Measure and optimize the hiring funnel: stage conversion rates, time-to-hire, cost-per-hire, source quality, offer-acceptance, and recruiter productivity. Use when the user asks for recruiting KPIs, hiring metrics dashboards, funnel analysis, ATS reporting, or diagnosing why hiring is slow/expensive.
npx skillsify add recruitment-funnel-analyticsOffer acceptance below ninety percent is a compensation or process problem, and high application volume with low screen-pass is a JD problem — this skill's diagnostic playbook maps each funnel symptom to its likely cause and fix. It defines the core formulas precisely: stage conversion by source and role, time-to-hire as median plus p90, cost-per-hire including allocated recruiter time, and quality-of-hire as a composite of ninety-day retention, manager satisfaction and first-review performance. Deliverables are a KPI definitions sheet, funnel dashboard spec and weekly pipeline report with aging-requisition alerts.
---
name: recruitment-funnel-analytics
description: "Measure and optimize the hiring funnel: stage conversion rates, time-to-hire, cost-per-hire, source quality, offer-acceptance, and recruiter productivity. Use when the user asks for recruiting KPIs, hiring metrics dashboards, funnel analysis, ATS reporting, or diagnosing why hiring is slow/expensive."
---
# Recruitment Funnel Analytics
## Purpose
Turn ATS data into decisions. Modeled on recruitment-funnel analytics features in modern ATS platforms (smart-ats funnel analytics, OpenCATS reporting, Frappe HRMS recruitment reports).
## Core funnel & formulas
Stages: Sourced → Applied → Screened → Interviewed → Offered → Hired.
- **Stage conversion %** = next-stage count / current-stage count (per stage, per source, per role)
- **Time to hire** = days from application to offer acceptance (report median + p90, by department)
- **Time to fill** = days from requisition open to acceptance
- **Cost per hire** = (ads + tools + agency fees + referral bonuses + allocated recruiter time) / hires
- **Quality of hire** = 90-day retention × hiring-manager satisfaction × first-review performance (composite)
- **Offer acceptance rate** = accepted / extended (target ≥90%; below = comp/process problem)
- **Source effectiveness** = hires per source AND quality-adjusted hires per source — cut sources that deliver volume without conversions
## Diagnostic playbook
| Symptom | Likely cause | Fix |
|---|---|---|
| High application, low screen-pass | JD mismatch / wrong channels | rewrite JD, re-target sourcing |
| Low interview→offer | mis-calibrated screening or interviewers | recalibrate rubric, interviewer training |
| Low offer acceptance | comp below market / slow process / candidate experience | comp review, compress timeline |
| Long time-to-fill, small funnel | sourcing shortage | sourcing plan, referral program |
| High early attrition (<90 days) | mis-sold role / bad onboarding | realistic job preview, onboarding fix |
## Deliverables
- KPI definitions sheet (formula, owner, target, frequency)
- Funnel dashboard spec: table per role × stage with conversion %, median days, bottleneck highlight
- Weekly recruiting report template (pipeline health, aging reqs >45 days, SLA breaches)
- Cohort analysis template (quality of hire by source/quarter)
Design the end-to-end candidate journey and communication templates: application, scheduling, prep, updates, rejection, and offer-stage messaging that protects employer brand. Use when the user asks for rejection email templates, candidate communication sequences, interview prep packs, or improving candidate experience/NPS.
0 installs · v1.0.0
Build employer brand and Employee Value Proposition: EVP definition, careers-page content, recruitment marketing, review-site management, and talent-audience campaigns. Use when the user asks to improve employer brand, write a careers page, define an EVP, respond to Glassdoor/Indeed reviews, or run recruitment marketing.
0 installs · v1.0.0
Audit hiring pipelines, job ads, screening criteria, and AI-recruiting tools for bias and legal/compliance risk (disparate impact, EU AI Act high-risk rules, PDPL/GDPR candidate data). Use when the user asks to check fairness of a hiring process, audit an AI screening tool, review adverse-impact metrics, or make recruitment compliant.
0 installs · v1.0.0