google-ads-api-account-diagnostics — Google Ads skill

---
name: google-ads-api-account-diagnostics
description: >-
  Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share metrics, investigating low lead flow, or searching for bidding and budget constraints. Don't use for setting up new campaigns, uploading conversion events directly, or general Google Mobile Ads SDK integration issues (use gma-android-integrate instead).
compatibility: "Google Ads MCP Server (tools: search, list_accessible_customers, get_resource_metadata); see the google-ads-api-mcp-setup skill."
metadata:
  category: GoogleAds
  author: google-ads-api-team
  version: "1.0.2"
---

# Google Ads API Account Performance Diagnostics Skill

This skill provides instructions on how to use the Google Ads MCP server tools to diagnose common account performance issues.

## Workflows

### Pre-Flight Tool Verification
Before starting any diagnostic task, verify whether the Google Ads MCP Server tools (`search`, `list_accessible_customers`, `get_resource_metadata` — these may be exposed with a server prefix, e.g. `customers_list_accessible_customers`) are available in the runtime environment:
- **If MCP tools are available**: Proceed with live diagnostics — first [identify active client accounts](#identifying-active-client-accounts), then run GAQL via the `search` tool (arguments `customer_id` and `query`).
- **If MCP tools are missing**: Follow [Fallback When MCP Tools Are Unavailable](#fallback-when-mcp-tools-are-unavailable).

### Identifying Active Client Accounts
Most diagnostics tasks require sending GAQL queries to a specific customer account. If the customer ID is not explicitly provided by the user, you must first call the `list_accessible_customers` (or `customers_list_accessible_customers`) tool to retrieve the customer resource names/IDs you have access to.

Once you have the list of accessible customer IDs, query the `customer_client` resource using the `search` tool under those customer accounts to find active client customer accounts. Make sure to select only enabled client accounts and filter out manager accounts:
```sql
SELECT
  customer_client.id,
  customer_client.descriptive_name,
  customer_client.status,
  customer_client.manager
FROM customer_client
WHERE customer_client.status = 'ENABLED' AND customer_client.manager = FALSE
```
Only run subsequent diagnostic queries against the enabled client customer IDs retrieved from this list. Do not query deactivated or manager accounts, as doing so will cause API errors.

### Fallback When MCP Tools Are Unavailable
When Google Ads MCP tools (`search`, `list_accessible_customers`, `get_resource_metadata` — these may be exposed with a server prefix, e.g. `customers_list_accessible_customers`) are not registered in the runtime environment:
1. **Inform the User**: State that live account performance diagnostics require the Google Ads MCP Server.
2. **Reference Setup Guide**: Direct the user to the setup instructions in the [google-ads-api-mcp-setup](../google-ads-api-mcp-setup/SKILL.md) skill to install and configure the Google Ads MCP Server for their assistant environment.
3. **Provide GAQL Templates, Gotchas, and Remediation Guidance**: Formulate and output the complete diagnostic plan for manual execution in the Google Ads Query Builder or via API integration:
   - Provide all multi-step GAQL queries for the workflow, including current-vs-prior date window comparisons (e.g. traffic, impression share, conversion breakdowns, or change events).
   - Explain all metric conversion and constraint gotchas (`metrics.cost_micros / 1,000,000` for currency, impression share reported as decimals or `"< 0.10"`, `change_event` 30-day window and `LIMIT 10000` without `metrics.*`, and `successful_event_count / total_event_count` plus `status` for upload health).
   - Outline concrete **actionable next steps** for each diagnostic branch (e.g., raising campaign budgets when `search_budget_lost_impression_share` is high vs. improving ad quality or bids when `search_rank_lost_impression_share` is high).
4. **Do Not Attempt Unauthorized Local Probing**: Do **not** attempt to run shell commands, custom Python scripts, local SQL/database queries, or direct RPC CLI utilities to access account data. These commands lack credentials and API access and will fail.

### 1. Conversion and Conversion Value Loss

When conversions or conversion value suddenly decline, use the following steps to diagnose the issue.

**Steps:**
1.  **Discover Fields**: Use `get_resource_metadata` with resource `campaign` or `ad_group` to ensure you have the correct field names.
2.  **Query Performance**: Use `search` to retrieve performance data.
    *   **Resource**: `campaign` or `ad_group`
    *   **Fields**: Include `campaign.name`, `metrics.conversions`, `metrics.conversions_value`, `metrics.cost_micros`.
    *   **Segments**: To isolate the loss, include segments like `segments.date`, `segments.device`, `segments.conversion_action`.
    *   **Conditions**: Compare the period of decline with a previous period (e.g., `segments.date >= '{start_date}'`).
    *   *Gotcha*: `metrics.cost_micros` must be divided by 1,000,000 to get standard currency amounts.
    *   *Gotcha (conversion action segmentation)*: In GAQL, `metrics.cost_micros` cannot be selected when segmenting by `segments.conversion_action`. Query conversion action breakdowns separately without `metrics.cost_micros`.

    **Example GAQL Queries:**
    1. To query performance and cost by date and device:
    ```sql
    SELECT
      campaign.name,
      metrics.conversions,
      metrics.conversions_value,
      metrics.cost_micros,
      segments.date,
      segments.device
    FROM campaign
    WHERE segments.date >= '{start_date}' AND segments.date <= '{end_date}'
    ```

    2. To query conversion breakdown by conversion action (without `metrics.cost_micros`):
    ```sql
    SELECT
      campaign.name,
      metrics.conversions,
      metrics.conversions_value,
      segments.date,
      segments.conversion_action
    FROM campaign
    WHERE segments.date >= '{start_date}' AND segments.date <= '{end_date}'
    ```

3.  **Analyze**: Check if the loss is limited to certain devices (e.g., mobile vs desktop) or specific conversion actions.
4.  **Check Uploads**: If using offline imports, query `offline_conversion_upload_conversion_action_summary` to verify upload pipeline health. If the query returns no results, report that no offline uploads exist for the account and proceed.

