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52 Account Structure Global

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minhnv0807
52-account-structure-global

Use when an ad account HIERARCHY needs designing or cleaning up — campaign, ad set, and ad structure by objective, a naming convention that keeps data readable, CBO versus ABO by stage, how many ad sets and creatives to run, and the minimum daily budget an ad set needs to exit learning. Trigger on 'account structure', 'campaign structure', 'naming convention', 'how many ad sets should I run', 'CBO or ABO', 'our account is a mess of duplicated campaigns'. Not for — scoring an existing account against 84 checkpoints, see `21-ads-audit-global`; pixel and conversion setup, see `53-tracking-setup-global`; budget across channels, see `54-media-plan-global`; scaling a winner, see `55-scaling-ads-global`.

Overview

Publisherminhnv0807
Repositoryai-business-skills
Skill name52-account-structure-global
Stars
612
Forks
228
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by minhnv0807 on GitHub. Read the source before you install it.

Installation

Install the 52 Account Structure Global AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/minhnv0807/ai-business-skills/tree/master/skills/en/52-account-structure-global
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/minhnv0807/ai-business-skills.git /tmp/ai-business-skills
mkdir -p .claude/skills
cp -r /tmp/ai-business-skills/skills/en/52-account-structure-global .claude/skills/52-account-structure-global
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 52 Account Structure Global in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 52 Account Structure Global on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 52 Account Structure Global is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

LevelFormatExample
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:

QuestionIf 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 whenTesting — you need guaranteed spend on each audienceScaling — a winner exists, let the algorithm allocate
AdvantageEvery ad set gets enough data to concludeAutomatically pushes spend to the best performer
RiskYou must manually pause losersBudget concentrates on one ad set; other tests starve
RuleDefault to ABO in testingMove 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% BudgetPurpose
Cold — testing30%Find new winners
Cold — scaling50%Main volume
Retargeting15%Convert warm and hot
Lookalike5%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 CPADerived 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 event such as Add to Cart or Lead instead of Purchase, (c) reduce the number of markets. Never split budget thinner and hope. In Tier 2 markets the same math produces a much lower floor because CPA is lower — recalculate per market, do not copy a Tier 1 floor into a Tier 2 account or vice versa.

Google Search and LinkedIn behave differently: Search needs enough clicks at the market CPC ($1-2 broad, $5-50+ on commercial intent) to gather signal, and LinkedIn's $30-100+ CPM means a viable B2B ad set floor is materially higher than a Meta one.

Output structure

File name: account-structure-[product]-[YYYYMMDD].md

markdown
# Account Structure — [Product] — [Platform]
Stage: [Testing/Scaling/Maintaining] · Monthly budget: [amount] · Markets: [list]

## 1. Campaign tree
[Full hierarchy using the naming convention]

## 2. Ad set table
| Campaign | Ad set (named) | Audience | Daily budget | ABO/CBO | Ads inside |

## 3. Naming convention applied
| Level | Format | Real example from this project |

## 4. Budget allocation
| Campaign type | % | Daily amount | Monthly amount |

## 5. Learning-phase math
| Ad set | Target CPA | Derived floor | Planned budget | Passes? |

## 6. Pre-launch checklist
- [ ] Pixel/CAPI fires correctly on landing and confirmation pages (see 53-tracking-setup-global)
- [ ] Correct conversion event selected (Lead / Purchase), no duplicates
- [ ] Consent mode and CMP live in EU/UK and California traffic
- [ ] UTMs on every link; utm_content matches the ad name exactly
- [ ] Test events all green — NOT GREEN MEANS DO NOT LAUNCH
- [ ] Naming format applied across campaigns, ad sets, and ads
- [ ] Every ad set budget clears the derived learning floor
- [ ] Exclusions applied: cold excludes purchasers and warm audiences

Common mistakes

MistakeConsequenceFix
Too many ad sets for the budgetNothing exits learning, no conclusive dataConsolidate to 3-5, or 1 broad plus tests
Editing an ad set mid-learningLearning resets, CPA swingsWait until learning completes, then edit
Ad-hoc namingData cannot be filtered or comparedApply the format and rename before launch
Retargeting mixed into coldWrong message, artificially cheap CPASplit campaigns and cross-exclude
CBO during testingBudget collapses onto one audienceABO to test, CBO to scale
One structure across many marketsTier 1 costs get blended with Tier 2Split by market or at minimum tag the market
Manual ad sets fighting Advantage+/PMaxOverlapping auctions, unreadable attributionPick one approach per objective and hold it

Related skills

  • 51-audience-research-global: source of the targeting behind each ad set.
  • 54-media-plan-global: total budget and channel split before campaigns are cut.
  • 53-tracking-setup-global: must verify green before launch.
  • 05-ad-copy-global: copy and creative for each ad.
  • 19-ab-test-setup-global: how to test one variable inside this structure.
  • 55-scaling-ads-global: rules for splitting out and funding winners.

Quality checklist

  • Hierarchy is clear: one campaign, one objective; cold separated from retargeting
  • Naming convention covers all three levels, includes market, and has real project examples
  • ABO/CBO choice matches the stage (test = ABO, scale = CBO)
  • Ad set count justified by budget, with a consolidation check documented
  • Every ad set clears the derived learning floor, calculated per market
  • Budget allocation follows 30/50/15/5 or states why it deviates
  • Pre-launch checklist includes tracking verified green and consent live

Frequently asked questions

What does the 52 Account Structure Global AI skill do?

Use when an ad account HIERARCHY needs designing or cleaning up — campaign, ad set, and ad structure by objective, a naming convention that keeps data readable, CBO versus ABO by stage, how many ad sets and creatives to run, and the minimum daily budget an ad set needs to exit learning. Trigger on 'account structure', 'campaign structure', 'naming convention', 'how many ad sets should I run', 'CBO or ABO', 'our account is a mess of duplicated campaigns'. Not for — scoring an existing account against 84 checkpoints, see `21-ads-audit-global`; pixel and conversion setup, see `53-tracking-setu...

Why use 52 Account Structure Global on TypingMind?

Because you install it once and use it with any model. 52 Account Structure Global is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 52 Account Structure Global in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/minhnv0807/ai-business-skills/tree/master/skills/en/52-account-structure-global. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 52 Account Structure Global?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 52 Account Structure Global?

As many as you like. As long as a model supports skills, you can use 52 Account Structure Global with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 52 Account Structure Global AI skill free?

Yes. It is published on GitHub by minhnv0807 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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