Lighthouse misleads product teams — map metrics to real conversions

Many product teams treat Lighthouse scores as a proxy for user experience, but Lighthouse is a lab tool that simulates conditions and often misleads prioritization because it doesn’t show which performance improvements actually move conversions. This creates a pain point for product managers, growth teams and engineers at digital-first companies—roughly 200,000 sites investing in UX—who must choose fixes that change revenue, not just improve synthetic scores. You could build a RUM-first platform that ingests real-user telemetry and analytics, correlates Core Web Vitals and other performance signals with funnel conversion and retention by cohort, and surfaces prioritized fixes with estimated dollar impact. Differentiate by pairing AI-driven causal and uplift modeling with out-of-the-box integrations to GA/Heap/Segment and ad platforms, lightweight instrumentation suitable for one-day installs, and prescriptive runbooks that tie fixes to revenue; strengths are clear ROI messaging and alignment with search/ad enforcement, while challenges include noisy attribution, privacy/compliance limits, and the need for strong initial reference customers. The timing is favorable: Core Web Vitals enforcement and ad-platform cost/quality signals create direct ROI pressure to optimize UX, RUM has become the preferred data source, and AI-driven observability makes mapping performance to business outcomes feasible at scale. Addressable market estimates are $6.0B (200,000 digital-first sites × $30K ACV), with a Market Score of 90/100 and Revenue Potential 88/100, and competition is medium—many APM/RUM vendors exist but few focus on conversion-mapped remediation—so a focused, proof-driven launch in a narrow vertical with 10–15 pilots would mitigate execution risk.