    **Example GAQL Query:**
    To check upload pipeline health for a customer account `{customer_id}`:
    ```sql
    SELECT
      offline_conversion_upload_conversion_action_summary.conversion_action_name,
      offline_conversion_upload_conversion_action_summary.successful_event_count,
      offline_conversion_upload_conversion_action_summary.total_event_count,
      offline_conversion_upload_conversion_action_summary.status
    FROM offline_conversion_upload_conversion_action_summary
    ```

### 2. Opportunities Lost (Impression Share)

To identify lost opportunities due to ad rank, bids, or budgets, analyze impression share metrics.

**Steps:**
1.  **Query Impression Share**: Use `search` to retrieve impression share metrics.
    *   **Resource**: `campaign`
    *   **Fields**: Include `campaign.name`, `metrics.search_impression_share`, `metrics.search_rank_lost_impression_share`, `metrics.search_budget_lost_impression_share`.
    *   *Gotcha*: Impression share values in the API are returned as decimals (e.g., 0.35 = 35%) or formatted strings (e.g., `"< 0.10"`).

    **Example GAQL Query:**
    To query impression share metrics for a customer account `{customer_id}` between `{start_date}` and `{end_date}`:
    ```sql
    SELECT
      campaign.name,
      metrics.search_impression_share,
      metrics.search_rank_lost_impression_share,
      metrics.search_budget_lost_impression_share
    FROM campaign
    WHERE segments.date >= '{start_date}' AND segments.date <= '{end_date}'
    ```

2.  **Analyze**:
    *   High `search_budget_lost_impression_share` indicates opportunities lost due to limited budget.
    *   High `search_rank_lost_impression_share` indicates opportunities lost due to low ad rank (bid or quality issues).

### 3. Low Lead Flow Diagnostics

When a user asks "why is my lead flow low these past few days?", follow this systematic approach.

**Steps:**
1.  **Confirm Drop**: Query conversions segmented by date for the last few days vs the previous period.
2.  **Isolate Cause**:
    *   Check if **Traffic** (clicks, impressions) dropped.
    *   Check if **Conversion Rate** (conversions/clicks) dropped.

    **Example GAQL Query (Traffic and Conversion Trends):**
    To query traffic and conversion rate metrics across campaigns segmented by date:
    ```sql
    SELECT
      campaign.id,
      campaign.name,
      segments.date,
      metrics.impressions,
      metrics.clicks,
      metrics.ctr,
      metrics.conversions,
      metrics.conversions_from_interactions_rate
    FROM campaign
    WHERE segments.date >= '{start_date}' AND segments.date <= '{end_date}'
    ORDER BY segments.date DESC
    ```

3.  **If Traffic Dropped**: Check Impression Share metrics (see Workflow 2) to see if it's a budget or rank issue, or if search volume generally declined.
4.  **If Conversion Rate Dropped**: Check breakdowns by `segments.device` or `segments.conversion_action` to see if a specific area is failing.
5.  **Check Changes**: Query the `change_event` resource to see if any changes were made to bids, budgets, or targeting around the time the drop started.
    *   *Gotcha (change_event constraints)*: Queries to the `change_event` resource:
        *   Must specify a `LIMIT` clause of less than or equal to 10000.
        *   Must filter by date (`change_event.change_date_time`) within the past 30 days.
        *   Cannot select performance metrics (e.g., `metrics.*` is not supported; only `change_event` attributes and allowed resource fields can be selected).

    **Example GAQL Query:**
    To query change events for a customer account `{customer_id}` between `{start_date}` and `{end_date}`:
    ```sql
    SELECT
      change_event.change_date_time,
      change_event.change_resource_name,
      change_event.resource_change_operation,
      change_event.changed_fields
    FROM change_event
    WHERE change_event.change_date_time >= '{start_date}' AND change_event.change_date_time <= '{end_date}'
    LIMIT 10000
    ```

### 4. Offline Upload Pipeline Diagnostics

When offline conversion uploads for a specific action (e.g., store-purchase) stop showing up or fail, use the following steps to diagnose the issue.

**Steps:**
1.  **Retrieve Client Accounts**: If `{customer_id}` is not provided, follow [Identifying Active Client Accounts](#identifying-active-client-accounts) to retrieve active client customer accounts.

2.  **Verify Pipeline Health**: Query `offline_conversion_upload_conversion_action_summary` for the active client account.
    *   **Fields**: Include `offline_conversion_upload_conversion_action_summary.conversion_action_name`, `offline_conversion_upload_conversion_action_summary.successful_event_count`, `offline_conversion_upload_conversion_action_summary.total_event_count`, and `offline_conversion_upload_conversion_action_summary.status`.

    **Example GAQL Query:**
    ```sql
    SELECT
      offline_conversion_upload_conversion_action_summary.conversion_action_name,
      offline_conversion_upload_conversion_action_summary.successful_event_count,
      offline_conversion_upload_conversion_action_summary.total_event_count,
      offline_conversion_upload_conversion_action_summary.status
    FROM offline_conversion_upload_conversion_action_summary
    ```

3.  **Analyze**:
    *   *Gotcha*: If the query to `offline_conversion_upload_conversion_action_summary` returns no results or is empty (indicating there are no offline conversion uploads configured or active for the customer account), immediately stop/break the diagnostic workflow. Report directly to the user that no offline conversion upload data or summaries exist in the accessible account(s), rather than retrying or attempting to generate custom scripts.
    *   If results are returned, verify the upload success rate by comparing `successful_event_count` with `total_event_count`. Check the `status` field to diagnose failures.