v1.0.0 to v1.1.2

---

name: search-campaign-audit

author: Cogny AI

requires: cogny-mcp

user-invocable: true

argument-hint: "[campaign name or id]"

allowed-tools:

- mcp__cogny__create_finding

- WebFetch

- WebSearch

---

# Search Campaign Audit

A deep audit of your Google Ads Search campaigns — the campaign type where you still

control keywords, match types, and ads directly. Finds quality-score drags, wasted

match-type spend, negative gaps, and weak ads.

## Usage

`/search-campaign-audit` — audit every Search campaign in the account

`/search-campaign-audit Brand - Exact` — audit one campaign by name or id

## Benchmarks

| Signal | Poor | OK | Good |

|--------|------|-----|------|

| Quality Score | ≤4 | 5–6 | 7–10 |

| Ad Strength | Poor / Average | Good | Excellent |

| Search term relevance | <50% spend on intent terms | 50–75% | >75% |

| Impression share lost (rank) | >40% | 20–40% | <20% |

## Steps

### 1. Find the Search campaigns

```sql

SELECT campaign.id, campaign.name, campaign.status,

campaign.bidding_strategy_type, campaign_budget.amount_micros,

metrics.cost_micros, metrics.conversions, metrics.conversions_value,

metrics.search_impression_share, metrics.search_rank_lost_impression_share,

metrics.search_budget_lost_impression_share

FROM campaign

WHERE campaign.advertising_channel_type = 'SEARCH'

AND segments.date DURING LAST_30_DAYS

ORDER BY metrics.cost_micros DESC

```

Flag campaigns losing >40% impression share to rank (quality/bids) or to budget.

### 2. Keyword performance & quality score

```sql

SELECT ad_group_criterion.keyword.text, ad_group_criterion.keyword.match_type,

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,

campaign.name, ad_group.name,

metrics.cost_micros, metrics.conversions, metrics.clicks, metrics.impressions

FROM keyword_view

WHERE segments.date DURING LAST_30_DAYS AND metrics.cost_micros > 0

ORDER BY metrics.cost_micros DESC

LIMIT 100

```

Flag:

(`creative_quality_score` = ad relevance, `post_click_quality_score` = landing page,

`search_predicted_ctr` = expected CTR)

- High-spend keywords with **zero conversions**

- Duplicate keywords across ad groups (internal auction competition)

### 3. Match-type mix

Aggregate spend and conversions by `match_type` (EXACT / PHRASE / BROAD).

Flag:

- Broad match taking a large share of spend with a worse CPA than exact/phrase —

broad only works well with Smart Bidding *and* tight negatives

- Accounts that are 100% exact (likely missing volume) or 100% broad (likely bleeding)

### 4. Search term analysis

```sql

SELECT search_term_view.search_term, search_term_view.status, campaign.name,

ad_group.name, metrics.cost_micros, metrics.conversions, metrics.clicks

FROM search_term_view

WHERE segments.date DURING LAST_30_DAYS AND metrics.cost_micros > 0

ORDER BY metrics.cost_micros DESC

LIMIT 100

```

Flag:

- Irrelevant / off-intent terms with spend — negative keyword candidates

- Converting terms with status `NONE` (not yet added as keywords) — harvest them

- The total cost of zero-conversion terms — this is the headline waste number

### 5. Negative keyword coverage

```sql

SELECT shared_set.name, shared_set.type, shared_set.member_count

FROM shared_set

WHERE shared_set.type = 'NEGATIVE_KEYWORDS'

```

list of perennial junk (`free`, `jobs`, `diy`, `cheap` — adjust to the business).

### 6. Ad strength & RSA coverage

```sql

SELECT ad_group.name, ad_group_ad.ad.id, ad_group_ad.ad.type,

ad_group_ad.ad_strength, ad_group_ad.status, campaign.name,

metrics.impressions, metrics.conversions

FROM ad_group_ad

WHERE campaign.advertising_channel_type = 'SEARCH'

AND ad_group_ad.status = 'ENABLED'

AND segments.date DURING LAST_30_DAYS

```

Flag:

- Ad groups with **only one RSA** (no test running)

- `ad_group_ad.ad_strength` of `POOR` or `AVERAGE`

- Any remaining Expanded Text Ads (deprecated)

- Ad groups with zero enabled ads

### 7. Asset (extension) coverage

```sql

FROM campaign_asset

```

and CTR that most accounts leave on the table.

### 8. Score and report

```

Search Campaign Audit — [Account Name]

Search Score: X/100 · 30-day spend: [X] · Conv: [X] · CPA: [X]

| Campaign | Spend | Conv | CPA | Avg QS | IS lost (rank) |

|----------|-------|------|-----|--------|----------------|

🔴 Critical — QS ≤4 on top spenders, zero-conversion keyword spend

🟡 Important — broad-match bleed, single-RSA ad groups, missing negatives

🟢 Optimization — extensions, search-term harvesting

Top 3 Actions:

1. [Highest $ impact]

2. ...

3. ...

```

### 9. Record findings

```json

{

"title": "Quality Score 3 on 'crm software' — $620/mo at a 2.4x CPA penalty",

"body": "'crm software' (phrase) has QS 3: ad relevance below average, landing page below average. It spent $620 last month at $94 CPA vs $39 account average. Tighten the ad group to one theme, mirror the keyword in RSA headlines, and point it at a dedicated landing page.",

"action_type": "keyword_optimization",

"expected_outcome": "QS to 6+, CPC down 20-35%, CPA toward account average",

"estimated_impact_usd": 380,

"priority": "high"

}

```

Action types: `keyword_optimization`, `negative_keyword`, `match_type`,

`creative_refresh`, `campaign_optimization`, `bidding_strategy`.

## Critical rules

1. **Read the QS components, don't just report the number.** The fix differs for ad

relevance vs landing page vs CTR.

2. **Zero-conversion search-term spend is the headline waste figure** — total it.

3. **Quote real numbers**: QS values, match-type splits, term costs.