Led a platform wide redesign of GoFundMe’s consumer reporting experience
Balancing Community Voice & Platform Integrity
ROLE + COMPANY + YEAR
Lead Product Designer, GoFundMe 2026
DELIVERABLES
Task Flows, Screen Flows, & Prototyping
PLATFORM + FRAMEWORK
www.gofundme.com / Heart DS
Overview
Led end to end design strategy, streamlining GoFundMe’s consumer reporting model and improving transparency and trust in the integrity process.
Goal
Provide a consistent, low friction way for consumers to report issues directly from a fundraiser page and shift from a vague, text heavy, high noise system into a structured, guided experience that captures clearer, more actionable signals.
Measuring Impact
Empower Community Advocacy
Provide clearer, more intuitive reporting experience.
Steer users toward actions aligned with their actual intent.
Strengthen Platform Trust
Accelerate identification of policy-violating fundraisers.
Increase user confidence in the reporting process.
Increase in policy-aligned submissions.
Boost Operational Efficiency
Achieve 30% reduction in misrouted cases.
Target 20% decrease in low signal disagreement submissions.
Target 30% improvement in documentation completeness.
Reduction in fraud loss exposure.
Project Challenges
Balancing Community Voice and Platform Integrity
How do we create a behavioral interface that honors both community advocacy and policy governance?
Takeaways
Empowerment with guardrails
Clear guardrails build trust and reduce misuse by providing a fair, defined path to action.
Discoverability prevents escalation
Emotionally reactive actions, when left unstructured, generate operational noise. Intent-based pathways transform them into actionable signal.
Policy Aligned Routing
Upstream UX decisions directly shape downstream operational efficiency.
Clear Intent Selection
Designing around real user intent improves both user experience and moderation accuracy.
User Scenarios
End to end product experience for various logged in personas.
Flow: Menu → Category → Detail → Reassurance
Time: 2-3 minutes
Steps: 5 screens
Flow: Menu → Category → Detail → Reassurance
Time: 1-2 minutes
Steps: 5 screens
Flow: Menu → Category → Detail → Reassurance
Time: 1-2 minutes
Steps: 4 screens
Flow: Menu → Category → Detail → Reassurance
Time: 1-2 minutes
Steps: 3 screens
Process
Synthesized research insights and problem statement.
How I applied generative AI as a strategic co-pilot to enhance pattern recognition, rapidly explore solution spaces, and accelerate iteration and design decision-making.
Defined foundational principles to structure the experience around intent, clarity, and operational integrity.
Defined a framework that converts emotion into structure signal.
Key design decisions that shaped the reporting experience.
Research Insights
✓
Unclear Entry Points, Static Form Experience
Form misuse & ticket misrouting caused by poor form discovery.
38% of reports are misrouted or require manual reassignment
27% of refund requests are incorrectly submitted as fraud reports
✓
Fragmented & Inconsistent Reporting Experiences Across Platform
Ticket misrouting caused by unstructured user input & incomplete submissions.
31% of cases require follow-up for missing information
✓
Emotionally Charged Non-Evidence Based Reporting Flood The System
Operational load of less actionable tickets & repetitive back and forth with users due to lack of upfront info.
18% of reporting submissions are disagreement-based with no policy violation
“Politically or virally charged fundraisers trigger mass reporting, creating volume but not actionable risk.”
⎯ Risk Team Analyst
“A significant portion of “fraud” submissions are actually standard refund requests, reflecting user confusion rather than true risk.”
⎯ Risk Team Analyst
“People don’t know which form to use... there are all these bars in place that prevent users from getting the help they need.”
⎯ Risk Team Analyst
“Many tickets lack necessary structure, resulting in subjective or speculative claims that analysts must spend time decoding.”
⎯ Risk Team Analyst
“Personal disputes (custody, family, moral objections) flood review queues without meeting actionable criteria.”
⎯ Risk Team Analyst
Problem
The current reporting ecosystem is fragmented across multiple entry points and supported by static, non-adaptive forms. This structure creates inconsistent journeys, duplicated workflows, and routing inefficiencies, while forcing consumers to self-navigate complex pathways before receiving support or voicing concerns. The experience also lacks intent-based structure, leading to emotionally reactive, low-signal submissions that are often misaligned with policy criteria and moderation workflows.
✦ AI Strategy
AI was integrated throughout the project as an acceleration layer across research, synthesis, and production. Rather than replacing design thinking, it enhanced pattern detection, iteration speed, and clarity of articulation.
Research Synthesis
I used NotebookLM to cluster qualitative themes across reporting categories, identify behavioral patterns, and surface recurring emotional triggers.
Signal Framing and Copy Iteration
Rapidly explored multiple tonal variations for modals, tooltips, and confirmation messaging to pressure test clarity, neutrality, and de escalation language using ChatGPT..
Intent Architecture Exploration
Used Miro AI & Whimsical AI to map steps across fraud, refund, beneficiary disputes and idealogical disagreements and stress test routing logic.
Vibe Coding for Flow Iteration
To accelerate early stage exploration, I used Figma Make to rapidly prototype high-level screen flows to pressure test.
Prompt:
How can I design a reporting experience that feels supportive, sets clear expectations, and elevates high-signal reports while reducing noise for review teams. Use a single adaptive form, empathetic guidance, and smart routing.
Design Principles
⚪️
Reduce Noise, Increase Signal
Clear pathways reduce reactive behavior and improves submission quality, routing accuracy, and operational efficiency.
⚪️
Guide, Don’t Police
Use framing, selection design, and evidence prompts to gently steer users toward policy-aligned actions rather than blocking them outright.
⚪️
Discoverability
Surface relevant guidance and alternative pathways at the point of friction to reduce false positives and better route issues before escalation.
Design Framework
Unifying Intake Architecture and Converting Emotion Into Structured Signal
By unifying fragmented entry points and structuring intent, this intake architecture transforms emotionally driven reporting into high-quality, policy-aligned signal.
Design for Intent
This section outlines the key design decisions that shaped the reporting experience.
1 / Discoverability
Surface relevant guidance and alternative pathways at the point of friction
Reduce false positives and better route issues before escalation:
In page nudges
Dynamic logic
Alternative pathways
Unified entry point for varied community concerns
Concerned supporters
Fraud reporters
Refund seekers
Beneficiaries owed funds
People who simply disagree
Safety teams reviewing cases
Ops teams routing issues
2 / Emotional Reaction
De-escalate emotionally charged situations with clear expectations
Leverage framing, intent-based selection, and evidence guidance to convert reactive reporting into policy-aligned signal. Providing clear pathways and a controlled outlet for context reduces low-signal submissions and minimizes unsupported claims.
Guide users through pathways that respect their perspective while aligning with policy criteria.
3 / Intent Framing + Structured Selection
Built around intent as its core structural layer.
Instead of relying on open-ended narrative, the flow presents clearly defined pathways mapped to policy categories, user behavior patterns, and moderation workflows.
4 / Evidence Guidance + Policy Aligned Signal
Designing for actionable input
Evidence guidance serves to:
Sets expectations for what can be reviewed
Increase the precision and efficiency of downstream moderation
Set clear expectations and reduce unnecessary follow ups
Provide clear messages for the various submission types. Set expectations for what can be reviewed.
Summary & Next Steps
Designed at the intersection of emotion and policy, this experience reframes reporting from reactive complaint to structured signal. Intent-based pathways and contextual guardrails transform unstructured input into policy-aligned submissions, improving signal quality, reducing false positives, and strengthening platform trust.
Next, we will validate with power users, stress-test content against backend and legal constraints, and align the workflow to a unified support model.