campaign-structure-auditor

name	campaign-structure-auditor
description	Audits Google Ads account structure including ad group strategy, keyword duplication, match type distribution, and naming conventions. Use when auditing campaigns, reviewing account structure, finding duplicate keywords, or checking naming conventions.

Campaign Structure Auditor

Performs comprehensive Google Ads account structure audits covering ad group strategy (SKAG vs STAG vs themed), duplicate keyword detection, match type distribution, ad group health, and naming convention enforcement. Outputs actionable recommendations with severity ratings.

Capabilities

• Ad Group Strategy Assessment: Evaluate SKAG, STAG, and themed ad group approaches
• Duplicate Keyword Detection: Find keyword overlap across campaigns and ad groups
• Match Type Audit: Analyze broad, phrase, and exact match distribution
• Ad Group Health: Check keyword-to-ad-group ratios, empty ad groups, RSA coverage
• Naming Convention Enforcement: Validate campaign/ad group naming patterns
• Quality Score Analysis: Correlate structure issues with Quality Score impact
• Budget Waste Identification: Find structural causes of wasted spend

Workflows

1. Full Account Structure Audit

Step 1: Pull account inventory

-- GAQL: Get all campaigns with status and type
SELECT
  campaign.id,
  campaign.name,
  campaign.status,
  campaign.advertising_channel_type,
  campaign_budget.amount_micros,
  metrics.cost_micros,
  metrics.impressions,
  metrics.clicks,
  metrics.conversions
FROM campaign
WHERE campaign.status != 'REMOVED'
  AND segments.date DURING LAST_30_DAYS
ORDER BY metrics.cost_micros DESC

Step 2: Pull ad group details

-- GAQL: Ad groups with keyword counts and performance
SELECT
  campaign.name,
  ad_group.id,
  ad_group.name,
  ad_group.status,
  ad_group.type,
  metrics.cost_micros,
  metrics.impressions,
  metrics.clicks,
  metrics.conversions,
  metrics.average_cpc
FROM ad_group
WHERE campaign.status = 'ENABLED'
  AND ad_group.status != 'REMOVED'
  AND segments.date DURING LAST_30_DAYS

Step 3: Pull keyword inventory

-- GAQL: All keywords with match types and Quality Score
SELECT
  campaign.name,
  ad_group.name,
  ad_group_criterion.keyword.text,
  ad_group_criterion.keyword.match_type,
  ad_group_criterion.status,
  ad_group_criterion.quality_info.quality_score,
  ad_group_criterion.quality_info.creative_quality_score,
  ad_group_criterion.quality_info.post_click_quality_score,
  ad_group_criterion.quality_info.search_predicted_ctr,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros,
  metrics.conversions
FROM keyword_view
WHERE campaign.status = 'ENABLED'
  AND ad_group.status = 'ENABLED'
  AND ad_group_criterion.status != 'REMOVED'
  AND segments.date DURING LAST_30_DAYS

Step 4: Check RSA coverage

-- GAQL: Ads per ad group
SELECT
  campaign.name,
  ad_group.name,
  ad_group_ad.ad.type,
  ad_group_ad.ad.responsive_search_ad.headlines,
  ad_group_ad.ad.responsive_search_ad.descriptions,
  ad_group_ad.ad_strength,
  ad_group_ad.status
FROM ad_group_ad
WHERE campaign.status = 'ENABLED'
  AND ad_group.status = 'ENABLED'
  AND ad_group_ad.status != 'REMOVED'

2. Ad Group Strategy Assessment

Strategy	Keywords/Ad Group	Best For	Risk
SKAG (Single Keyword Ad Groups)	1	Maximum control, exact match focus	Over-segmentation, low volume per group
STAG (Single Theme Ad Groups)	3-5	Balanced control, theme consistency	Requires tight theme discipline
Themed (Broad Theme)	5-20	Scale, Smart Bidding compatibility	Diluted relevance, mixed intent
Alpha/Beta	Varies	Mining new keywords + proven performers	Complex management

Assessment criteria:

IF keywords_per_ad_group == 1:
  strategy = "SKAG"
  IF using Smart Bidding: WARN "SKAGs limit Smart Bidding signal volume"
  IF avg_impressions_per_ad_group < 100/month: WARN "Low volume SKAGs"

IF keywords_per_ad_group BETWEEN 2 AND 7:
  strategy = "STAG"
  CHECK all keywords share semantic theme
  IF keyword themes diverge: WARN "Mixed intent in STAG"

IF keywords_per_ad_group > 15:
  strategy = "Over-stuffed"
  SEVERITY: HIGH
  RECOMMEND: Split into themed groups of 5-10

3. Duplicate Keyword Detection

Cross-campaign duplicates (cannibalization):

-- GAQL: Find keywords appearing in multiple campaigns
SELECT
  ad_group_criterion.keyword.text,
  ad_group_criterion.keyword.match_type,
  campaign.name,
  ad_group.name,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros
FROM keyword_view
WHERE campaign.status = 'ENABLED'
  AND ad_group_criterion.status = 'ENABLED'
  AND segments.date DURING LAST_30_DAYS
ORDER BY ad_group_criterion.keyword.text

Duplicate classification:

Type	Severity	Description	Action
Exact duplicate	HIGH	Same keyword, same match type, different campaigns	Remove from lower-performing campaign
Cross-match duplicate	MEDIUM	Same keyword, different match types, different campaigns	Ensure intentional funnel (broad→exact)
Near duplicate	LOW	Singular/plural or minor variants	Consolidate if same intent
Intentional split	INFO	Brand vs non-brand separation	Verify negative keyword coverage

