Case Study
A research-driven AI solution for adolescent health
Summary
Research leadership and AI platform integration • May-July 2025
Led systematic AI evaluation and UX research for educational chatbot serving adolescents aged 8-14 with menstrual health content. Applied responsible AI development practices to identify critical market gaps, delivering strategic positioning that achieved exceptional client satisfaction and prototype quality indistinguishable from production applications.
Challenge
Adolescents aged 8-14 lack access to stigma-free, age-appropriate menstrual health education. Existing AI solutions either target older teens (13+) or provide medically accurate but emotionally sterile responses that fail young users.
My Role
UX Research Lead and Initial Project Manager
Led 3-person UX team coordinating with 4-person development team
Conducted systematic competitive analysis across AI platforms
Delivered client presentations and strategic recommendations
Research Approach
Competitive Analysis Methodology
I evaluated AI platforms using standardized educational scenarios to assess age-appropriateness, emotional intelligence, and cultural sensitivity.
Key Testing Questions:
"What is menstruation?" (age-appropriate explanations)
"I'm at school and just got my period" (crisis response)
Religious and cultural scenarios (inclusive design)
Competitors Analyzed
Planned Parenthood's "Roo":
Medically accurate but emotionally sterile responses
Targets teens 13+, leaving gap in 8-12 age range
Rigid conversation flows lacking empathy
OpenAI’s ChatGPT and similar AI Platforms:
Highly adaptable and empathetic responses
No built-in age controls or educational safety measures
Privacy concerns for vulnerable populations
Research Deliverables
Competitive analysis report (12 pages)
Research presentation slides (20-minute client presentation)
Strategic positioning recommendations framework
AI platform evaluation documentation
Key Research Insights
Market Gap Discovery
Identified critical underserved population: No existing solutions effectively serve elementary/middle school students (ages 8-12) with appropriate tone and emotional support. Despite menstruation beginning, on average, when a child turns 12, existing products primarily focused on those 13 and older.
User Behavior Finding
Young users often don't know what questions to ask about menstruation, requiring conversation starters and guided discovery rather than reactive Q&A.
Cultural Sensitivity Gaps
AI-powered platforms for puberty education inadequately handled religious and cultural considerations, missing opportunities for inclusive health education.
Strategic Recommendations
AI Development Priorities
Built-in age-responsive design with automatic tone adjustment
Panic recognition and comfort provision beyond clinical information
Privacy-first architecture with ephemeral conversations
Cultural Competency Framework
Respectful handling of diverse family structures and religious practices
Myth-busting approach with cultural sensitivity
Inclusive language supporting all backgrounds and personal identities
Design Process
Wireframing and Prototyping
In addition to creating some early sketches, I created user flow documentation and provided extensive feedback on wireframes developed by a UX designer on our team. We progressed from initial concepts to high-fidelity prototypes with a comprehensive style guide for handoff to the engineering team.
Research
The wireframing and prototyping work proceeded on a parallel track with competitive research, allowing us to meet compressed client timeline requirements while building strategic foundation for future iterations.
Conversation Design
I developed sample conversation examples using ChatGPT with an uploaded knowledge base of vetted resources (50+ HTML files) to demonstrate realistic AI response patterns. This testing informed technical constraints and provided the engineering team with additional considerations.
Additional Challenges
Limited Access to Target Users
Direct user testing with 8-14 year olds would required parental consent and specialized protocols we couldn't implement within timeline constraints. I addressed this recruiting an additional UX researcher with a pre-teen family member interested in providing feedback and testing.
Technical AI Constraints
Balancing educational UX ideals with the OpenAI platform limitations and $20 budget required creative workarounds. I focused on conversation design examples that demonstrated potential within technical feasibility.
Results and Impact
Client Success
Delivered 20-minute research presentation achieving exceptional client satisfaction
Created prototype quality indistinguishable from production application
Research insights directly informed client's competitive positioning strategy
Strategic Value
Identified clear market opportunity in underserved age demographic
Provided framework for responsible AI implementation in education
Established competitive differentiation against established players
Core Contributions
Research Innovation in New Domain
Successfully adapted systematic competitive analysis methodology to AI platform evaluation, identifying critical market gaps in educational technology while building expertise in responsible AI practices for vulnerable populations.
Cross-Functional Project Coordination
Successfully managed research, design, and client stakeholder alignment within compressed timeline while maintaining quality standards and ensuring seamless deliverable handoff.
Tools and Methods
Research: Competitive analysis, AI platform evaluation, user scenario testing
Prototyping: Figma for wireframes and prototypes, style guide development
Project Management: Notion and Otter for documentation, Google Drive for asset management
AI Integration: OpenAI platform assessment, conversation design, technical constraint evaluation