Summary
In-depth
Overview
Project Type: Internship Project
Duration: 1.5 months
Role: UX Designer & Researcher
Methods: User Interviews, A/B Testing, Prototyping, Usability Testing
FamilySearch’s Family Tree platform helps users preserve and explore their family history. As part of an effort to improve data quality and user trust, the team introduced a Data Quality Score. It's a feature that flags inconsistencies and suggests areas for improvement in the family tree. My task was to redesign this tool for clarity, trust, and usability.
Problem
Data Quality Issues Were Undermining Trust:
Many users encountered inconsistent or conflicting data in their family trees, but lacked visibility into what needed fixing or why it mattered. An algorithm had been developed to detect potential data issues—but the initial designs weren't effectively supporting users.
Key Pain Points Identified via A/B Testing & User Feedback:
Ambiguous iconography and unclear messaging
Low user confidence and motivation to engage with the tool
Score presentation felt complex and hard to interpret
Solution
Design a Data Quality Tool That Drives Action Through Clarity:
The goal was to improve users’ confidence in their data and increase engagement with the Data Quality Score tool through improved UX.
Strategic UX Goals:
Simplify how quality issues are communicated
Reduce cognitive load with intuitive visual hierarchy
Drive engagement through urgency and clarit
Key Features
Quality Score Summary:
Reorganized issue layout for scannability
Collapsible sections for efficient browsing
Clear visual cues to reduce overwhelm
Quality Score Info Sheet:
Unified right-hand side sheet for deeper issue details
Updated score bar color logic to better convey urgency
Total issue count now visible for quick assessment
Improved overview to guide next steps
Mobile-First Optimization:
Redesigned touchpoints for mobile interaction
Multiple access points to the score to support different workflows
Balanced layout simplicity with backend system limitations
Outcomes & Insights
Though I joined after the algorithm was conceptualized, I significantly enhanced the usability of the Data Quality Score through research-backed iteration.
Key Learnings:
User Testing Rigor: Crafting the right testing prompts led to more actionable feedback.
System Thinking: Learned how backend limitations impact UI design trade-offs.
Adapting Design Processes: Navigating real-world constraints sharpened my product thinking.
Empathy for Complex Relationships: Designing for family structures requires nuance and sensitivity.
Summary
In-depth
Overview
Project Type: Internship Project
Duration: 1.5 months
Role: UX Designer & Researcher
Methods: User Interviews, A/B Testing, Prototyping, Usability Testing
FamilySearch’s Family Tree platform helps users preserve and explore their family history. As part of an effort to improve data quality and user trust, the team introduced a Data Quality Score. It's a feature that flags inconsistencies and suggests areas for improvement in the family tree. My task was to redesign this tool for clarity, trust, and usability.
Problem
Data Quality Issues Were Undermining Trust:
Many users encountered inconsistent or conflicting data in their family trees, but lacked visibility into what needed fixing or why it mattered. An algorithm had been developed to detect potential data issues—but the initial designs weren't effectively supporting users.
Key Pain Points Identified via A/B Testing & User Feedback:
Ambiguous iconography and unclear messaging
Low user confidence and motivation to engage with the tool
Score presentation felt complex and hard to interpret
Solution
Design a Data Quality Tool That Drives Action Through Clarity:
The goal was to improve users’ confidence in their data and increase engagement with the Data Quality Score tool through improved UX.
Strategic UX Goals:
Simplify how quality issues are communicated
Reduce cognitive load with intuitive visual hierarchy
Drive engagement through urgency and clarit
Key Features
Quality Score Summary:
Reorganized issue layout for scannability
Collapsible sections for efficient browsing
Clear visual cues to reduce overwhelm
Quality Score Info Sheet:
Unified right-hand side sheet for deeper issue details
Updated score bar color logic to better convey urgency
Total issue count now visible for quick assessment
Improved overview to guide next steps
Mobile-First Optimization:
Redesigned touchpoints for mobile interaction
Multiple access points to the score to support different workflows
Balanced layout simplicity with backend system limitations
Outcomes & Insights
Though I joined after the algorithm was conceptualized, I significantly enhanced the usability of the Data Quality Score through research-backed iteration.
Key Learnings:
User Testing Rigor: Crafting the right testing prompts led to more actionable feedback.
System Thinking: Learned how backend limitations impact UI design trade-offs.
Adapting Design Processes: Navigating real-world constraints sharpened my product thinking.
Empathy for Complex Relationships: Designing for family structures requires nuance and sensitivity.
FamilySearch
Olive Yuen