Land Insights

Making property listings more competitive

The Opportunity

Land Insights helps real estate investors flip land — buying, marketing, and reselling parcels. The Dispo Tool helps investors track every property from acquisition through resale, combining listing management, AI-powered recommendations, and performance insights in one workspace.

Managing land listings required more than tracking properties — it required understanding where each listing stood, why it wasn't selling, and what to do next. The opportunity was to design an intelligent listing management workflow that combined sales-stage visibility, AI-powered recommendations, and contextual insights to help users prioritize work, sell faster, and maximize profitability.

Role: Lead Product Designer
Team: Chief Product Officer
Tools: Figma · Claude Code

Discovery

Defining the feature before designing it.

Before designing the interface, I needed to understand how the listing workflow fit within the broader platform, how data moved through the experience, and how competing products solved similar problems.

I translated those findings into an end-to-end workflow and information architecture before moving into high-fidelity design.

Discovery board showing user flows, sitemap, and listing detail explorations — Feature exploration and competitor analysis

User flows for adding, tracking, viewing, and removing land listings — End-to-end listing workflow and information architecture

Solution

Designing an end-to-end listing workflow.

I designed an end-to-end listing workflow — from managing listings and creating new properties to viewing individual properties with AI-powered recommendations, listing grades, and performance metrics.

Listing management

Investors manage dozens of properties simultaneously, so I designed multiple viewing options, filtering, and sortable KPIs to help them prioritize listings without opening each property individually.

Kanban listing tracker with top-level stats and property cards organized by stage

Sortable listings table with price, county, acreage, profit, traction, and status

Listing creation

New listing form with Zillow URL, financials, live profit breakdown, and deal details

New listing form filled with property lookup, owner info, and acreage details

Kanban view with a new listing loading its details

Property insights

Rather than overwhelming investors with raw listing data, I surfaced AI recommendations, listing grades, and performance metrics directly within the property page so users could prioritize their next action without switching contexts.

Listing detail page with photos, MLS metrics, traction score, listing grade, recommendations, and timeline

Design Ownership

Sole designer from requirements through engineering handoff
Led discovery, competitor analysis, and end-to-end user flows
Rapidly explored concepts, refined workflows, and validated ideas using Claude Code
Built interactive prototypes in Claude Code to validate user workflows
Translated validated concepts into high-fidelity designs, polished UI, and developer-ready specifications in Figma
Documented detailed interaction behavior, edge cases, and specifications for seamless developer handoff

Feature Highlights

Feature launched with $35M in projected user sales
Listing management with search, filters, sorting, and KPI metrics
Kanban workflow for organizing properties by listing stage
Contextual profit calculations during listing creation
Property insights with AI-powered recommendations, listing grades, and performance metrics
Responsive experience across desktop and tablet