Cannibalization impact calculation:

wasted_spend = SUM(cost of losing auction participant)
cannibalization_rate = duplicate_impressions / total_impressions
IF cannibalization_rate > 15%: SEVERITY = HIGH
IF cannibalization_rate > 5%: SEVERITY = MEDIUM

4. Match Type Distribution Audit

Recommended distribution by strategy:

Strategy	Exact	Phrase	Broad	Notes
Conservative	60-70%	20-30%	0-10%	Max control, lower reach
Balanced	40-50%	30-40%	10-20%	Good for most accounts
Smart Bidding	20-30%	20-30%	40-60%	Let algorithm optimize
Discovery	10-20%	20-30%	50-70%	New account/market

Match type health checks:

IF broad_match_pct > 50% AND NOT using_smart_bidding:
  SEVERITY: HIGH
  MESSAGE: "High broad match without Smart Bidding wastes budget"

IF exact_match_pct > 80%:
  SEVERITY: MEDIUM
  MESSAGE: "Over-reliance on exact match limits discovery"

IF phrase_match_pct < 10%:
  SEVERITY: LOW
  MESSAGE: "Phrase match underutilized for intent capture"

CHECK negative_keyword_count:
  IF broad_match_active AND negative_keywords < 50:
    SEVERITY: HIGH
    MESSAGE: "Insufficient negative keywords for broad match protection"

5. Naming Convention Enforcement

Recommended naming pattern:

Campaign: {Platform}_{Type}_{Objective}_{Geo}_{Audience}_{Date}
  Example: GADS_Search_LeadGen_US_Remarketing_2026Q1

Ad Group: {Theme}_{MatchType}_{Modifier}
  Example: CRM_Software_Exact_Desktop

Standard abbreviations:
  Platforms: GADS, META, LNKD, RDDT, MSFT, TKTK, XADS
  Types: Search, Display, PMax, DemGen, Shopping, Video
  Objectives: LeadGen, Sales, Awareness, Traffic
  Match: Exact, Phrase, Broad, BMM (legacy)
  Geo: US, UK, CA, APAC, EMEA, GLOBAL

Validation rules:

RULE: No spaces in campaign names (use underscores)
RULE: No special characters except underscore and hyphen
RULE: Must contain campaign type identifier
RULE: Date or quarter suffix recommended
RULE: Max 100 characters
RULE: Consistent casing (Title_Case or lowercase)

6. Empty Ad Group Detection

-- GAQL: Find ad groups with no enabled keywords
SELECT
  campaign.name,
  ad_group.name,
  ad_group.status,
  ad_group.id
FROM ad_group
WHERE campaign.status = 'ENABLED'
  AND ad_group.status = 'ENABLED'
  AND metrics.impressions = 0
  AND segments.date DURING LAST_90_DAYS

-- GAQL: Find ad groups with no enabled ads
SELECT
  campaign.name,
  ad_group.name,
  ad_group.id
FROM ad_group
WHERE campaign.status = 'ENABLED'
  AND ad_group.status = 'ENABLED'
  AND ad_group.id NOT IN (
    SELECT ad_group.id FROM ad_group_ad
    WHERE ad_group_ad.status = 'ENABLED'
  )

Reference Data

Quality Score Impact by Structure Issue

Issue	Avg QS Impact	CPC Impact	Recommended Fix
Keyword-ad mismatch	-2 to -3	+30-50%	Align ad copy to keyword theme
Too many keywords per group	-1 to -2	+15-25%	Split into themed groups
Missing ad extensions	-1	+10-15%	Add sitelinks, callouts, snippets
Low RSA asset count	-1	+10-20%	Add 10+ headlines, 4 descriptions
No negative keywords	0 (indirect)	+20-40% wasted	Build negative keyword lists

Ad Group Health Scorecard

Metric	Good	Acceptable	Poor
Keywords per ad group	3-10	11-20	20+ or 0
RSAs per ad group	2-3	1	0
Headlines per RSA	10-15	8-9	<8
Descriptions per RSA	4	3	<3
Ad strength	Excellent/Good	Average	Poor/No ads
Negative keywords	50+ per campaign	20-49	<20

Examples

Example: Full Audit Report Output

# Account Structure Audit Report
**Account:** Acme Corp (ID: 123-456-7890)
**Date:** 2026-03-06
**Period:** Last 30 Days

## Summary
- 🔴 3 Critical Issues
- 🟡 5 Warnings
- 🟢 12 Passed Checks

## Critical Issues

### 1. Keyword Cannibalization (HIGH)
- "crm software" appears in 4 campaigns (Brand, Non-Brand, Competitor, Remarketing)
- Estimated wasted spend: $2,340/month
- **Fix:** Consolidate to single campaign, use audience targeting for segmentation

### 2. Empty Ad Groups (HIGH)
- 14 enabled ad groups have 0 impressions in 90 days
- **Fix:** Pause or remove: [list of ad groups]

### 3. Missing RSAs (HIGH)
- 8 ad groups have 0 enabled responsive search ads
- **Fix:** Create RSAs with 10+ headlines and 4 descriptions

## Warnings

### 1. Match Type Imbalance
- Current: 72% Broad, 18% Phrase, 10% Exact
- Using manual CPC (not Smart Bidding)
- **Recommendation:** Shift to 40% Exact, 35% Phrase, 25% Broad
  OR enable Target CPA bidding

### 2. Naming Inconsistency
- 6 campaigns use spaces, 4 use underscores, 2 use hyphens
- **Fix:** Standardize to underscore format

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