Project Overview
Goal
Create an “apartments.com for senior housing” for Welltower Inc. that could market their 3,000+ communities.
Challenge
Inconsistent data maturity across properties created a mismatch between client vision and actual feasibility. Plus, the need to capture lead generation without eroding trust and compromising usability.
Impact
A scalable marketplace that supports a phased rollout across inconsistent datasets, mirrors users' natural decision progression, and turns lead capture into intent-driven interactions.
My Role
Led client-facing presentations, gaining trust through strategic, solution-oriented design proposals
Aligned cross-functional teams on a feasible MVP that also met client expectations.
Validated key design hypotheses through user testing to better reflect real user behavior
Designed a trust-based lead capture flow tied to meaningful user actions—boosting conversion without gating content
Key Design Decisions
🔍 Information Architecture That Fits the User’s Mental Model
Early Design Approach
To support both user decision-making and phased data rollout, we structured search results to reflect how people naturally narrow choices: starting with communities, then filtering by care type, and eventually considering specific units.
Default: Location-based searches return community cards
Filtered by care type: Results shift to floor plan cards since layout options vary by care type (e.g. ,memory care units lack kitchens)
Future-ready: As data improves, unit availability can be layered in
This structure earned client buy-in and created a scalable, user-aligned framework.
Testing a New Hypothesis
Initial Hypothesis (Design A)
If a user is filtering by care type, then they are ready to choose a floor plan option.
Opposing Hypothesis (Design B)
If a user is filtering by care type, they still want to evaluate community fit.
To validate the new hypothesis, I ran a split test comparing community vs floor plan search results when filtering by care type.
Do people prefer to browse by community or by floor plan?
How do the search results affect their decision-making process?
VS
Key Learnings
73%
73% of decisions are primarily based on community fit
47%
47% did not understand care type and floor plans correlation
67%
67% prioritized bed/bath count over visual floor plan diagrams
Final Design Principles
Lead with community context: Whether users are early-stage shopping or filtering by care type, all journeys begin with evaluating the community itself.
Care type filters ≠ floor plan readiness: Many users filtering by care type aren’t yet ready to choose specific layouts.
Community-first design ensures data resilience: Community-level results rely on baseline data available across all listings.
Nesting reflects decision flow: Embedding floor plans within communities aligns with how users move from environment to layout.
🧭 No Dead Ends
To avoid disruptions in the search experience, I designed a fail-soft approach to prevent user drop-off. When a search yields no exact matches, the system now:
Surfaces nearby communities within a reasonable radius
Loosens filters (e.g. price or room type) prompting users to adjust their criteria.
Suggests similar options that meet most, but not all, of the user's criteria
This design preserves momentum, encourages exploration, and ensures users never hit a dead end.
↔️ Fair-Value Lead Capture
From the start, we aimed to move away from gated content. Forcing users to give their personal information in exchange for browsing erodes trust and can increase drop-off rates—especially for casual browsers.
Instead, users can freely explore listings, with lead capture triggered only by meaningful interactions, such as:
Favoriting a community
Sharing a listing
Saving a search
This approach built trust and made sharing personal contact information feel like a fair-value exchange—earned through engagement, not forced up front.
Reflection
We began designing around client requirements, but real progress came when we shifted focus to the user’s mental model. By aligning the experience to how people naturally navigate —starting from community, then care type, then floor plan—we created a flow that felt intuitive and supportive.
I'm glad we were all aligned on avoiding the industry norm of gating content. Instead, we prioritized trust by tying lead capture to meaningful, user-driven actions. I would be very curious to see if this converts just as well, if not better, than more aggressive approaches.