NewParentCF
Health App for Mothers Navigating New Parenthood & Cystic Fibrosis
Project Details
Overview
Role
UX Research, Interaction Design, Information Architecture, Prototype Development, Visual Design & Illustration
Timeline
Jan-Feb 2023
Team
Audrey Reiley
Melina Phan
NewParentCF is a mobile web application designed to support new mothers with cystic fibrosis as they navigate one of the most complex decisions of early parenthood: how to feed their newborn. For women with CF, breastfeeding and formula feeding carry unique medical, nutritional, and financial considerations that are rarely addressed in one place.
The app guides users through five key areas (FAQs and misconceptions, medication interactions, nutrition, associated costs, and time management) and lets them build a personalized summary list to bring to conversations with their care team.
The Challenge
New mothers with cystic fibrosis face a distinct and underserved information gap. Feeding decisions intersect with medication safety, elevated caloric needs, financial constraints, and time pressures that differ significantly from the general population. Existing resources are scattered, overly clinical, or simply absent.
The goal was to design a tool that felt empowering rather than overwhelming, one that respected the user's intelligence while translating complex medical information into something actionable and personal.
Information Architecture
The app is designed to be used with or without an account. Users can access the tool as a guest or sign in to save notes and generate a printable summary. From the home page, they can navigate nonlinearly across seven sections.
Research
Secondary Research
Onsite Observations & Interviews
Conducted systematic observations across different departments, documenting customer behavior patterns, pain points, and interaction needs.
Web Articles
Conducted background research on Lowe's business model and
the broader DIY culture in the United States through online articles
and industry reports.
App Audit
Conducted a comprehensive audit of the existing Lowe's mobile application to map user journeys and identify improvement opportunities.
Conducted 12 guerrilla interviews with customers and staff, plus 4 in-depth interviews with experienced DIYers to understand motivations, challenges, and decision-making processes.
Interviews
We began by analyzing DIY culture in America, discovering that 47% of Americans consider themselves somewhat handy, while only 18% consider themselves extremely handy. This gap indicated a significant opportunity to support intermediate DIYers who want to tackle projects but need guidance and confidence-building.
Primary Research
Key Research Findings
Through our research synthesis, we identified six critical pain points in the DIY journey:
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Customers need experience to identify root causes and aren't sure if projects match their skill level.
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Customers want to know if required products are in stock before making a trip to the store.
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Large retail spaces create difficulty finding specific products and frequent walking back and forth.
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Getting timely assistance from knowledgeable staff, especially during peak hours.
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Finding products best suited for specific needs among overwhelming options and technical specifications.
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Diagnosing and resolving issues that arise during the project execution phase.
Design Solution
Sign In and Account Creation
Returning users sign in with email and password. After entering their email, the user's profile card appears on screen for confirmation. New users can sign up with their name, email, and an optional profile photo. A guest mode allows access without an account, with a persistent prompt to sign in to save information.
To enhance user experience, the app offers a Night Mode feature, which presents all content against a dark background to minimize eye strain.
Menu & Night Mode
As feeding methods carry a wide range of cultural considerations, this section provides a neutral space to address common concerns and dispel misconceptions. Users can scroll through a list of frequently asked questions about breastfeeding and formula feeding, expanding each one to reveal the answer. Content will be updated as new information becomes available. A future iteration would include a write-in box, allowing users to submit any questions not already covered.
Frequently Asked Questions
Users can generate a list of their medications to view known interactions and a traffic-light risk assessment.
Medication Interactions
A functional calculator tailored to CF to provide relevant health data to users. The focus is on personal health, while avoiding the use of BMI-based language in favour of nutritional macros and balanced diets.
Nutrition Calculator
Users can select their state and preferred feeding method — breastfeeding, formula feeding, or a combination of both.
Average Costs By State
After entering their state, users can view the financial support resources available in their chosen state.
Average Costs Resources
An interactive weekly planner where users drag and drop time blocks for pumping, feeding, and appointments into each day of the week. Tapping a day opens an expanded view with controls for editing labels, time, and colour. A running counter tracks total hours accounted for per day.
Time Management Planner
Notes saved as high priority or for later can be accessed through the My List section. Users can also print their saved notes onto letter-sized paper to use as a discussion point with their medical team and support network.
My List
The homepage serves as the first point of entry. The app is designed to be used without an account, so the URL links directly to this page. If the user is not signed in, a pop-up alert will appear at the top of the screen prompting them to sign in if they wish to save their information.
Home Page
1
User Journey Mapping
We mapped the complete DIY experience across three key phases:
Pre Store
Problem Identification
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Need experience to identify the root cause
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Uncertain if project matches skill level
1
Pre Store
Problem Identification
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Need experience to identify the root cause
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Uncertain if project matches skill level
Action planning
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Product availability uncertainty
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Lack of clarity on necessary tools
2
In Store
Store Navigation
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Difficulty finding products
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Frequent walking back and forth
2
In Store
Store Navigation
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Difficulty finding products
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Frequent walking back and forth
Product Comparison
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Overwhelming text and small print
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Unsure which product is suitable
3
Post Store
Planning & Kickstart
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Underestimating time
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Mixing up project steps
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Information overload
3
Post Store
Planning & Kickstart
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Underestimating time
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Mixing up project steps
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Information overload
Troubleshooting
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Struggling to diagnose when things go wrong
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Need for adaptive problem-solving support
Designing an AI Personal Assistant
Based on our research findings, we developed "Lo" - a conversational AI assistant designed specifically for Lowe's customers. Lo embodies the helpful, inspiring, and community-centric values of the Lowe's brand while providing personalized guidance throughout the DIY journey.
Al Characteristics
Character Traits
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Reliable and trustworthy
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Encouraging and optimistic
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Intelligent but approachable
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Collaborative and adaptive
Tone and Language
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Casual yet informative
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Direct and personable
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Optimistic and educational
Purpose
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Educate customers about products and techniques
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Inform with relevant, timely information
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Enable successful project completion
Interaction States & Behaviors
Design Language System
Visual Identity
Color Palette
Lo's visual representation uses Lowe's established color palette and typography while introducing a distinctive helper icon that suggests both human assistance and technological capability.
Typography
Inter family (Light, Regular, Bold) for consistency with Lowe's brand standards while ensuring readability across devices.
Clean, minimal icons that support voice interaction without overwhelming the interface, following Lowe's established visual language.
Iconography
Final Outcomes
Our solution addresses the need for retail home improvement stores like Lowe's who would benefit from carefully designed conversational voice interactions that prioritize human needs while leveraging technology as an enabling tool rather than the primary focus. Lo employs augmented reality and conversational AI to guide customers through problem diagnosis, product selection, and project execution. The system combines machine learning with real-time inventory data to create personalized shopping experiences, enabling customers to navigate complex product decisions with confidence. This approach sets our work apart from typical retail technology implementations. Instead of adding digital layers that distance customers from products, our system promotes deeper engagement with the physical materials and tools central to DIY success.
Next Steps & Further Development
Given more time and resources, we identified several key areas for continued development and enhancement:
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Social functionality allowing DIYers to share projects, ask questions, and learn from each other's experiences. This could include project galleries, peer mentoring systems, and collaborative problem-solving forums integrated directly into the Lo experience.
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Develop algorithms that anticipate home maintenance needs based on customer purchase history, local weather patterns, and typical wear cycles where Lo could proactively suggest preventive projects and seasonal preparations.
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Help customers understand the environmental impact of their choices, suggest eco-friendly alternatives, and track resource conservation across projects.