ComeHome Case Study | Hosna Mamouri

Overview

ComeHome was an Australian property platform that let users search for homes based on commute time to work, nearby amenities, and lifestyle-relevant data like internet speed and noise levels. This was information that traditional portals like Domain and realestate.com.au didn't surface.

I joined in a dual admin and UX design assistant role whilst in high school, supporting both operations and the design team. This gave me direct exposure to user feedback, stakeholder communication, and the product decisions shaping the platform. ComeHome has since shut down.

The Problem

Property portals treated home search as a purely transactional process. Filter by suburb, price, and bedrooms, then figure out the rest yourself. But the factors that actually determine whether someone is happy where they live (commute time, internet reliability, nearby schools, noise levels) required hours of separate research across multiple sites.

Core Features

Commute-Based Search

Users entered their workplace, selected a transport method (driving, walking, or transit), and the platform surfaced every property within their commute radius on an interactive map with duration badges and price pins.

Places Nearby

A toggleable layer system overlaid amenity data onto the map, including schools, hospitals, restaurants, shopping centres, libraries, bus stops, and train stations, each showing a count of options in the area.

Property Intelligence

Each listing displayed internet speed with a percentile ranking against the region, mobile reception quality, 4G availability, and noise level. This was data users would normally only discover after moving in.

Refined Search

The search panel brought commute and lifestyle filters alongside traditional property criteria. Users could specify their workplace, choose a commute method, and filter by features like internal laundry, pet-friendliness, or a balcony.

My Contribution

My role blended administration with UX design support. Being embedded in operations meant I was often the first to see user feedback and support queries, putting me in a unique position to spot patterns the design team could act on.

Key findings:

Users were piecing together commute times, amenity proximity, and property data across multiple sites, the core problem ComeHome solved
Internet speed and noise levels were recurring post-move complaints, validating their inclusion as pre-search filters
Mobile users consistently struggled with toggling between map layers

Through reviewing data from usability testing sessions, we identified a pattern of users enabling too many amenity layers simultaneously, causing the map to become visually cluttered. I flagged this to the design team, contributing to discussions around introducing clearer visual grouping.

I assisted with wireframing, helped prepare materials for research sessions, and coordinated between design, development, and business stakeholders to keep workflows moving.

Key Learnings

Design is applied psychology

ComeHome was where I first saw how design decisions are rooted in real human behaviour. The commute-first search worked because it matched how people actually think about where to live, not by suburb name, but by "can I get to work in under 30 minutes?" Seeing that connection between psychology and interface design is what drew me into UX as a career.

Real users surprise you

Reading support tickets taught me that the gap between how designers expect a product to be used and how people actually use it is always wider than you think. That lesson has shaped how I approach design. Start with what users are actually doing, not what you assume they'll do.