Google ads audit

Google Ads Audit

A one-time, account-wide Google Ads health audit using live data via Cogny's MCP server. Covers every campaign type, scores the account out of 100, and routes you to the right campaign-type skill for deeper drill-down.

Requires: Cogny Agent subscription ($9/mo) — Sign up

Prerequisites Check

Verify Google Ads MCP tools are available. If mcp__cogny__google_ads__tool_execute_gaql is not available:

This skill requires Cogny's Google Ads MCP server.

1. Sign up at https://cogny.com/agent
2. Connect your Google Ads account
3. Add Cogny to your .mcp.json (see the repo README)
4. Restart Claude Code

Stop here if the tools are missing — do not guess at numbers.

Usage

/google-ads-audit — full account audit /google-ads-audit campaigns — campaign structure + performance only /google-ads-audit budget — budget pacing only /google-ads-audit tracking — conversion tracking sanity only /google-ads-audit negatives — account negatives + exclusions only

Approach

This is the account-level audit — it finds structural problems and wasted spend across the whole account. For campaign-type depth (asset groups, keywords, feeds, audiences) it points you to /pmax-audit, /search-campaign-audit, /shopping-campaign-audit, or /demand-gen-audit.

All money fields come back in micros — divide cost_micros etc. by 1,000,000.

Steps

1. Account discovery

tool_list_accessible_accounts

If multiple accounts are accessible, list them and ask which to audit. Confirm the account name and currency before continuing.

2. Campaign overview by channel type (last 30 days)

SELECT campaign.name, campaign.status, campaign.advertising_channel_type,
  campaign.bidding_strategy_type, campaign_budget.amount_micros,
  metrics.cost_micros, metrics.conversions, metrics.conversions_value,
  metrics.clicks, metrics.impressions
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
ORDER BY metrics.cost_micros DESC

Build a per-channel-type summary (Search / Performance Max / Shopping / Display / Video / Demand Gen): total spend, conversions, CPA, ROAS (conversions_value / cost).

Flag:

• Campaigns spending >5% of account budget with zero conversions
• MAXIMIZE_CONVERSIONS / TARGET_CPA campaigns with <15 conversions/30d (too little data for the bidding strategy to learn)
• Multiple campaigns of the same type competing for the same theme (self-competition)
• Enabled campaigns with zero spend (broken, or budget/targeting starved)

3. Conversion tracking sanity

You must run BOTH queries below before flagging anything in this section. Structure alone (which actions exist, which are primary_for_goal) tells you nothing about what is actually driving the bidding signal. A "Primary" action with zero recent volume is harmless; a "Secondary" action can be a deliberate dedup choice. Always cross-reference the structure against actual conversion volume per action.

3a. Structure — which conversion actions exist:

SELECT conversion_action.name, conversion_action.status, conversion_action.type,
  conversion_action.category, conversion_action.counting_type,
  conversion_action.primary_for_goal, conversion_action.include_in_conversions_metric
FROM conversion_action

3b. Volume — which actions are actually firing (last 30 days):

SELECT segments.conversion_action_name, segments.conversion_action_category,
  metrics.all_conversions, metrics.all_conversions_value,
  metrics.conversions, metrics.conversions_value
FROM customer
WHERE segments.date DURING LAST_30_DAYS

Then join: for every conversion action with non-trivial volume, note whether it is Primary or Secondary, and whether metrics.conversions (the bidding signal) or only metrics.all_conversions (the reporting signal) is counting it.

3c. Reconcile against account totals. Pull account-level metrics.conversions and metrics.conversions_value for the same window — the sum across Primary actions in 3b should match (within rounding). If it does, the metrics.conversions figure is the real booking/purchase/lead action and bidding is grounded in real value. State this explicitly in the report before making any tracking claim.

Flag (each must be backed by a number from 3b, not a guess from 3a):

• No primary action has volume in the last 30 days — bidding really is flying blind. (Note: a Primary action with zero recent volume is harmless, not broken.)
• A high-volume real revenue action (purchase, booking, qualified lead) is Secondary while a low-value proxy (page view, "Lokala åtgärder", "Detail product page view") is the only Primary — that is the "bidding on page views" pattern.
• MANY_PER_CLICK counting on a lead-gen action with meaningful volume (double-counts leads; usually should be ONE_PER_CLICK).
• Two near-duplicate Primary actions both firing on the same event (e.g. on-site booking + GA4 booking both Primary → double-counted bid signal).
• REMOVED / HIDDEN actions still receiving conversions.

