Individual skill

roi-benchmark-library

Reference benchmarks for CAC, CPL, ROAS, and payback across channels and segments.

plugins/marketing-analytics/skills/roi-benchmark-library/SKILL.md

Read pinned source

Source commit 78e0419f4440bcb43bc80127e174ecf5adef1753

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Instructions only
Last checked
Nov 10, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
438
Repository last updated
Apr 3, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# ROI Benchmark Library Skill

## When to Use
- Comparing current performance vs historical or industry benchmarks.
- Setting guardrails for budgeting, pacing, and campaign approvals.
- Equipping finance/marketing leaders with realistic ROI expectations.

## Framework
1. **Benchmark Sources** – internal history, partner data, analyst reports, industry surveys.
2. **Segmentation** – channel, region, persona, product, funnel stage.
3. **Metric Definitions** – CAC, CPL, ROAS, payback, pipeline-to-spend, revenue-to-spend.
4. **Update Cadence** – monthly for active channels, quarterly for strategic benchmarks.
5. **Usage Guidance** – when to escalate variances, how to contextualize outliers.
Back to top