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.