Recruitment Channel ROI Diagnoser

Problem

A low cost per hire does not prove a channel is healthy: resumes may be imprecise, offer conversion may be weak, and new hires may leave quickly. If a team only compares spend and hires, it can overinvest in high-volume, low-quality channels and miss differences in headhunter billing, brand ad spend, sample size, and trend changes that affect budget decisions.

How It Works

The skill accepts recruitment channel data in Markdown, Excel, CSV, or plain-text channel descriptions. It first validates cascading counts: resumes >= interviews >= offers >= hires, retained hires <= hires, positive spend, and at least two comparable channels. It then calculates cost, conversion, and quality metrics by channel, ranks them by a composite score, and compares funnel stages.

Key capabilities include:

• Using a quality coefficient to correct rankings and surface channels that are cheap but retain poorly
• Producing increase, hold, or reduce budget recommendations with expected adjustment ranges
• Handling missing retention data, single-channel inputs, zero hires, and small sample sizes
• Flagging headhunter versus platform billing differences, brand ad treatment, period-over-period trends, and channel fatigue signals

Boundaries

It is best suited to diagnosing existing recruitment channel data, not automatically scraping job platforms or replacing compensation, talent profiling, and employer brand judgments. With small hire samples, conclusions are directional; budget changes should keep control channels so the next cycle can attribute results.