Research and Iteration Process

Data-Driven Approach

I take a systems-thinking, data-driven approach to product management, ensuring alignment between business objectives and user needs. My process involves deconstructing business requirements, mapping end-to-end user flows, and proactively identifying risks.

To optimize decision-making, I leverage A/B testing, heatmaps, user session replays, and qualitative feedback to refine hypotheses and validate solutions. Success is measured through key KPIs like conversion rates, engagement, and retention, ensuring continuous improvement based on user behavior.

Stakeholder & User-Centered Strategy

Collaboration is key—I work closely with engineering, design, and business teams to align on priorities, trade-offs, and risks. By clearly communicating insights and alternatives, I drive informed decision-making while balancing speed and scalability.

User insights guide every step, using journey maps, interviews, surveys, and behavioral analytics to uncover pain points and refine experiences.

“Build to Learn” Mindset

As a product manager, I approach every project with a 'built to learn' mindset, continuously leveraging user behavior insights and analytics tools to refine and deliver meaningful value to the end user.

Data-Driven Implementation & Continuous Refinement

User behavior data is at the core of both implementation and post-release optimization. While A/B testing is ideal for validating changes, I recognize it’s not always feasible. In such cases, rapid iteration—guided by user research, intuition, and historical data—is essential, ensuring every change is backed by a clear validation method.

Post-release, I rely on tools like Quantum Metric and Clarity to analyze real user behavior through heatmaps, session replays, and funnel analysis. These insights enable fast, data-driven decisions, helping to refine the product, address pain points, and drive continuous improvement.