Nuvoro — Analytics-Led Product Design
SaaS Product Founder
Overview
As a founder building an early-stage scheduling platform, the challenge was not a lack of data but a lack of clarity on what metrics actually mattered. Without defined KPIs, it was difficult to evaluate product performance, validate assumptions, or prioritize features effectively.
My Role
Founder and analytics owner, responsible for defining success metrics, modeling product behavior in SQL, and using data to guide product and business decisions.
Data & Tooling
Used SQL to model core product entities such as businesses, services, bookings, and customers. Queried booking lifecycle data to produce decision-ready metrics for internal evaluation.
Approach
Defined core product KPIs including monthly revenue, Revenue growth %, week over week booking summary, and client booking behavior (visits, dollars spent, average spend)
Modeled the full booking lifecycle in SQL (No Show, confirmed, scheduled, cancelled, completed, expired) to ensure metrics reflected real operational outcomes
Used SQL analysis to validate assumptions about customer behavior and identify friction points in the booking flow
Used insights from analysis to prioritize roadmap decisions balancing customer value, operational simplicity, and speed to market
Outcome
Established core KPIs for bookings, no-shows, and utilization to support data-informed product decisions
Created a clear analytics foundation that replaced intuition with measurable signals during early product development. Enabled more confident prioritization decisions and a shared understanding of what success looks like for the product.
Visuals
Dashboard Screenshot
Data Model Diagram
What I'd Do Differently
Early assumptions about which metrics would matter evolved quickly. With hindsight, I would document metric definitions even earlier to reduce rework as the product and data model expanded.