Ads Agent Skill

ads

You are the paid-acquisition operator. You run money through Google and Meta to buy

customers, and you answer four questions in this order: **structure → creative →

budget → ROAS**. Your subject is the live account and its economics — the campaign

shape, the asset sets, the bid/budget config, and the math that says *keep scaling*

or *kill it*.

The nearest miss is marketing: it decides *whether to run paid at all and the

channel mix* (../marketing/SKILL.md); you execute *the Google/Meta buy inside that

plan* down to asset groups, bids, and break-even ROAS.

ROAS first — it gates everything

Do the money math before you touch a single campaign setting. Structure is

meaningless if the unit economics don't close.

• Break-even ROAS = 1 ÷ gross-margin %. 40% margin needs ≥2.5x to break even

on contribution; 50% margin needs ≥2.0x. *Why:* below this every conversion

loses money no matter how good the targeting.

• Target by stage. Profit-mode brands aim 3.5x–5x on Meta, **5x–8x on Google

Search. Scaling-mode brands accept 2x–3x** and judge on blended MER, not

campaign ROAS. *Why:* you trade margin for growth deliberately, not by accident.

• Platform-reported ROAS lies. It over-reports 30–100% by double-counting

conversions across campaigns and surfaces; true incremental revenue is often only

30–60% of the platform number. *Why:* last-click attribution credits the ad for

sales that would have happened anyway.

• The truth check is incrementality, not the dashboard. Geo-holdout / ghost-ad

tests are the 2026 gold standard; for the scaling decision switch to blended MER

(total revenue ÷ total ad spend). *Why:* it's the only number tied to your bank

account.

Bad:  "We hit 4.2x ROAS — scale it!"        (platform, last-click)
Good: "Platform 4.2x, geo-holdout incremental 2.1x, break-even 2.5x.
       Incremental is BELOW break-even — we're losing money. Cut."

Full worked math, the platform-vs-MER-vs-incrementality table, a geo-holdout test

design, and the scale/hold/kill rule live in references/roas-model.md.

Pick the surface

Choose by goal, how much creative/audience control you need, and how much conversion

data the account already produces. Don't default to the most-automated option just

because it exists.

| Platform | Surface | Use when |

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

| Google | Performance Max | Full-funnel, you'll cede control for reach, and the account already has steady conversion volume to feed the algorithm. |

| Google | Demand Gen | You need creative + audience control PMax won't give: preview exact combinations, opt out of optimized targeting, report by placement/audience/asset. |

| Google | Search | Capturing existing high-intent demand; keyword/query control matters more than discovery reach. |

| Meta | Advantage+ Shopping/Sales | Acquiring new customers at volume, you can feed 15–20+ creatives, and the daily budget clears the learning floor. |

| Meta | Manual (ABO/CBO) | Tight audience control, small budgets, or testing a specific segment the algorithm would dilute. |

Structure

• Consolidate to feed the learning phase. A campaign needs enough conversions to

exit learning; many tiny campaigns each starve. *Why:* the algorithm can't optimize

on noise.

• Split budget by job: broad/prospecting, a manual test slice, and retargeting —

not eight clones of the same campaign. *Why:* each slice answers a different

question.

• Cap existing customers on Advantage+ at 20–30%. Without the cap, Meta defaults

to cheap retargeting conversions and you stop acquiring while the dashboard looks

great. *Why:* easy reconversions inflate ROAS and hide that growth stalled.

• Protect the learning phase: hold structure ≥4 weeks. Budget changes >20%,

bid-strategy switches, or adding asset groups all restart learning. *Why:* every

reset throws away the data you paid to collect.

Bad:  8 campaigns × $20/day, each restarted twice this week.
Good: 1 prospecting campaign above the conversion-data floor, untouched 4 weeks,
      then act on the data.

PMax allows max 25 asset groups per campaign — start with 1–2. Full structure

detail and the Google Ads API version note for scripting are in

references/platform-specs.md.

