skill-003-naming-convention-consistency

Skill 003: Campaign Naming Convention Consistency

Purpose

Audit naming conventions across all campaigns, ad groups, and labels for a standardized taxonomy. Inconsistent naming makes reporting unreliable, cross-account management chaotic, and automation rules fragile.

Data Requirements

Data Source: Standard

Standard Data:

• data/account/campaigns/*/campaign.md - All campaign names
• data/account/campaigns/*/*/ad_group.md - All ad group names

Reference GAQL:

SELECT
  campaign.id,
  campaign.name,
  campaign.advertising_channel_type
FROM campaign
WHERE campaign.status != 'REMOVED'

Use /google-ads:get-custom if you need to include labels or additional metadata.

Analysis Steps

1. Extract all entity names: List all campaign and ad group names from the data files
2. Detect naming patterns: Identify delimiters (-, _, |, /) and common segments (Region, Product, Network, Match Type)
3. Analyze consistency: Group by detected pattern, calculate percentage using each, flag outliers
4. Check for problems: Very long names (>100 chars), special characters, duplicates, non-descriptive names ("Campaign 1", "Test")
5. Recommend taxonomy: Suggest format based on majority pattern or best practice

Thresholds

Condition	Severity
Consistency score < 50%	Critical
Duplicate campaign/ad group names	Critical
Consistency score < 80%	Warning
Non-descriptive names ("Test", "Campaign 1")	Warning
Name > 100 characters	Info

Output

Use Short format by default. Use Detailed if user requests comprehensive analysis.

Short:

## Naming Convention Audit
**Account:** [Name] | **Analyzed:** [X] campaigns, [Y] ad groups | **Consistency:** [Z]%

### Critical ([Count])
- **Duplicate names:** "[Name]" appears [X] times → Rename to differentiate

### Warnings ([Count])
- **[Entity]**: Non-descriptive name → Rename to [Suggested]

### Recommendations
1. Adopt format: [Region]_[Brand/NB]_[Product]_[Network]
2. Rename [X] non-conforming entities

Detailed adds:

• What Was Checked (patterns detected, delimiter analysis)
• Pattern breakdown table with counts and percentages
• Before/After rename suggestions for each entity