Over the years, I’ve refined a structured process that helps me move from identifying a real user or business problem to delivering a measurable product impact. This approach combines research, product thinking, and storytelling – ensuring every design decision connects to business goals and user needs.

Define the problem

Everything starts with clarity. I begin by formulating a clear problem statement – what exactly isn’t working and for whom.

Example: “40% of new users drop off on day one because onboarding feels confusing.”

The goal is to articulate the issue in a way that the product team understand and care about.

Connect it to strategy

Not every problem deserves immediate attention. I evaluate why this problem matters in the context of company priorities and growth goals.

Who is the target segment, what metric does this influence (activation, retention, monetisation), and how does solving it move us toward the strategic goals?

Support it with data

Next, I gather quantitative and qualitative evidence: analytics, user interviews, NPS comments, behavioural heat maps, or funnel data.

If data is missing, I make it a priority to get it before moving forward. Understanding the scale (“how many”, “how often”, “why”) helps me focus on the highest-impact problems.

Analyze the current user journey

I map out the existing experience, highlighting friction points and emotional drop-offs.

This usually involves screenshots, user recordings, or a simplified flow diagram showing where users struggle or disengage.

When needed, I record short walkthrough videos to help the team visualize the issue.

Explore and define solutions

Then I move into the ideation phase – generating and testing potential design directions.

I describe how each concept solves the root cause, not just the symptom. I aim to avoid over-designing: changing one variable at a time makes impact easier to measure.
I often prepare alternative solutions in case trade-offs or constraints emerge during review.

Visualize improvements (before & after)

I create clear visual comparisons between the current and proposed designs.

This helps the team and stakeholders quickly see what’s changing and why. It also becomes a useful artefact later to evaluate what worked and what didn’t after release.

Define expected outcomes and metrics

For each solution, I set measurable success criteria.
What metrics should move – activation, D1/D7/D30 retention, churn, completion rate – and by how much?
I also define how long the experiment or A/B test should run and how we’ll interpret the results.

Assess risks and constraints

Every design decision has potential risks – technical, behavioral, or market-related.

I identify them early and outline mitigation plans. Having a backup plan (plan B) helps the team stay confident even if the first iteration fails.

Estimate implementation and timeline

I collaborate with PMs and developers to estimate effort and define milestones. We clarify which sprints will include design and development, which resources are needed, and when we expect to see measurable outcomes.

Validate and iterate

After launch, I track the actual performance against expected results. If data doesn’t confirm improvement, I dig into why – was it the hypothesis, execution, or timing?
Then I iterate quickly, improving step by step rather than waiting for a perfect solution.

In summary

This process helps transform design work into a measurable, story-driven practice. Each step builds on the previous one: from understanding the problem to visualizing change, forecasting outcomes, and closing the loop with data.

It keeps the team aligned, focused on real impact, and ensures design decisions always serve both user value and business growth.