Ecopart — Trust-first Shared Living Service | Mobile

About Ecopart

This project explores a trust-first mobile platform for room rentals and shared living. A single system that supports the full journey: discovery, viewing, application, and rental management.

Two connected roles in one product:

• Residents renting rooms in shared apartments
• Property owners placing apartments under management

Product focus

Instead of optimizing for speed or short-term profit, I designed the experience to reduce uncertainty in shared living and support confident, long-term housing decisions.

Design goal

My main goal is to turn shared living from a risky compromise into a deliberate, comfortable choice.

Problem

I started with qualitative interviews, and the pattern was consistent: despite clear economic advantages, people hesitate to consider shared living. The core barrier is not price. It is perceived safety. People are reluctant to share a home with strangers because of fear of uncertainty, lack of control, and potential negative experiences. That insight became the foundation for every product decision in this case study.

Opportunity

This creates a clear opportunity for a structured, trust-first platform that reduces uncertainty and aligns what residents need with what property owners need.

For the business, this means:

• Better match quality and fewer early move-outs
• Higher long-term retention and contract stability
• Predictable recurring revenue from managed rentals
• Lower operational costs through structured flows and guided support

Market gap

Most rental platforms focus on fast booking and listings. Speed, speed, speed. The result? Users face uncertainty, weak matching, and unstable outcomes. Nobody is building around trust and predictability. That is the gap.

What I wanted to understand

The psychological and practical barriers preventing users from choosing shared living, even when it makes financial sense.

How I researched it

• Qualitative interviews with target users
• Behavioral pattern analysis across decision stages
• Market and competitor review to identify structural gaps

What I found

• Lack of trust is the primary adoption barrier. Users fear uncertainty about safety, predictability, and who they will live with.
• Emotional risk outweighs financial benefit. Affordability alone does not drive the decision. People would rather pay more for a studio than share with strangers they cannot trust.
• Ambiguous rules, unknown roommates, and weak platform responsibility increase perceived risk and make users hesitate even more.

Strategic goal

• Increase adoption of shared living by reducing perceived risk and emotional stress.

My approach

Shift the product from speed-driven transactions to trust-driven decision-making. Build confidence before commitment, not after. Everything in this strategy comes from that single shift.

Product principles

• Trust over speed
• Predictability over flexibility
• Structure over ambiguity
• Guidance in high-risk moments

How this translates into product mechanisms

• Make safety and reliability visible way before user makes rental decisions
• Reduce uncertainty through clear, structured steps
• Improve match quality rather than maximize transactions
• Support long-term stability over short-term conversion

Core audience

• Young professionals (25-35) in large cities with above-average income. They can afford it but they want to feel safe about it.
• Young couples (25-32) trying to find ways to save for a mortgage down payment. They are not here because they have no choice. They are here because it is a smart financial move, and they need the experience to match that decision.
• Property owners who want hands-off management and reliable tenants. They do not want to deal with constant turnover and problem tenants.

Secondary audience

• Graduate students and early-career professionals with stable income who value safety over the cheapest option
• International students and expats who need a predictable move-in process in an unfamiliar country
• People in life transitions (relocation, breakup, first job) who need stability quickly

Use cases and user stories

Young professional

I just moved to a new city for work. I do not know anyone here. I need a place that is safe, comfortable, and where the rules are clear from day one so I can focus on my job and my life, not on worrying about my living situation.

Young couple

We are saving for our own place. Shared living makes financial sense for us right now, but we need to trust the service, trust the conditions, and know exactly what we are paying and what we are getting. No surprises.

Property owner

I have an apartment but no time or desire to manage tenants. I want a service that handles everything, brings reliable people, and gives me stable income without me chasing late payments or dealing with conflicts.

The product is built around a small number of core journeys that guide users from discovery to long-term living. Each journey is designed to reduce uncertainty and support confident decision-making at every stage. Every transition between stages has a clear trigger and a clear set of expectations.

The central question

How can a product reduce perceived risk and make shared living feel safer and more predictable?

The answer is not one feature. It is a set of deliberate mechanisms embedded throughout the rental journey. Each one translates a research insight into a concrete product decision. Together, they form a system.

Core solution: Trust-building through verification

Problem

Users perceive shared living as risky due to unknown roommates and low predictability.

Solution

Safety is made visible before commitment through identity verification, mandatory viewing, and clear eligibility rules. You know who you are living with. They know who you are. The platform takes responsibility for that

Impact

Higher perceived safety, better match quality, fewer early drop-offs.

1. Viewing before renting

Problem

Users fear mismatched expectations and making a wrong decision about where they will live.

Solution

Every rental begins with a guided viewing, online or in person, before any commitment. I added this step on purpose. You cannot skip it. Because an informed decision beats a hopeful one, and one extra step now prevents regret later.

Impact

Reduced anxiety, fewer mismatches, more confident decisions.

2. Structured rental flow

Problem

Unclear next steps increase cognitive load and uncertainty during the moments that matter most.

Solution

A predictable, step-by-step process guides users from application to contract and move-in. Clear states, clear actions, clear expectations at every stage. Users can only apply to rent a room after the viewing is completed. The system enforces the order because the order is what builds confidence.

Impact

Lower cognitive load, higher completion, fewer support requests.

3. Personal dashboard

Problem

After move-in, often information is fragmented. Contracts in email, payment dates in a message somewhere, house rules in a PDF nobody saved.

Solution

A single dashboard centralizes everything: address, dates, payments, terms, documents, and support access. No hunting through emails. No confusion. When a user needs something, they find it immediately.

