This workflow automates employee retention analytics by combining candidate performance data with trait-level retention statistics. It scores candidates, validates data, and generates a polished Retention Digest HTML email using GPT (Azure OpenAI). Hiring managers receive structured insights weekly, highlighting top/weak traits, candidate scores, and actionable JD refinement tips.
⚡ Manual Trigger – Starts workflow execution on demand.
📑 Candidate Data Fetch (Google Sheets – Hires Tracking) – Pulls candidate-level details like name, role, traits, start date, and retention status.
📑 Trait Summary Fetch (Google Sheets – Retention Summary) – Fetches aggregated trait-level retention statistics, including hires, stayed, left, retention %, and weight adjustments.
🔀 Merge Candidate + Trait Data – Combines both datasets into a unified stream for scoring.
🧮 Candidate Scoring & Data Normalization (Code Node) –
Google Sheets (Hires Tracking + Retention Summary + Error Log)
Gmail API credentials
Azure OpenAI access (gpt-4o-mini model)
n8n instance (self-hosted or cloud)
✅ Automates retention analytics & reporting
✅ Provides AI-powered insights in structured HTML
✅ Improves hiring strategy with trait-based scoring
✅ Reduces manual effort in weekly retention reviews
✅ Ensures reliability with error handling & validation
HR & Recruitment teams monitoring post-hire retention
Organizations optimizing job descriptions & hiring strategy
Talent analytics teams needing automated, AI-driven insights
Stakeholders requiring clear weekly digest emails