Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill google-ads-benchmark-databasegit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-benchmark-database)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-benchmark-database"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-benchmark-database/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-benchmark-database"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-benchmark-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.07215 |
| Opus 5.5 | $0.00040 | $0.02886 |
| Sonnet 5.5 | $0.00020 | $0.01443 |
| Haiku 4.5 | $0.00010 | $0.00722 |
Grade A, and why
google-ads-benchmark-database scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 624 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Database
Complete database with Google Ads KPI benchmarks per industry, campaign type, and region for performance comparison and goal setting.
How to Pull Live Account Data First
Before applying benchmarks, pull actual account data via MCP to ground the comparison:
google_ads_run_gaql(query="
SELECT campaign.name, campaign.advertising_channel_type,
metrics.clicks, metrics.impressions, metrics.ctr,
metrics.average_cpc, metrics.conversions,
metrics.cost_per_conversion, metrics.conversions_value,
metrics.cost_micros
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
AND campaign.status = 'ENABLED'
ORDER BY metrics.cost_micros DESC
LIMIT 20
")
Compare the output against the benchmarks below to identify gaps.
Disclaimer
BENCHMARK DISCLAIMER
════════════════════
These benchmarks are compiled from:
├── WordStream/LOCALiQ "Google Ads Benchmarks 2025" (Sep 2025, ~16K campaigns)
├── LOCALiQ "Search Advertising Benchmarks for 2025" (updated Feb 2026)
├── WordStream "Conversion Rate Benchmarks" (updated Nov 2025)
├── Tinuiti "Digital Ads Benchmark Report Q4 2025" (Jan 2026)
└── Agency experience and case studies
IMPORTANT NUANCES:
├── Benchmarks are AVERAGES
├── Top 10% performers do 2-3x better
├── Bottom 10% performers do 2-3x worse
├── Your results depend on:
│ ├── Landing page quality
│ ├── Brand awareness
│ ├── Product/market fit
│ ├── Competition in your niche
│ └── Account history
USE FOR:
├── Initial target setting (new account)
├── Performance check (significant deviations)
├── Budget planning (CPA estimates)
└── Client benchmarking
DO NOT USE AS:
├── Absolute truth
├── Guarantee of results
└── Direct comparison without context
Search Campaign Benchmarks
CTR Benchmarks per Industry
SEARCH CTR BENCHMARKS (2025/2026)
═════════════════════════════════
┌────────────────────────────┬─────────┬─────────┬─────────┐
│ INDUSTRY │ AVG CTR │ TOP 25% │ TOP 10% │
├────────────────────────────┼─────────┼─────────┼─────────┤
│ Dating & Personals │ 6.05% │ 8.5% │ 11%+ │
│ Travel & Hospitality │ 4.68% │ 6.5% │ 9%+ │
│ Advocacy │ 4.41% │ 6.0% │ 8%+ │
│ Auto │ 4.00% │ 5.5% │ 7%+ │
│ Education │ 3.78% │ 5.2% │ 7%+ │
│ Real Estate │ 3.71% │ 5.0% │ 7%+ │
│ Health & Medical │ 3.27% │ 4.5% │ 6%+ │
│ Employment Services │ 2.42% │ 3.5% │ 5%+ │
│ Finance & Insurance │ 2.91% │ 4.0% │ 5%+ │
│ E-Commerce (Retail) │ 2.69% │ 4.0% │ 5%+ │
│ Consumer Services │ 2.41% │ 3.5% │ 5%+ │
│ Industrial Services │ 2.61% │ 3.5% │ 5%+ │
│ Home Goods │ 2.44% │ 3.5% │ 5%+ │
│ Legal │ 2.93% │ 4.0% │ 5%+ │
│ Technology │ 2.09% │ 3.0% │ 4%+ │
│ B2B │ 2.41% │ 3.5% │ 5%+ │
└────────────────────────────┴─────────┴─────────┴─────────┘
OVERALL SEARCH AVERAGE: 6.66% (LOCALiQ/WordStream 2025 report)
Note: significant increase vs prior years due to PMax, branded queries, and methodology shift
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 624 lines · 99 tokens per session scan A 3c0b494a8be3
google-ads-benchmark-database is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 29d ago), licensed MIT. It adds 99 tokens to every session and 7,215 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-11.
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