optimizing AI Interactions
Too many options cluttered the screen; unclear icons and badges confused parents.
Overwhelming Layout
Unclear Task Flow
Messaging Confusion
Parents struggled to follow a clear path, causing hesitation and errors.
Parents weren’t sure who received their messages or how Naly (AI) was involved.
KEY INSIGHTS
My Role
Principal User Researcher and UX Designer
Discovery Research, Interaction, Visual Design, Prototyping and Testing
Impact
xxx
02 Design
Competitive Analysis
To better understand the market landscape, we analyzed 10 platforms, including other FRMs, school information systems, and broader AI tools—to gain an overall understanding of the market, gaps, and opportunities for innovation.
INSIGHT
EVIDENCE
Only 2 out of 10 of educational competitors have integrated and actively promoted AI assistance in their products. (excluding AI chat companies)
Limited AI Adoption
Market Opportunity
4 out of 10 of the competitors offer an all-in-one solution suite that includes communications, attendance tracking, grade reporting, and scheduling.
8 out of 10 competitors offer multiple disjointed communication tools that require parents to switch between platforms.
Only 2 out of 10 provide an integrated, one-stop solution for all school communications.
Fragmentation
Integration Gap
Research Planning
In the discovery phase, I created a research plan to uncover parents’ needs, frustrations, and expectations with the Actionaly parent hub. My approach included:
* Defining objectives to identify usability gaps and address concerns about AI so design decisions were grounded in real user needs.
* Shaping research questions to explore both functional challenges (ease, effectiveness) and emotional drivers (trust, expectations), ensuring a holistic view.
* Recruiting participants to capture diverse perspectives across family structures, tech skill levels, and communication habits, making insights broadly applicable.
* Structuring interviews to combine contextual inquiry and task evaluation, followed by reflective questioning, so findings revealed not just what parents do, but why.
* Team collaboration to gather multiple perspectives during observation and note-taking, strengthening analysis and reducing researcher bias.
Research Questions
Based on our planning, we defined key research questions to guide discovery and ensure our study stayed focused on parents’ needs and expectations.
How do users currently navigate around obstructions, and what pain points exist in those strategies?
What accessibility concerns should be addressed?
What types of real-time or community-driven data would users trust and find helpful?
I conducted surveys to confirm a perceived user need being unmet by existing navigation tools. The goal was to gather insights from a broad swath of pedestrians, traveling under diverse conditions and in diverse environments.
Users value and are willing to contribute real-time, community-sourced reports more than official feeds.
Peer-to-peer data inspires the highest practical trust.
People navigate reactively; they need proactive alerts and rerouting to reduce risk.
Reactive coping signals demand for predictive guidance.
Lighting and surface conditions matter to all users, not just those with mobility impairments.
Safety and reliability outweigh accessibility alone.
There’s a major gap between app-based maps and lived pedestrian experience.
Current navigation tools feel blind to real conditions.
Urban pedestrians encounter recurring barriers that significantly impact mobility and safety.
Daily walkers face frequent, tangible obstructions.
Core Insights
Participants
41 individuals, ages 18-65
Varying genders, household types, and
Methodology
Asked questions regarding daily habits, accessibility needs, and environmental circumstances
Discovery Surveys
Research Objective
Assess interest in a tool designed to help pedestrians avoid waste, obstacles, and other obstructions when navigating city streets. Determine how the tool can be designed to best meet the needs of a diverse range of users.
Research Objective
Case Studies
About
Contact
User Researcher + UX Designer
01
discovery
02
design
03
validation
04
refinement
user research,
interviews
flows,
prototypes
iteration,
optimization
usability
testing
View Full User Journey
End State User Journey
Naly, an AI assistant handles:
Task management
Calendar syncing
Communication tools
Key features included:
Seamless access to school updates through a single hub
Smart notifications
Auto-filled calendars
We designed a streamlined, AI-assisted experience that unified fragmented tools into a single hub, helping parents access school-related information quickly and confidently, without platform switching.
These features created a more efficient and personalized experience, guiding parents from initial anticipation to growing trust and ultimately peace of mind.
We turned research insights into a low-fidelity prototype that tackled parents’ frustrations with fragmented platforms, missed updates, and unclear priorities.
Usability Testing
We refined the dashboard to reduce clutter, surface priority alerts, and turn scattered data into actionable next steps.
The refinement stage focused on addressing the most critical usability issues identified in testing while strengthening parent trust in the AI assistant.
We clarified Naly’s role with clear labeling, visual separation, and choice-based responses to build trust and control.
Persona: The Active Urban Walker
Name: Jordan Reyes
Age: 34
Occupation: Marketing Manager (Hybrid Work)
Location: Brooklyn, NY
Household: Shares an apartment with one roommate
Walks multiple times per day for mixed purposes (commuting, errands, leisure).
Occasionally reports civic issues through city apps or social media.
Adopts new tech quickly—especially if it feels community-driven and practical.
Behavior Patterns
Motivations
Efficiency: Wants the quickest, least-disruptive route to destinations.
Comfort & Safety: Prefers paths that are well-lit, clear, and less congested.
Contribution: Likes to give feedback to improve city life and help others avoid issues.
Encountering unexpected obstructions (trash, construction) that force sudden detours.
Lack of reliable, real-time info about sidewalk conditions.
Frustration when walking apps don’t reflect the actual pedestrian experience.
Pain Points
Frequent Walking Barriers
Daily walkers face frequent, tangible obstructions
Pedestrians regularly encounter trash, damaged pavement, and parked scooters, causing 49% to experience safety concerns or delays.
Enable Predictive, Real-Time Navigation
Add live obstruction alerts (“blocked ahead”) and adaptive rerouting to help users avoid hazards before reaching them.
Reactive Coping Patterns
Most users “detour on the fly” or briefly walk in the street
risky, reactive behavior showing urgency to keep moving.
Design Anticipatory Guidance Systems
Provide proactive notifications, predictive routing, and pre-walk summaries (e.g., “cleaner route available”) to reduce unsafe improvisation.
Peer Data Trust
Users trust and prefer peer-generated insights over official data.
41% rely on user reports; 85% would contribute their own.
Build a Community-Driven Reporting Ecosystem
Enable one-tap reporting, optional photo uploads, and visible “trusted contributor” badges to foster credibility and participation.
Map Blind Spots
70% agree that current map apps don’t reflect real sidewalk conditions, a major gap between digital and physical reality.
Create Hyper-Local, Trustworthy Map Layers
Merge user input with official feeds for a constantly updating “clean path” map reflecting street-level changes.
Safety & Accessibility
Concerns like poor lighting and uneven surfaces affect all walkers — 42% cited streetlight outages as a top issue.
Emphasize Safety-Focused Design
Integrate lighting-aware routing, surface quality indicators, and nighttime “safe path” heatmaps for better perceived security.
Contextual Awareness Needs
Users most value weather-aware routing (55%) and activity heatmaps (50%), showing preference for environmental context over static ratings.
Integrate Contextual Intelligence
Use weather, time, and traffic data to predict optimal walking conditions and surface cleanliness.
Price Sensitivity Reality
While interest and willingness are high, most users expect free access or low-cost tiers.
Adopt a Freemium Adoption Model
Offer core features (alerts, reports) free to drive growth; add premium layers for customization and analytics later.
Design Recommendation
Research Insight
