git:20260518.9974a1f to git:20260711.c346837

14 added, 191 removed. Audit A to A.

---

name: ads-budget

- description: "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."

- user-invokable: false

- tested_date: 2026-05-17

- tested_with: claude-code v2.x

+ description: "Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs."

---

-

- # 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

- |---------------|---------|-----------|---------|

- | 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

- - **Manual CPC**: recommended starting point for cost control

- - **Cost Cap**: efficiency at scale with predictable CPA

- - **Maximum Delivery**: highest volume, most expensive. Use only for scale with established data

- - **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

- - Manual CPC for low-volume campaigns (Enhanced CPC deprecated on Google March 2025; verify Microsoft availability before recommending)

- - Target CPA / Target ROAS for automated (requires 15+ conversions/30 days)

- ## v1.5 Bidding Innovations

- ### Google AI Max for Search

- - 14% avg conversion lift for non-retail brands at similar CPA/ROAS, up to 27% for exact/phrase-match-heavy campaigns ([Google Ads blog, May 2025](https://blog.google/products/ads-commerce/google-ai-max-for-search-campaigns/))

- - Independent data is more conservative: median +13% revenue / +16% CPA across 250+ campaigns ([ALM Corp](https://almcorp.com/blog/google-ai-max-search-campaigns-performance-cpa-revenue-study/))

- - Requires strong negative keyword lists (AI Max casts a wider net)

- - DSA likely consolidated into AI Max by Q2 2026

- - Best for: accounts with mature conversion tracking and keyword history

- ### TikTok Smart+ Modular Control (2025)

- - Lock targeting, creative, budget, or placement independently (mix of manual and AI)

- - TikTok platform median ROAS 1.41-1.67 in 2025; Smart+ delivers ~53% lift over standard campaigns ([TikTok for Business](https://ads.tiktok.com/business/en-US/blog/smart-plus-ai-performance-solution))

- - October 2025 update added module-by-module control after early-2025 control complaints

- - Best for: advertisers wanting partial AI control without full black-box

- ### Apple Ads Maximize Conversions

- - GA: February 26, 2026. AI-powered auto-bidder for Apple Ads

- - Target CPA based on weekly average (not per-conversion)

- - Daily budget must be >=5x target CPA for stable performance

- - Two-week learning phase required; avoid changes during learning

- - Currently supports installs only (not post-install events)

- ### Meta Advantage+ Bidding

- - Automatic optimization across all placements within Advantage+ Sales campaigns

- - Budget automatically shifts to highest-performing placements in real time

- - Best combined with broad targeting and high creative volume

- ## 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 and Bidding

- ```

- Budget Allocation Health

+ 1. Establish objective, conversion value, gross margin, cash constraints, sales

+ capacity, attribution uncertainty, seasonality, and platform minimum evidence.

+ 2. Normalize spend and outcomes to comparable windows and definitions.

+ 3. Calculate break-even boundaries and show formulas, inputs, uncertainty, and

+ sensitivity cases.

+ 4. Distinguish committed baseline, controlled experiments, and reserve capacity.

+ 5. Compare hold, reallocate, scale, reduce, or experiment options using marginal

+ evidence rather than blended averages alone.

+ 6. Return a decision-complete plan with platform/campaign amount, timing, owner,

+ guardrails, success measure, and rollback trigger.

- Allocation Strategy: ████████░░ XX/100

- Bidding Strategies: ██████████ XX/100

- Scaling Readiness: ███████░░░ XX/100

- Budget Sufficiency: █████░░░░░ XX/100

- ```

+ Rules such as 70/20/10, fixed CPA multiples, fixed budget-to-CPA ratios, and fixed

+ percentage scaling are optional heuristics, never universal authorization.

- ### 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