--- title: The Product Health Score: How I Reduced Critical... description: A B2B SaaS platform reduced critical incidents by 35% using an automated monitoring system built with n8n. The solution includes a Product Health Score (0-100)... canonical: https://daily.dev/posts/the-product-health-score-how-i-reduced-critical-incidents-by-35-with-unified-monitoring-and-n8n-au-37ju9blxm twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation | daily.dev og:description: A B2B SaaS platform reduced critical incidents by 35% using an automated monitoring system built with n8n. The solution includes a Product Health Score (0-100)... og:url: https://daily.dev/posts/the-product-health-score-how-i-reduced-critical-incidents-by-35-with-unified-monitoring-and-n8n-au-37ju9blxm og:image: https://api.daily.dev/og/posts/37jU9BLXM.png og:image:alt: The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # The Product Health Score: How I Reduced Critical Incidents by 35% with Unified Monitoring and n8n Automation **[Towards Data Science](https://daily.dev/sources/tds)** · 10 min read · 0 upvotes · 0 comments ## Summary A B2B SaaS platform reduced critical incidents by 35% using an automated monitoring system built with n8n. The solution includes a Product Health Score (0-100) that aggregates incident volume, severity, affected users, and business metrics like MRR and churn. Four automated streams detect anomalies in revenue, feature usage, and system health using z-score analysis, then leverage AI to generate root cause hypotheses and send alerts via Slack and email. A unified dashboard consolidates scattered data from Notion, Slack, PostgreSQL, and Google Sheets into a single source of truth, enabling faster incident response and saving 10 hours per week of manual investigation. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Cutting Customer Case Volume 20x with Petabyte-Scale Health Signals](https://daily.dev/posts/cutting-customer-case-volume-20x-with-petabyte-scale-health-signals-jgf5of23j) · Salesforce Engineering · 0 upvotes · 0 comments - [The Innovation Paradox: How We Reduced Incidents by 25% While Deploying Faster](https://daily.dev/posts/the-innovation-paradox-how-we-reduced-incidents-by-25-while-deploying-faster-uaztzi4rc) · Cisco · 0 upvotes · 0 comments - [I built a monitor. 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