Maxime Amoudruz

Design systems specialist enabling teams to ship consistent high-impact products at scale.

Asking sensitive questions to improve property purchase experience

When trust is designed into the system, sensitive interactions become usable, scalable, and reliable.

Product design2019–2020

I joined Crowdhouse as the first Product Designer, when the organisation was still small and the product in its early stages.

Over three years, the company scaled from 10 to 140 employees. During that time, I helped shape both the product and the design practice—moving from foundational work to addressing increasingly complex user and business challenges.

This case study focuses on a later initiative: improving buyer profile completion by asking sensitive questions in a way that preserved trust, while enabling more relevant and effective property recommendations.

The challenge

The core challenge was trust: gathering meaningful data without breaking user confidence.

One initiative focused on improving buyer profile completion so advisors could offer more relevant, tailored property recommendations. To achieve this, the product needed to collect highly sensitive information such as income and wealth.

Asking too directly risked abandonment or incomplete data—undermining both user experience and business value. Asking too indirectly risked reducing the quality and usefulness of the information.

The challenge was to design an experience that felt respectful, transparent, and in the user’s control—while maintaining the integrity of the data being collected.

Trust as a product constraint

Trust was not an abstract concept—it was a product constraint.

In real estate investment, users are making high-stakes decisions and are highly sensitive to how their information is handled. This meant the experience could not feel transactional or invasive.

The flow needed to feel intentional and guided—providing clarity on why information was being requested, how it would be used, and what users could expect in return.

Designing for trust required balancing transparency, control, and progression throughout the experience.

Designing for comfort and transparency

The experience was framed as a dialogue to reduce intrusiveness while preserving clarity and control.

After multiple iterations, we implemented a conversational, multi-step questionnaire. This approach leveraged familiar interaction patterns while allowing for progressive disclosure—reducing cognitive load and perceived friction. This enabled us to:

  • Reduce perceived intrusiveness
  • Keep the interface clean and focused, especially on mobile
  • Give users a clear sense of control and progress

The goal was not just completion, but perception—ensuring the experience felt trustworthy, understandable, and easy to navigate.

Validation signals

Success was measured across perception, behaviour, and data quality—not just completion rates.

Once the new feature has been shipped, we evaluated:

• Completion rate and drop-off across steps
• Quality and consistency of submitted profile data
• Qualitative feedback on clarity and trustworthiness

This allowed us to validate not only whether users completed the flow, but whether they felt confident and comfortable doing so.

Embedding into the design system

The questionnaire patterns were contributed back into the design system as reusable components.

This transformed the solution from a single feature into a scalable pattern. Teams could reuse and adapt the approach for other sensitive-data flows, reducing duplication and ensuring consistency across the platform.

By embedding these patterns into the system, we lowered the cost of future implementations while increasing confidence in how sensitive interactions should be handled.

Impact

This work established a reusable pattern for sensitive data collection while improving both trust and data quality.

The outcomes extended beyond a single feature and influenced how similar interactions were designed across the product.

Data Quality

This work established a reusable pattern for sensitive data collection while improving both trust and data quality.

Advisor effectiveness

Richer and more accurate profiles enabled advisors to deliver more relevant, tailored property recommendations.

Positive perception

Post-release feedback reflected increased confidence in the clarity, transparency, and trustworthiness of the experience.

Scalable contribution

The questionnaire components were reused across the platform, extending the impact beyond the initial feature.

Designing for trust resulted in a durable interaction pattern that could scale with the product.

Final thoughts

Designing for trust is as critical as designing for usability—especially when asking users to share sensitive information.

When familiar patterns, progressive disclosure, and clear intent are combined, teams can balance business needs with user confidence—creating experiences that are both effective and respectful.

Crowdhouse offers accessible investments in Swiss real estate. Founded and profitable since its 2015 start, it has grown to over 140 employees and placed more than 1B CHF of real estate with investors through its platform.

crowdhouse.ch

Crowdhouse

Real Estate Investment