Do NOT flag:

• A gap between all_conversions and conversions, by itself. That gap is just the pile of Secondary actions (store visits, GA4 echoes of an on-site action, local actions, contacts, etc.) — it is often correct and intentional. Only flag if a high-value, non-duplicate action is sitting in Secondary.
• View-through / page-view actions marked primary_for_goal = true if they have ~0 conversions in 3b — they cost nothing, so they are not polluting bidding.
• A Secondary GA4 purchase when on-site purchase/booking is Primary — that is the textbook dedup pattern, not a bug.

4. Budget pacing (last 7 days)

SELECT campaign.name, campaign.status, campaign_budget.amount_micros,
  metrics.cost_micros, metrics.impressions
FROM campaign
WHERE segments.date DURING LAST_7_DAYS AND campaign.status = 'ENABLED'

For each campaign compute average daily spend vs daily budget.

Flag:

• Campaigns consistently capped at ~100% of daily budget while converting profitably (budget-limited — leaving volume on the table)
• Campaigns spending <50% of budget (delivery problem: bids, targeting, or quality)

5. Account negatives & exclusions

SELECT shared_set.name, shared_set.type, shared_set.status, shared_set.member_count
FROM shared_set

Flag:

• No negative keyword lists shared across Search campaigns
• No brand-term handling (brand traffic mixed into non-brand campaigns)
• For Performance Max / Display: missing account-level placement and content exclusions (brand-safety + waste risk)

6. Wasted spend scan (last 30 days)

SELECT search_term_view.search_term, campaign.name, campaign.advertising_channel_type,
  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 50

Sum the cost of terms with zero conversions and meaningful spend — this is the headline "wasted spend" number and the source of the largest estimated_impact_usd.

7. Score and report

Google Ads Audit — [Account Name]
Health Score: X/100  ·  30-day spend: [X]  ·  Conversions: [X]  ·  CPA: [X]

Score breakdown:
  Account structure ...... X/20
  Conversion tracking .... X/25   (weighted highest — everything depends on it)
  Budget efficiency ...... X/20
  Wasted spend control ... X/20
  Negatives & exclusions . X/15

By campaign type:
| Type          | Spend | Conv | CPA | ROAS | Drill-down skill        |
|---------------|-------|------|-----|------|-------------------------|
| Performance Max | ... | ...  | ... | ...  | /pmax-audit             |
| Search          | ... | ...  | ... | ...  | /search-campaign-audit  |
| Shopping        | ... | ...  | ... | ...  | /shopping-campaign-audit|
| Demand Gen      | ... | ...  | ... | ...  | /demand-gen-audit       |

🔴 Critical
- ...
🟡 Important
- ...
🟢 Optimization
- ...

Top 3 Actions:
1. [Highest $ impact — estimated savings/lift]
2. ...
3. ...

Run next: [the campaign-type skill for the highest-spend type]

8. Record findings

For every actionable issue, call mcp__cogny__create_finding:

{
  "title": "$1,840/mo wasted on zero-conversion search terms",
  "body": "23 search terms spent $1,840 over 30 days with 0 conversions, led by 'free [product]' ($420) and '[competitor] alternative' ($310). Add as negative keywords and create a shared negative list.",
  "action_type": "negative_keyword",
  "expected_outcome": "Reclaim ~$1,800/mo of spend for converting queries",
  "estimated_impact_usd": 1840,
  "priority": "high"
}

Action types: campaign_optimization, budget_adjustment, bidding_strategy, conversion_tracking, negative_keyword, account_structure.

Critical rules

1. Conversion tracking is checked first and weighted highest. A great account on broken tracking is a broken account — say so loudly.
2. Never claim tracking is broken from structure alone. primary_for_goal = true on an action only matters if that action has volume. Pull conversion volume per action (step 3b) and reconcile against account totals (step 3c) before writing any finding about conversion tracking, CPA basis, or bidding signal quality. If metrics.conversions reconciles to a real revenue/booking action, say so — don't wave at the all_conversions gap as if it implies missing primaries.
3. Quote real numbers, never benchmarks alone. "CPA is $48" beats "CPA looks high."
4. One finding per issue, each with a dollar figure. No vague advice.
5. This skill reads only. It never pauses campaigns or changes budgets.