Industry
AI and privacy
Client
Decentriq
Position
Head of product design
Unlocking confidence in data collaboration and ML
AI, Security and privacy @Decentriq
Large organizations such as banks, insurers, and hospitals increasingly need to collaborate and share sensitive data to unlock AI-driven insights, from identifying individuals at risk for disease to predicting insurance demand. The challenge is enabling this collaboration while meeting strict privacy regulations and protecting sensitive information.
What I did on the project
When I joined Decentriq, the platform was a "technological powerhouse" with a "usability bottleneck." The experience was fragmented and highly technical, which stalled the sales cycle for non-technical stakeholders and limited the platform’s expansion within the MarTech ecosystem. My job was to transition the product from a specialized technical tool to an enterprise-grade platform capable of supporting multi-persona collaboration at scale.
The Executive Strategy: Product-Led Transformation
I defined and championed a product experience strategy that aligned Design, Engineering, and Sales. I moved the organization from a feature-centric roadmap to a outcome-oriented vision, focusing on three strategic pillars: Trust, Velocity, and Accessibility.
Goals
Main issues:
High cognitive load for non-technical users
Poor discoverability of core features
Limited transparency around data usage
No scalable design system to support growth
Inconsistent visual language and workflows
These problems directly impacted confidence, retention, and expansion.
What we shipped
Platform redesign to increase usage
New look and feel, onboarding, navigation
The Decentriq platform redesign focused on improving usability, clarity, and trust across core workflows. I led the definition of product goals and priorities, guiding the team toward a modern visual identity, simplified onboarding, and improved navigation.
Step-by-step guidance and in-context support reduced onboarding friction, while a clearer information architecture improved discoverability and task completion. These changes were validated through user research and iterative testing, ensuring they delivered measurable improvements to user confidence and efficiency.
New design system
To support product scalability and faster iteration, I led the introduction of a structured design system. The system established a cohesive visual language through modern typography, a refined color palette, and consistent iconography, reinforcing Decentriq’s credibility in an enterprise context.
Reimagined components improved clarity, accessibility, and interaction quality, while responsive and modular layouts enabled consistency across devices. Centralized guidelines improved alignment between design and engineering, reducing rework and accelerating product delivery. The design system became a foundational asset for ongoing product development.
Importance of discovery
Customer design program
I conducted user interviews and usability testing, ensuring product decisions were grounded in real customer needs. This research surfaced key insights that directly informed roadmap priorities:
01
Transparency: Users needed clear visibility into how their data was processed and governed.
02
Real-time feedback: Users expected immediate feedback during critical actions such as data uploads or audience definition.
03
Privacy controls: Privacy safeguards, including anonymization thresholds, were essential for adoption and regulatory compliance.
Personas
Personas alignment
To align product decisions across teams, I helped define three primary user types:
01
Data analyst:
Focused on secure collaboration, governance, and correct data handling.
02
Campaign manager:
Responsible for activating audiences efficiently across ad platforms.
03
Marketing manager:
Needed an intuitive way to upload data, define segments, and evaluate campaign potential without technical overhead.
This shared understanding enabled clearer prioritization and reduced ambiguity across product initiatives.
Feature Spotlight: Audience Builder
The Audience Builder addressed major workflow bottlenecks for users handling complex datasets.
01
Fragmented audiences:
Data scattered across multiple segments made it difficult to create cohesive targeting strategies. The Audience Builder enables seamless dataset combination to support unified audience creation.
02
Complex filtering:
Refining audiences through filters and criteria was time-consuming and error-prone. The new experience introduced an intuitive interface with real-time visualization and feedback.
03
Limited flexibility:
Traditional tools often required technical expertise to create tailored segments. The Audience Builder removed these barriers, enabling faster experimentation without coding or data science support.
What colleagues say about working with me
KPIs
Decentriq’s platform redesign, design system, and new features streamlined workflows, improved confidence in data collaboration and the product position in a highly regulated market.
