Ad Ops & Cross-Channel Advertising Agent

Autonomous advertising operations framework for AI agents managing campaigns across Google Ads, Meta, LinkedIn, TikTok, and programmatic.

3,880 stars
Complexity: medium

About this skill

This skill transforms an AI agent into a proactive ad operations manager, capable of planning, auditing, optimizing, and reporting on digital advertising campaigns without direct dashboard interaction. It provides structured frameworks for strategic decisions, including a channel selection matrix, a 70/20/10 budget allocation rule, and a standardized campaign naming convention across platforms. The skill automates critical weekly tasks such as performance audits, which flag issues like inefficient spend (CPA >2x target), budget pacing problems, creative fatigue (CTR decline), audience overlap, and landing page misalignment (high bounce rates). It also includes an optimization playbook, providing specific actions for the agent to take based on performance signals, such as refreshing targeting for audience fatigue or A/B testing landing pages for conversion issues. By leveraging this skill, users can enhance the efficiency and effectiveness of their ad spend, reduce manual oversight, and ensure campaigns are consistently optimized towards performance goals. It provides a systematic approach for an AI agent to adapt strategies in real-time based on data-driven insights.

Best use case

The primary use case is autonomous, data-driven management and optimization of digital advertising campaigns across multiple platforms. Marketing teams, digital agencies, and businesses with significant ad spend will benefit most by empowering an AI agent to systematically monitor, analyze, and execute optimizations, freeing up human resources for higher-level strategy and creative development.

Autonomous advertising operations framework for AI agents managing campaigns across Google Ads, Meta, LinkedIn, TikTok, and programmatic.

Users should expect more efficient ad spend, improved campaign performance (CPA/ROAS), and reduced manual effort in managing cross-channel advertising campaigns.

Practical example

Example input

Run a weekly performance audit on our current ad campaigns, focusing on spend efficiency, budget pacing, and creative fatigue across Google Ads and Meta. Propose optimizations for any flagged issues.

Example output

Audit complete.
- **Spend Efficiency**: Campaign 'BRAND_META_CONVERSION_RETARGET_US_202310' flagged: CPA >2x target.
- **Budget Pacing**: Google Search channel at 115% weekly pace, consider adjustment.
- **Creative Fatigue**: Ad 'SpringSale_Banner3' on Meta, CTR decline >20% over 14 days.
- **Optimizations Proposed**: For 'SpringSale_Banner3', recommend new creative variants. Adjust Google Search budget to align with pacing.

When to use this skill

  • When managing complex cross-channel digital advertising campaigns (Google Ads, Meta, TikTok, etc.).
  • To automate routine performance audits, budget pacing, and creative fatigue detection.
  • For data-driven optimization of ad spend and campaign strategies based on predefined rules.
  • To enforce consistent campaign architecture and reporting standards across platforms.

When not to use this skill

  • For brand awareness campaigns where precise performance metrics are not the primary goal.
  • If you prefer complete manual control and real-time human decision-making for every ad campaign adjustment.
  • When dealing with very small or highly niche ad budgets that require minimal automation.
  • If you lack existing advertising campaigns or historical data for the agent to analyze and learn from.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/afrexai-ad-ops/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-ad-ops/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/afrexai-ad-ops/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Ad Ops & Cross-Channel Advertising Agent Compares

Feature / AgentAd Ops & Cross-Channel Advertising AgentStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexitymediumN/A

Frequently Asked Questions

What does this skill do?

Autonomous advertising operations framework for AI agents managing campaigns across Google Ads, Meta, LinkedIn, TikTok, and programmatic.

How difficult is it to install?

The installation complexity is rated as medium. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Ad Ops & Cross-Channel Advertising Agent

Autonomous advertising operations framework for AI agents managing campaigns across Google Ads, Meta, LinkedIn, TikTok, and programmatic.

## What This Skill Does

Turns your agent into an ad ops manager that can plan, audit, optimize, and report on cross-channel advertising — without touching a dashboard.

## Capabilities

### Campaign Architecture
- **Channel Selection Matrix** — Score 8 channels (Google Search, Display, Meta, Instagram, LinkedIn, TikTok, Programmatic, YouTube) across 6 factors: CPL range, intent level, audience precision, creative complexity, minimum viable budget, time-to-signal
- **Budget Allocation Framework** — 70/20/10 rule: 70% proven channels, 20% scaling channels, 10% experimental. Rebalance weekly based on CPA trends
- **Campaign Naming Convention** — `{brand}_{channel}_{objective}_{audience}_{geo}_{date}` — enforced across all platforms for clean reporting

### Performance Audit (Run Weekly)
1. **Spend Efficiency** — Flag any campaign with CPA >2x target or ROAS <1.5x
2. **Budget Pacing** — Alert if any channel is >110% or <80% of weekly pace
3. **Creative Fatigue** — Flag ads with CTR decline >20% over 14 days
4. **Audience Overlap** — Identify cross-channel audience collision (Meta + Google remarketing competing)
5. **Landing Page Alignment** — Check bounce rate by ad-to-page combination; flag >65%