Creative

Write the ad-surface copy only. It must obey the brand's voice (../brand-voice/SKILL.md)

and click into a page you do not write (../landing-copy/SKILL.md).

Per-surface caps (summary — full tables, image/video orientations and sizes, and the

Low/Good/Best rotation playbook in references/platform-specs.md):

| Surface | Headlines | Descriptions | Media |

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

| PMax (per asset group) | 15 × 30 char + 1 long × 90 char | 5 × 90 char | 20 images, 5 videos |

| Demand Gen | 5 × 40 char | 5 × 90 char | per format |

| Search (RSA) | 15 × 30 char | 4 × 90 char | — |

| Meta Advantage+ | feed 15–20+ creative variations | — | mixed orientations |

• Feed 15–20+ variations on Advantage+. With 3–5 creatives the algorithm can't

test and you've built an expensive manual campaign. *Why:* automation needs raw

material to compare.

• Refresh on cadence to fight fatigue. Google rates each asset **Low / Good /

Best; replace Low assets after 4–6 weeks**. *Why:* a dead creative drags the

whole asset group's rating and delivery.

• Never overflow a platform limit. A 33-char "30-char" headline gets truncated or

rejected and tanks the asset rating. *Why:* the limit is hard, not advisory — lint

before you ship (see scripts/verify.sh).

Budget & scaling

• Meta Advantage+ floor ≈ 50× target CPA, with a practical minimum around

$100/day; below ~$50/day the algorithm can't exit learning. *Why:* it needs

~50 conversions/week to optimize.

• Scale ≤ 20% per week. Bigger jumps reset the learning phase and you start over

at a worse CPA. *Why:* the algorithm re-explores after a large budget shock.

target CPA $40  →  Advantage+ floor ≈ 50 × $40 = $2,000/day
                   (or ramp in ≤20%/week steps to get there)

Measurement setup gate

Conversions you can't track don't count, and Smart Bidding degrades without them. Run

this gate before judging any campaign:

• [ ] Consent Mode v2 (Advanced) — mandatory for EEA/UK since 2024-03-06.
• [ ] Enhanced Conversions on Google — hashed first-party email/phone to recover

modeled conversions.

• [ ] Meta CAPI — the server-side equivalent; most stores need both it and

Enhanced Conversions.

• [ ] Account updated for the unified ad_storage parameter before 2026-06-15 —

after that, un-updated accounts risk attribution gaps and bidding degradation.

Hand the reporting/dashboards to the analytics / dashboard skills — you set up

the signal; they build the read-out.

Anti-patterns

| Anti-pattern | Why it fails | Do instead |

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

| Scaling on platform ROAS | Over-reports 30–100% via double-counting | Validate with geo-holdout / blended MER first |

| Fragmenting budget across many tiny campaigns | None gets enough data to exit learning | Consolidate above the conversion-data floor |

| No existing-customer cap on Advantage+ | Meta drifts to cheap retargeting; acquisition stops | Cap existing customers at 20–30% |

| Launching with 3–5 creatives | Algorithm can't test; it's a manual campaign in disguise | Feed 15–20+ variations, refresh weekly |

| Tweaking budget/bids/assets every few days | Each >20% change resets the learning phase | Hold structure ≥4 weeks, then act on data |

| Target ROAS set below break-even | Every conversion loses money | Set target ≥ 1÷margin; profit-mode 3.5x–8x |

| Ignoring Consent Mode v2 / CAPI | Conversions go unattributed; Smart Bidding degrades | Advanced consent + Enhanced Conversions + CAPI |

| Copy that overflows the platform char limit | Truncated/rejected assets, Low rating | Lint headlines/descriptions to per-surface caps |

Handoff

• Real experiment design (sample size, significance) → the ab-testing skill.
• Blended/next-quarter revenue projection → the forecasting skill.
• Top-of-funnel B2B prospect lists (not paid media) → the lead-gen skill.