ads-budget
Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and identifies campaigns to kill or scale. Uses 70/20/10 rule, 3x Kill Rule, and 20% scaling rule. Use when user says budget allocation, bidding strategy, ad spend, ROAS target, media budget, or scaling.
Best use case
ads-budget is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and identifies campaigns to kill or scale. Uses 70/20/10 rule, 3x Kill Rule, and 20% scaling rule. Use when user says budget allocation, bidding strategy, ad spend, ROAS target, media budget, or scaling.
Teams using ads-budget should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ads-budget/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ads-budget Compares
| Feature / Agent | ads-budget | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and identifies campaigns to kill or scale. Uses 70/20/10 rule, 3x Kill Rule, and 20% scaling rule. Use when user says budget allocation, bidding strategy, ad spend, ROAS target, media budget, or scaling.
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.
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SKILL.md Source
# Budget Allocation & Bidding Strategy ## Process 1. Collect budget and performance data across all active platforms 2. Read `ads/references/budget-allocation.md` for allocation framework 3. Read `ads/references/bidding-strategies.md` for strategy decision trees 4. Read `ads/references/benchmarks.md` for CPC/CPA benchmarks 5. Read `ads/references/scoring-system.md` for health score algorithm 6. **Validate**: confirm spend data covers ≥14 days before evaluating kill/scale decisions 7. Evaluate budget allocation, bidding strategy, and scaling readiness 8. **Validate**: verify kill list candidates have sufficient data (≥20 clicks or ≥$100 spend) before recommending pause 9. Generate recommendations with kill list and scale list ## Budget Allocation Framework ### 70/20/10 Rule - **70%** on proven channels (consistent ROAS/CPA targets met) - **20%** on scaling channels (showing promise, need more data) - **10%** on testing channels (new platforms, audiences, creatives) ### Platform Selection Matrix | Business Type | Primary | Secondary | Testing | |---------------|---------|-----------|---------| | SaaS B2B | Google Search, LinkedIn | Meta, YouTube | TikTok, Microsoft | | E-commerce | Google Shopping, Meta | TikTok, YouTube | Microsoft, LinkedIn | | Local Service | Google Search, Google LSA | Meta | Microsoft, YouTube | | B2B Enterprise | LinkedIn, Google Search | Meta | Microsoft, TikTok | | Info Products | Meta, YouTube | Google Search | TikTok | | Mobile App | Meta, Google UAC | TikTok | Apple Search Ads | | Real Estate | Google Search, Meta | YouTube | Microsoft | | Healthcare | Google Search | Meta | Microsoft, YouTube | | Finance | Google Search, Meta | LinkedIn | Microsoft | | Agency (clients) | Varies by client | N/A | N/A | ### Budget Sufficiency Rules | Platform | Minimum Daily | Learning Phase Budget | |----------|--------------|----------------------| | Google Search | $20/day | Sufficient for 15+ conv/month | | Google PMax | $50/day | Sufficient for algorithm optimization | | Meta | $20/day per ad set | ≥5x target CPA per ad set | | LinkedIn | $50/day Sponsored Content | 15+ conversions/month | | TikTok | $50/day campaign, $20/day ad group | ≥50x target CPA per ad group | | Microsoft | No strict minimum | Sufficient for stable delivery | ## Bidding Strategy Evaluation ### Google Ads Bidding Decision Tree ``` Start ├─ <30 conversions/month? │ └─ Use Maximize Clicks (cap CPC at benchmark) │ └─ When >30 conv/month → Maximize Conversions ├─ 30-50 conversions/month? │ └─ Use Maximize Conversions │ └─ When stable CPA → Target CPA ├─ >50 conversions/month? │ └─ Use Target CPA │ └─ When revenue tracking → Target ROAS └─ Revenue tracking active + >50 conv/month? └─ Use Target ROAS ``` ### Meta Ads Bidding - **Lowest Cost (default)**: best for volume, may have CPA variance - **Cost Cap**: sets CPA ceiling, may reduce volume - **Bid Cap**: maximum bid per auction, most control - **ROAS Goal**: target return on ad spend - **CBO vs ABO**: CBO for proven campaigns, ABO for testing ### LinkedIn Bidding - **Cost Per Send (CPS)**: for Message Ads - **Maximum Delivery**: for Sponsored Content (recommended) - **Manual CPC**: for tight budget control - **Target Cost**: for predictable CPA ### TikTok Bidding - **Lowest Cost**: maximize conversions within budget (volume) - **Cost Cap**: set maximum CPA (efficiency) - **Bid Cap**: maximum bid per impression - Budget ≥50x CPA per ad group for learning phase exit ### Microsoft Bidding - Mirror Google strategy but bid 20-35% lower - Enhanced CPC for manual campaigns - Target CPA / Target ROAS for automated ## Scaling Assessment ### Ready to Scale (Green Light) - CPA consistently below target for 2+ weeks - ≥50 conversions per week (learning phase exited) - CTR stable or improving - ROAS above target - No creative fatigue signals ### 20% Rule Never increase budget by more than 20% at a time: - Week 1: $100/day → $120/day - Week 2: $120/day → $144/day - Week 3: $144/day → $173/day - Monitor 3-5 days after each increase for performance stability ### Scaling Methods 1. **Vertical**: increase budget on winning campaigns (20% rule) 2. **Horizontal**: duplicate winning campaigns to new audiences 3. **Platform expansion**: add budget on new platforms 4. **Geographic expansion**: test new markets/regions 5. **Format expansion**: test new ad formats on same platform ## Kill List Assessment ### 3x Kill Rule - Any campaign/ad group with CPA >3x target → **flag for pause** - Review spend in last 14 days with no conversions → **flag for pause** - Creative with CTR >50% below platform benchmark → **flag for creative kill** ### Kill Decision Framework | Scenario | Data Required | Action | |----------|---------------|--------| | CPA >3x target | ≥7 days data, ≥20 clicks | Pause immediately | | No conversions | ≥$100 spend or ≥50 clicks | Pause and diagnose | | CTR <50% of benchmark | ≥1,000 impressions | Kill creative, test new | | ROAS <50% of target | ≥14 days data | Reduce budget 50% or pause | ## MER (Marketing Efficiency Ratio) ``` MER = Total Revenue / Total Marketing Spend ``` - Assess blended efficiency across all platforms - Target MER varies by business: 3x-10x depending on margins - Use MER to evaluate overall health, not just per-platform ROAS - Incrementality testing recommended for MER accuracy ## Output ### Budget & Bidding Assessment ``` Budget Allocation Health Allocation Strategy: ████████░░ XX/100 Bidding Strategies: ██████████ XX/100 Scaling Readiness: ███████░░░ XX/100 Budget Sufficiency: █████░░░░░ XX/100 ``` ### Deliverables - `BUDGET-STRATEGY-REPORT.md`: Full allocation and bidding analysis - Current vs recommended budget split (pie chart data) - Bidding strategy recommendations per platform/campaign - Scale list: campaigns ready for more budget - Kill list: campaigns/ad groups to pause immediately - MER analysis and trend - Quick Wins for immediate budget optimization
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