Rental Genome Map Visualization
Location Intelligence platform providing data-driven insights for Single-Family investors.
B2B
0-1
Web Map App
Mapbox
Industry
Real Estate
Duration
1 month
Responsibilities
User Research
Geospatial Data Visualization
Map Interaction Design
Rapid Prototyping
Usability Testing
Quality Assurance
Team
1x Product Designer
1x Product Manager
4x Engineers
Project Overview
Business Context & Challenges
Roofstock had accumulated 1 billion+ proprietary data points across market trends, institutional buyer activity, neighborhood analytics, and property performance metrics — a powerful competitive advantage in the single family rental marketplace. However, this advantage wasn’t visible or actionable for investors and internal analysts in an intuitive tool.
Solution
We developed a Map Visualization Strategy that transforms Roofstock’s data into an interactive mapping solution, providing investors with the clarity and confidence they need to explore new markets, benchmark opportunities, and expand existing portfolios.
Results
1 B+
Data points on interactive map
8 Layers
Visualized for analysis
2x
Faster Analysis
Solution
Design Process
Discovery & Definition
Conducted User & Stakeholder Interviews
Mapped user decision-making workflows
Analyzed 5 competitor platforms
Prioritized key data requirements
Defined success metrics and KPIs
Map Data Visualization
Collaborated with engineers on technical exploration in Mapbox
Tested 4 clustering approaches with 1,000+ datasets
Evaluated different map styles
Defined map interactions
Prototype
Interactive Prototyping (Figma)
Cross-Functional Alignment
Validated choropleth designs
Tested color schemes
Design System Contribution
Delivery & Development
Developer Collaboration
Edge Case & State Validation
Comprehensive Test Case Development
Responsive QA & Bug Triage
From Research to Strategic Design Principles
Location Drives Investment Strategy
Investors structure their decisions from market → neighborhood → property.
Fragmented Tools Slow Decision-Making
Investors currently switch between multiple platforms to gather data, slows down their evaluation process.
Transparency in Data Sources
Trust is critical. Investors want to know exactly where each dataset comes from, how often it is updated, and whether it is reliable.
Comprehensive Property, Market & Neighborhood Data
Investors need a holistic view—market trends, neighborhood insights, rental performance, before they can make confident decisions.
What data investors care the most
User interviews revealed the most critical data points for property evaluation. I categorized these findings, collaborated with the internal team to assess data availability and implementation effort, then created a prioritization matrix. Features rated 4+ stars (high user value, feasible development) were selected for the MVP launch.
Visualizing Thousands of Properties on the map
The biggest challenge was transforming thousands of dense property data points into a single, actionable, and scannable map view. I partnered closely with engineering to rapidly test visualization methods in Mapbox Studio—evaluating Dot Density, Heat, Hexagon, and Choropleth styles. Through rigorous testing against user clarity and technical performance, we concluded that Choropleth maps were the most intuitive and familiar format for financial investors, significantly boosting data comprehension.
Dot Density Map
Pro: Shows raw property concentration at a glance.
Con: Too chaotic for pattern recognition at scale.
Hexagon Map
Pro: Eliminates boundary bias with uniform grid.
Con: Unfamiliar format confuses non-technical users.
Heat Map
Pro: Instantly reveals high-density hotspots.
Con: No clear boundaries for actionable decisions.
Choropleth Map
Selected
Pro: Familiar geographic boundaries.
Con: Visual bias toward large, sparse areas.
Strategic Map Visualization Decisions
Diverging vs. Sequential Color Schemes
I iterated from sequential to diverging color schemes because diverging palettes reveal deviation from meaningful thresholds (like market average or "moderate" rating), not just magnitude. This helps investors instantly identify areas performing above or below benchmarks, enabling faster comparative analysis.
5 vs. 7 Classification Levels
User testing showed investors made decisions faster with 5 classification levels compared to 7 levels. With fewer classes, users spent less time cross-referencing the legend and could identify patterns through rapid visual scanning. Five levels also align with cognitive science research on optimal pattern recognition.
Color Choice
I chose a red-to-green diverging palette because investors naturally interpret green as positive and red as negative, matching financial and real-estate dashboards. This direction improved instant comprehension and reduced the need to rely on the legend.
Sequential Scheme
Sequential Scheme
Selected
Map Controls and Interactions
Map Layers Management
Dot Density Map
Pro: Shows raw property concentration at a glance.
Con: Too chaotic for pattern recognition at scale.
Hexagon Map
Pro: Eliminates boundary bias with uniform grid.
Con: Unfamiliar format confuses non-technical users.
Heat Map
Pro: Instantly reveals high-density hotspots.
Con: No clear boundaries for actionable decisions.
Choropleth Map
Selected
Pro: Familiar geographic boundaries.
Con: Visual bias toward large, sparse areas.
Map Controls
Map Legend
Crime Score
0
2
4
5
7
10
Popups on Hover
Crime Score
7/10
Popups on Click
Census Tract: 008301
Property Count
1,364
Grass Yield
5.54%
Roofstock Rent Est.
$3,250
Renter-ship Rate
35%
Corporate Saturation
28%
Neighborhood Score
2/5
Crime Score
7/10
Basemap Switcher & Zoom Controls
Streets
Satellite
Light
Dark
Learning
Navigating Ambiguity with Collaboration and Alignment
When I joined this project, I had no prior domain knowledge, and the initial requirements were broad and ambiguous. It was intimidating at first, but I learned to navigate ambiguity by communicating openly and learning from my team. I focused on trusting the design process and building clarity step by step alongside others. Designing early prototypes and sharing quick visuals gave the team something tangible to align on. Through consistent communication and alignment, we turned uncertainty into a shared direction — helping the team move forward with confidence.
Designing at Fast-Paced Startup
Working in a fast-paced startup environment taught me to design and iterate alongside development. With limited design time, I leaned on rapid prototyping and early weekly testing systems to validate designs quickly and de-risk decisions. I focused on building reusable task patterns to improve efficiency and leveraging the design system to accelerate delivery. Over time, I began contributing back to the system, refining components and patterns to support future design speed and consistency