From Design
to SVP.

Data Dive Tools is an Amazon seller analytics SaaS. The product helps sellers validate niches, launch products, and optimize listings. It tracks over 2.3 million keywords across the platform. Fast-moving, data-heavy, competing in a space where speed and signal-to-noise ratio are everything.

I joined as Head of Design, became VP of Product and Design three months later, and within eight months was SVP of Product and Engineering, owning vision, roadmap, and delivery across the full stack. That progression reflected exactly what the role became.

The clearest opportunity when I arrived: onboarding was a gauntlet. Amazon sellers, not data analysts, were bouncing before they ever saw the product’s value. The setup assumed expertise most users didn’t have.

We rebuilt onboarding using the “Validate, Launch, Optimize” framework. We met users where they actually were, not where the product assumed they were. Onboarding went from 42 minutes to 5, and 91% of users completed a first key action within 24 hours. That one change drove 86% faster time-to-value.

Key actions on a core product doubled, from 226K to 453K in 12 months. We didn’t get there by adding features. We got there by making the existing ones obvious. When users understand what a tool does for them in the first session, they come back. That’s the principle behind every product decision we made.

As my scope grew to include engineering, I focused on making product and development function as one unit: shared priorities, shared metrics, shared accountability. The $3.2M ARR was a result of that alignment, not any single feature.