Roi Benchmark Library

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

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

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

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

Templates

Benchmark matrix (channel x metric x segment).
Variance alert sheet with thresholds + recommended actions.
Executive summary page for QBRs.

Tips

Normalize for currency changes and attribution windows before comparing.
Pair with monitor-channel-pacing to trigger alerts against guardrails.
Share benchmark deltas with channel owners to inform creative/test roadmaps.

More on the bench

Email Sequence

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Alireza Rezvani

marketing-growth-copy+2

Launch Brand Kit

Packages updated brand guidelines, assets, and enablement resources for GTM teams.

marketing-growth-copy+2

Registration Ops

Use when configuring registration flows, reminders, and data sync for webinars.

sales-gtm-revops+2

Sharebench · Public bench

Connect via MCP.

Add the public bench to any AI tool. Your agents read every artifact you see — no signup needed.

1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
  "mcpServers": {
    "sharebench-public": {
      "url": "https://mcp-public.sharebench.ai"
    }
  }
}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
url = "https://mcp-public.sharebench.ai"

2Ask your agent for an artifact

Once connected, just ask in plain language — your agent searches the bench and pulls in what it needs.“Pull the brand voice from sharebench and rewrite this draft.”