Research & Insight

Speed, Clarity and Reuse

Research creates the most value when it is operationalized—embedded into how teams plan, prioritize, and make decisions. My approach to research and insight operations focuses on speed, clarity, and reuse, ensuring that user insight continuously informs strategy without slowing delivery.

Research is not a phase. It is a capability.

Research Operations Model

I’ve implemented research operations models that scale across teams and products, combining qualitative and quantitative methods to reduce risk and increase confidence.

Common methods and tools include:

• User testing for usability and concept validation

• Behavioral analytics using tools such as Hotjar, Pendo, and Google Analytics

• A/B testing to validate design and product decisions

• Surveys to capture attitudinal and directional feedback

These methods are selected based on decision risk, timeline, and business impact

Insight Capture, Sharing & Reuse

Insights only matter if they are seen, understood, and reused.

To ensure visibility and longevity, I focus on:

• Presenting key findings directly to stakeholders

• Sharing concise summaries via email for fast consumption

• Maintaining centralized documentation in Confluence

• Tagging and organizing insights for future reference

The goal is to move beyond one-off studies toward institutional knowledge that compounds over time.

Influencing the Product Roadmap

Research has the greatest impact when it informs decisions upstream.

I ensure insights are:

• Presented during roadmap planning and prioritization

• Framed around risks, opportunities, and tradeoffs

• Connected directly to business and customer outcomes

By bringing user evidence into roadmap conversations, research shifts discussions from opinion-based debate to informed decision-making.

Balancing Speed and Rigor

Not every decision requires the same level of rigor.

I encourage teams to right-size research by considering:

• Cost of being wrong

• Time sensitivity

• Scope and reach of the decision

In high-risk or strategic initiatives, deeper research is warranted. In fast-moving or low-risk contexts, lightweight testing and directional insight often provide enough signal to move forward confidently.

This balance allows teams to learn quickly without sacrificing quality where it matters most.

Artifacts & Practices

To support scalable research operations, I rely on:

• Research repositories housing studies, insights, and recordings

• Insight frameworks that synthesize findings into themes and opportunities

• Stakeholder readouts designed for decision-making, not just reporting

• Case examples where research directly influenced or changed product strategy

These artifacts help teams build on past learning rather than starting from scratch.

Example: Research Changing Strategy

In one instance, early usability testing and behavioral data revealed that a planned feature set addressed edge cases rather than core user needs. By presenting these insights during roadmap planning, we were able to pivot investment toward higher-impact workflows—reducing development risk and improving adoption post-launch.

This shift reinforced the value of bringing research into strategic conversations early, not after decisions had already been made.

This Enables

• Faster, more confident decision-making

• Reduced rework and wasted effort

• Stronger stakeholder trust in UX

• A shared understanding of user needs across teams

When research is operationalized effectively, it becomes a strategic advantage—guiding direction, shaping priorities, and grounding decisions in real user behavior.