Context

Retrofitting residential properties requires:

• Reliable building data
• Expert surveying
• Accurate energy modelling

However, private homeowners typically lack the knowledge and tools to make informed decisions.

This creates a gap between:

• Accessible decision-making for non-expert users
• Complex technical processes

My Role: Solo Product Designer

Challenge

Homeowners faced significant barriers when planning retrofit projects:

• Limited understanding of available measures and their impact
• Difficulty accessing qualified professionals
• Risk of poor decisions leading to inefficiencies or structural issues

The challenge was to explore whether a digital product could simplify decision-making while maintaining technical reliability.

Approach

This project was a feasibility study focused on validating both:

• Market demand
• Product viability

I reframed the problem as a service + platform experience, combining:

• Data inputs (property information)
• Expert validation (surveyors)
• Decision support (recommended improvement packages)

Key design principles:

• Reduce complexity for non-expert users
• Guide users toward reliable outcomes (not just options)
• Align the interface with real-world service delivery (survey → recommendations)

Solution

I designed a prototype platform that:

• Generates tailored retrofit recommendations based on property data
• Connects users with qualified surveyors to validate decisions
• Shifts the user journey from “choosing measures” to “booking a survey” as a critical step
• Structures information progressively to balance simplicity and technical depth
• Supports mobile-first usage to improve accessibility

The design evolved from an existing concept, refining:

• User flow and decision points
• Information clarity and hierarchy
• Alignment between user intent and system outcomes

Interim web view workflow:

Design development highlights:

Mobile view of flow from onboarding to check out:

Decisive points:

Impact

• Validated early market interest with potential customer groups
• Demonstrated feasibility of combining public data with energy modelling
• Supported decision-making on future product direction and investment

Key Takeaway

When designing for non-expert people in technically complex domains, the challenge is to structure their decision-making process so that they arrive at reliable outcomes that they can trust.