Know which product actually pays your hours — revenue/$ per hour dashboard

Executive Summary

Independent makers, solo founders and micro‑SaaS operators—roughly 1,000,000 creators averaging $20,000/year—regularly misjudge which products or features actually justify the hours they invest, tracking gross revenue but not revenue per hour or effective hourly rates. That blind spot forces bad prioritization: building low‑yield features, running costly experiments, or keeping legacy products that consume time but barely pay. You could build a lightweight dashboard that links billing metadata (Stripe, App Store, Paddle) to tracked or estimated hours per product, feature or cohort, surfacing revenue-per-hour, LTV-per-hour and comparative unit economics with opinionated defaults and simple manual tagging for ambiguous cases. Aim for 30‑minute setup, integrations with time trackers and PM tools, exportable reports and an API; pricing could be founder‑friendly (single‑digit to low‑double‑digit $/month tiers) to match budgets. This is an attractive moment: total addressable creator revenue is roughly $20B and the trend toward creator economy scale, mature billing APIs and an increased focus on LTV/CAC and labor economics pushes founders to seek lightweight, actionable analytics. Market and revenue potential scores are high (92/100 and 88/100 respectively), and competition is currently low for tools that explicitly optimize for hours‑to‑revenue rather than only subscription metrics. To stand out, specialize on labor‑aware metrics, provide a fast, opinionated UX and reliable connectors while offering clear guidance for attribution and decisions, not just dashboards. The main challenges will be accurately attributing revenue across bundles and shared infrastructure, handling privacy/consent for billing data, and convincing tight‑budget founders to instrument time tracking, but solving those creates a defensible niche versus generalist incumbents that focus on MRR or churn rather than effective hourly rates.