### Optimization Playbook
| Signal | Action | Timeline |
|--------|--------|----------|
| CPA rising, CTR stable | Audience fatigue — refresh targeting | 48 hours |
| CPA rising, CTR falling | Creative fatigue — new variants | 24 hours |
| High CTR, low conversion | Landing page mismatch — A/B test | 72 hours |
| Low impression share | Budget cap or bid floor — increase or restructure | Same day |
| One channel dominates ROAS | Scale budget 20% weekly until CPA ceiling | Weekly |

### Budget Framework by Company Size

| Company Size | Monthly Ad Budget | Channels | Expected Pipeline |
|-------------|-------------------|----------|-------------------|
| Startup (1-10) | $2,000-$5,000 | 2 channels max | $20K-$50K |
| Growth (11-50) | $5,000-$25,000 | 3-4 channels | $50K-$250K |
| Scale (51-200) | $25,000-$100,000 | 5-6 channels | $250K-$1M |
| Enterprise (200+) | $100,000+ | Full stack | $1M+ |

### Channel-Specific Benchmarks (B2B SaaS, 2026)

| Channel | Avg CPC | Avg CPL | Avg CTR | Conv Rate |
|---------|---------|---------|---------|-----------|
| Google Search (branded) | $2-$5 | $15-$40 | 4-8% | 8-15% |
| Google Search (non-brand) | $5-$15 | $40-$120 | 2-4% | 3-6% |
| LinkedIn Sponsored | $8-$14 | $75-$200 | 0.4-0.8% | 2-4% |
| Meta (B2B lookalike) | $1-$4 | $30-$80 | 0.8-1.5% | 3-5% |
| Programmatic Display | $0.50-$2 | $50-$150 | 0.1-0.3% | 1-2% |
| YouTube Pre-roll | $0.03-$0.08/view | $80-$200 | 0.5-1% | 1-3% |
| TikTok (B2B emerging) | $1-$3 | $40-$100 | 1-2% | 2-4% |

### Reporting Template (Weekly)
```
WEEKLY AD OPS REPORT — Week of [DATE]

TOTAL SPEND: $[X] ([+/-]% vs budget)
TOTAL LEADS: [X] (Blended CPL: $[X])
TOTAL PIPELINE: $[X] (ROAS: [X]x)

BY CHANNEL:
[Channel] — $[spend] | [leads] leads | $[CPL] CPL | [ROAS]x ROAS
[repeat per channel]

TOP PERFORMERS:
- [Campaign] — [metric] ([why it works])

UNDERPERFORMERS (action required):
- [Campaign] — [metric] → [recommended action]

NEXT WEEK PLAN:
- [Action 1]
- [Action 2]
```

### 7 Ad Ops Mistakes That Burn Budget

1. **Running identical audiences across channels** — Cross-platform audience collision inflates your own CPMs. Segment by funnel stage per channel.
2. **Ignoring frequency caps** — Showing the same ad 15+ times doesn't build brand, it builds resentment. Cap at 3-5/week for prospecting.
3. **Optimizing for clicks instead of pipeline** — CTR is vanity. Optimize for cost-per-qualified-lead or cost-per-opportunity.
4. **No creative testing cadence** — Launching 1 ad and "seeing how it goes" is not a strategy. Run 3-5 variants, kill losers weekly.
5. **Budget allocation by gut** — "LinkedIn feels right" isn't data. Allocate by CPA-to-deal-value ratio per channel.
6. **Ignoring attribution windows** — LinkedIn's 90-day influence window vs Google's 30-day click. Comparing raw ROAS across channels is misleading.
7. **Manual bid management at scale** — If you're managing >20 campaigns manually, you're leaving 15-30% efficiency on the table. Automate or agent-ify.

### Industry Ad Strategy Quick-Reference

| Industry | Top 2 Channels | Key Metric | Budget Sweet Spot |
|----------|---------------|------------|-------------------|
| Fintech | Google Search + LinkedIn | Cost per qualified demo | $15K-$40K/mo |
| Healthcare | Google Search + Programmatic | Cost per HCP engagement | $10K-$30K/mo |
| Legal | Google Search + YouTube | Cost per consultation | $8K-$25K/mo |
| Construction | Google Search + Meta | Cost per RFQ | $5K-$15K/mo |
| Ecommerce | Meta + Google Shopping | ROAS (target 4x+) | $10K-$50K/mo |
| SaaS | LinkedIn + Google Search | Cost per trial signup | $10K-$35K/mo |
| Real Estate | Meta + Google Display | Cost per showing/inquiry | $5K-$20K/mo |
| Recruitment | LinkedIn + Indeed/programmatic | Cost per application | $8K-$25K/mo |
| Manufacturing | Google Search + LinkedIn | Cost per RFQ | $5K-$15K/mo |
| Professional Services | LinkedIn + Google Search | Cost per consultation | $8K-$30K/mo |

---

## Get Industry-Specific Ad Strategy

These frameworks give you the structure. For deep industry context — compliance rules, audience segments, messaging angles, competitive positioning — grab the full context packs:

**[AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/)** — $47 each | Pick 3 for $97 | All 10 for $197

10 industries. Real operator knowledge, not recycled blog posts.

**Free tools:**
- [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find where you're losing money
- [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Configure your first AI agent in 5 minutes

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