Impact

Clarity, control, and reduced post-move anxiety. That is not a feature. That is respect for someone's time.

4. Support architecture

Problem

High user uncertainty leads to constant direct contact with managers. That increases response time, operational costs, and slows down resolution for everyone.

Solution

The support flow is structured to resolve most issues without a manager. Users are guided to quick-access options first: FAQs, emergency help, neighbor complaints, repair requests, bug reporting. Live chat with a manager is there, but as a last resort, not the first option. The idea is simple: if a question can be answered without a human, it should be.

Impact

Faster resolution for common issues, reduced manager workload, lower operational costs. The support team handles what actually needs a human, not repetitive questions.

5. Emotional design & micro-interaction

Problem

Housing search is stressful. Steps like verification and applying for rent increase anxiety, and that is where people drop off.

Solution

I gave the app a character. Literally. A mascot that lives in the whole journey. It celebrates when your booking is confirmed. It is honest when something breaks. It gets super sad when you want to leave. It shows up in the boring parts, the frustrating parts, the good parts. Everywhere.

This is not decoration. It is a tiny guide that makes the whole experience feel less like a cold service and more like someone is actually there with you. During error states and technical issues, it acknowledges what you feel instead of pretending everything is fine.

Impact

Reduced perceived stress, improved task completion during high-friction stages, and sustained engagement throughout the journey.

Unified platform model

The platform acts as an intermediary layer between residents, properties, and owners. Contracts, payments, and lifecycle transitions are all managed in a single system.

Lifecycle architecture

The experience follows a clearly defined rental lifecycle:

Each stage determines available actions, system behavior, and user expectations.

Information continuity

Core data persists across the entire lifecycle: rental terms, payment schedule, documents, support history. No fragmented processes. Everything lives in one place, accessible at any point.

Operational standardization

Rental operations are standardized through a unified contract model, centralized coordination, and defined lifecycle states. This reduces manual complexity and supports scalability across properties. The system works because it is a system. Every part supports every other part.

The product was designed to support a stable, predictable rental model.

Revenue model

• Margin between room price and owner payout
• Minimum lease duration (4+ months) increases stability
• Late fees and structured payments reinforce discipline
• Room-based leasing improves yield per property

Business impact

• Better match quality leads to fewer early move-outs
• Structured flow reduces operational conflicts
• Predictable process strengthens retention
• Centralized model supports consistent platform performance

Operational efficiency

• Standardized contracts reduce legal and coordination overhead
• Lifecycle states streamline operations
• Self-service support lowers manager workload
• Unified system supports scalable property management

Long-term value

The model introduces more structure upfront. That is intentional. Because it enables higher retention, more stable contracts, better tenant-owner alignment, and predictable recurring revenue. It is more expensive to find a new tenant than to keep an existing one. I designed for the existing one.

Designing this model required deliberate trade-offs. Some decisions intentionally add friction to improve match quality and operational predictability. I am not pretending there are no costs:

Trust vs Speed

Verification and mandatory viewing slow initial conversion. But they reduce uncertainty and improve rental stability. Fewer mismatches, more reliable tenancies.

Friction vs Commitment

Extra steps also increase short-term effort. But they lead to more confident decisions and lower early churn. Higher-quality commitments for longer.

Structure vs Flexibility

Standardized contracts and defined lifecycle states limit flexibility. But they ensure clarity and consistent system behavior. Smoother operations, easier scaling.

Safety vs Maximum occupancy

Strict screening may reduce short-term fill rate. But it protects residents, property condition, and long-term platform performance. As long as platform’s reputation. Stronger retention, sustainable growth.

Responsibility vs Simplicity

Centralized mediation increases system complexity. But it keeps interactions consistent and coordinated. Lower uncertainty, more predictable operations.

Open questions I am still thinking about:

• How much friction is too much?
• Could mandatory viewing reduce the top of the funnel too aggressively?

These outcomes reflect the anticipated impact of a trust-first, structured rental model:

• Reduced early drop-off risk
• Increased decision confidence
• Lower cognitive load during critical steps
• Improved match quality and tenancy stability

What should be validated

• Does mandatory viewing actually improve match quality?
• Does the structured application reduce early drop-offs?
• Does visible verification increase decision confidence?
• Does self-service support lower operational load?

How to measure

• Viewing to application conversion rate
• Early move-out rate
• Support ticket volume
• Completion rate during verification

Beyond the interfaces, this project demonstrates a systems-level approach to product thinking. Here’s the main takeaways:

• Trust is a core product mechanism, not a nice-to-have
• Strategic friction improves long-term value when applied at the right moments
• Emotional design sustains engagement through the parts of the journey that nobody enjoys but everyone has to go through
• A system works because it is a system. Take one piece out and the rest feels incomplete.

File in Figma

Project details

Role: Product Designer (end-to-end) Timeline: November 2025 — February 2026 Platform: Mobile (iOS, Android) Tools: Figma, Jitter Type: Case study, full product design from scratch Industry: Proptech, co-living, shared housing, room rental Skills: Product Design, Product Thinking, UX Design, UI Design, Trust Architecture, Intentional Friction, Interaction Design, Identity Verification UX, Onboarding Flow Design, Emotional Design, Mascot System, Design Systems, Information Architecture, User Research, User Interviews, Prototyping, Systems Thinking, Support Architecture Location: Marseille, France Open to: Remote product designer roles in SaaS, fintech, proptech across Europe