52-account-structure-global

# Account Structure (Global)

Good structure means data you can read, optimizations you can trust, and scaling that does not fall apart. Run this after `53-tracking-setup-global` verifies green, and after `51-audience-research-global` and `54-media-plan-global` exist.

## Information gathering

Read the media plan and audience profile if they exist. If information is missing, ask up to 4 questions:

1. **Which platforms and objective?** Meta / Google / TikTok / LinkedIn — lead gen / conversion / traffic / awareness?
2. **How many products or offers are running?** Each primary offer generally deserves its own campaign.
3. **Total monthly budget and target CPA?** This determines how many ad sets the account can actually feed.
4. **Which stage are you in?** Testing / scaling / maintaining?

## Principles

1. **Consolidate before you split.** Fewer, better-funded ad sets is now the platform-recommended structure on both Meta (Advantage+ / broad) and Google (Performance Max, broad match + smart bidding). Splitting an already-small budget across many ad sets starves every one of them.
2. **Consistent naming from day one.** Renaming later is painful, and historical data becomes unfilterable.
3. **One campaign, one objective.** Never mix lead generation and purchase optimization in the same campaign.
4. **Cold stays separate from retargeting.** Different campaigns, different message, never a shared audience pool.
5. **Do not touch an ad set that is still in learning.** Meta needs roughly 50 optimization events per ad set per week to exit learning. Every significant edit restarts it.
6. **Structure follows budget, not ambition.** If the budget cannot fund the structure, cut ad sets, not budget per ad set.

## Workflow

### 1. Hierarchy overview

```
Account
|-- Campaign 1 — [Objective] — [Product/Offer] (Cold Testing)
|   |-- Ad Set 1.1 — [Broad / Advantage+]      -> Ad A (hook 1) / Ad B (hook 2)
|   |-- Ad Set 1.2 — [Interest theme A]        -> Ad A / Ad B
|   |-- Ad Set 1.3 — [Interest theme B]        -> Ad A / Ad B
|   \-- Ad Set 1.4 — [Lookalike 1-3%]          -> Ad A / Ad B
|-- Campaign 2 — [Objective] — Scale winner (split out once a winner is proven)
\-- Campaign 3 — Retargeting
    \-- Ad Set 3.1 — [Warm 7-30 days] — objection-handling creative
```

### 2. Naming convention

| Level | Format | Example |
|-------|--------|---------|
| Campaign | `[Platform]_[Objective]_[Product]_[AudienceType]_[Market]_[MMYY]` | `META_LEAD_COURSE-A_COLD_US_0726` |
| Ad Set | `[Audience]_[Age]_[Gender]_[Placement]_[Budget]` | `INT-BUSINESS_25-45_ALL_ADVPLUS_150USD` |
| Ad | `[CreativeType]_[HookType]_[Version]` | `VID_PAIN_v1`, `IMG_SOCIAL-PROOF_v2` |

Rules: uppercase, underscore separators, no spaces, no special characters. Include the market code when running more than one country — regional cost differences are large enough (Tier 1 CPM 6-7x Tier 2, per `references/benchmarks-global.md`) that blended reporting hides the truth. The ad name must match `utm_content` exactly (see `53-tracking-setup-global`) so ads manager data and GA4 reconcile in both directions.

### 3. Consolidation check

Before building, run this test on the planned structure:

| Question | If no |
|----------|-------|
| Can every ad set reach ~50 optimization events per week at its budget? | Merge ad sets or optimize for an earlier funnel event |
| Do two ad sets target overlapping pools? | Merge them; overlap bids against yourself |
| Is there a real hypothesis behind each split? | Delete the split |

On Meta, the default modern answer is one broad or Advantage+ ad set with several creatives, plus a small number of deliberate tests. On Google, prefer fewer campaigns with more conversion volume over many thin ad groups.

### 4. CBO vs ABO

| | ABO (budget at ad set) | CBO / Advantage campaign budget |
|---|------------------------|----------------------------------|
| Use when | **Testing** — you need guaranteed spend on each audience | **Scaling** — a winner exists, let the algorithm allocate |
| Advantage | Every ad set gets enough data to conclude | Automatically pushes spend to the best performer |
| Risk | You must manually pause losers | Budget concentrates on one ad set; other tests starve |
| Rule | Default to ABO in testing | Move to CBO only once an ad set is proven stable |

### 5. Structure by stage

**TESTING (weeks 1-2):** one campaign per objective; 3-5 ad sets (broad/Advantage+, interest theme A, interest theme B, lookalike, small retargeting); 2-3 ads per ad set to test creative and hook. ABO with even budgets. Goal: find the winning audience and creative. Pause any ad set above 2x target CPA after 3 days.

**SCALING:** split the winner into its own CBO campaign. Increase +20-30% per step, never double overnight (see `55-scaling-ads-global`). Do not edit the winning ad set while scaling. Keep testing new creative in parallel inside the testing campaign.

**MAINTAINING:** 15 minutes of daily monitoring. Refresh creative every 2-3 weeks. Retargeting runs continuously.

### 6. Budget allocation by campaign type

| Campaign type | % Budget | Purpose |
|---------------|---------|---------|
| Cold — testing | 30% | Find new winners |
| Cold — scaling | 50% | Main volume |
| Retargeting | 15% | Convert warm and hot |
| Lookalike | 5% | Open new pools from proven seeds |

### 7. Minimum daily budget per ad set

Do not use a fixed currency figure. Derive it from the target CPA so it holds in any market:

```
Daily floor per ad set = (50 optimization events x target CPA) / 7 days
Quick sanity check     = daily budget >= 5x target CPA
```

Using global Meta CPA medians of $18-38 from `references/benchmarks-global.md`, the derived floor is roughly:

| Target CPA | Derived daily floor per ad set |
|-----------:|-------------------------------:|
| $18 | ~$130 |
| $25 | ~$180 |
| $38 | ~$270 |

If the budget cannot support that floor, do one of three things, in order: (a) merge ad sets, (b) optimize for an earlier, more frequent eve