The Ad Performance by Location report provides geographic performance breakdown, allowing you to analyze how your ads perform across different store locations.

¶ Report Details

Report Type ID: AD_PERFORMANCE_BY_LOCATION

Use Cases:

• Geographic performance analysis
• Store-level optimization
• Regional budget allocation

Dimensions:

• ad_account_id, campaign_id, ad_group_id: Campaign hierarchy
• location_id: Specific store/location identifier
• currency_code: Currency for monetary values

Supported Time Units:

Time Unit	Async	Sync
HOURLY	❌	✅
DAILY	✅	✅
WEEKLY	✅	❌
MONTHLY	✅	❌
SUMMARY	✅	❌

¶ Available Metrics

Metric	Hourly	Daily	Weekly	Monthly	Summary
impressions	✅	✅	✅	✅	✅
clicks	✅	✅	✅	✅	✅
ad_spend	✅	✅	✅	✅	✅
click_through_rate	✅	✅	✅	✅	✅
cost_per_click	✅	✅	✅	✅	✅
orders_7d_on_click_date	❌	✅	✅	✅	✅
sales_7d_on_click_date	❌	✅	✅	✅	✅
exposed_orders_7d_on_impression_date	❌	✅	✅	✅	✅
exposed_sales_7d_on_impression_date	❌	✅	✅	✅	✅
orders_7d_on_order_date	❌	✅	✅	✅	✅
sales_7d_on_order_date	❌	✅	✅	✅	✅
exposed_orders_7d_on_order_date	❌	✅	✅	✅	✅
exposed_sales_7d_on_order_date	❌	✅	✅	✅	✅
roas_7d_on_click_date	❌	✅	✅	✅	✅
exposed_roas_7d_on_impression_date	❌	✅	✅	✅	✅
roas_7d_on_order_date	❌	✅	✅	✅	✅
exposed_roas_7d_on_order_date	❌	✅	✅	✅	✅
cost_per_order_7d_on_click_date	❌	✅	✅	✅	✅
cost_per_exposed_order_7d_on_impression_date	❌	✅	✅	✅	✅
cost_per_order_7d_on_order_date	❌	✅	✅	✅	✅
cost_per_exposed_order_7d_on_order_date	❌	✅	✅	✅	✅
avg_order_value_7d_on_click_date	❌	✅	✅	✅	✅
exposed_avg_order_value_7d_on_impression_date	❌	✅	✅	✅	✅
avg_order_value_7d_on_order_date	❌	✅	✅	✅	✅
exposed_avg_order_value_7d_on_order_date	❌	✅	✅	✅	✅
click_to_order_rate_7d_on_click_date	❌	✅	✅	✅	✅
exposed_click_to_order_rate_7d_on_impression_date	❌	✅	✅	✅	✅
click_to_order_rate_7d_on_order_date	❌	✅	✅	✅	✅
exposed_click_to_order_rate_7d_on_order_date	❌	✅	✅	✅	✅
new_to_brand_customers	❌	✅	✅	✅	✅
42d_lapsed_to_brand_customers	❌	✅	✅	✅	✅
42d_existing_to_brand_customers	❌	✅	✅	✅	✅
exposed_new_to_brand_customers	❌	✅	✅	✅	✅
exposed_42d_lapsed_to_brand_customers	❌	✅	✅	✅	✅
exposed_42d_existing_to_brand_customers	❌	✅	✅	✅	✅

¶ Time Range Configuration

When configuring time ranges, follow these guidelines for proper aggregation:

Hourly Reports

• Start Date: Any valid date
• End Date: Any valid date after start date
• Example: "start_time": "2025-07-15T05:00:00Z", "end_time": "2025-07-16T00:00:00Z"

Daily and Summary Reports

• Start Date: Any valid date
• End Date: Any valid date after start date
• Example: "start_time": "2025-07-15T00:00:00Z", "end_time": "2025-07-20T00:00:00Z"

Weekly Reports

• Start Date: Must be a Monday
• End Date: Must be the next Monday
• Example: "start_time": "2025-07-21T00:00:00Z", "end_time": "2025-07-28T00:00:00Z"

Monthly Reports

• Start Date: Must be the first day of a month
• End Date: Must be the first day of the next month
• Example: "start_time": "2025-07-01T00:00:00Z", "end_time": "2025-08-01T00:00:00Z"

¶ Filter Operators

Supported operators: EQUAL, NOT_EQUAL, IN

¶ Sync Reporting Limitations

When using sync reporting for this report type:

Time Ranges:

• Hourly: You can pull up to 24 hours of data at a time. Data is available for the last 7 days.
• Daily: You can pull up to 30 days of data at a time. Data is available for the last 2 years.

¶ Example Request (Async)

curl -X POST "https://api.uber.com/v1/ads/{account_id}/reporting/report" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "Accept: application/json" \
  -d '{
    "report_type": "AD_PERFORMANCE_BY_LOCATION",
    "time_range": {
      "start_time": "2025-07-21T00:00:00Z",
      "end_time": "2025-07-28T00:00:00Z"
    },
    "columns": [
      "campaign_id",
      "ad_group_id",
      "location_id",
      "impressions",
      "clicks",
      "ad_spend",
      "sales_7d_on_click_date",
      "orders_7d_on_click_date",
      "roas_7d_on_click_date"
    ],
    "time_unit": "WEEKLY",
    "file_format": "CSV",
    "filters": [
      {
        "column": "location_id",
        "operator": "IN",
        "values": ["65681a33-d4b2-4e23-b9a2-8e9fd44f0b60", "9ec56511-e1d6-4361-86b3-0e35f55fe24f"]
      }
    ]
  }'

¶ Example Response

{
  "report_id": "7c4e9f2a-1d3b-5a8e-b6c0-2f7d4e9a3b15"
}

¶ Example Request (Sync)

curl -X POST "https://api.uber.com/v1/ads/{account_id}/reporting/sync" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "report_type": "AD_PERFORMANCE_BY_LOCATION",
    "time_range": {
      "start_time": "2025-11-03T00:00:00Z",
      "end_time": "2025-11-05T00:00:00Z"
    },
    "columns": [
      "campaign_id",
      "ad_group_id",
      "location_id",
      "impressions",
      "clicks",
      "ad_spend",
      "sales_7d_on_click_date",
      "roas_7d_on_click_date"
    ],
    "time_unit": "DAILY",
    "filters": [
      {
        "column": "location_id",
        "operator": "IN",
        "values": ["b2e7d4a1-6f3c-4890-a5d8-1c9e0b7f3a62"]
      }
    ]
  }'

¶ Example Response (Sync)

{
  "schema": {
    "columns": [
      {
        "name": "day_of",
        "type": "COLUMN_TYPE_TIMESTAMP"
      },
      {
        "name": "campaign_id",
        "type": "COLUMN_TYPE_STRING"
      },
      {
        "name": "ad_group_id",
        "type": "COLUMN_TYPE_STRING"
      },
      {
        "name": "location_id",
        "type": "COLUMN_TYPE_STRING"
      },
      {
        "name": "impressions",
        "type": "COLUMN_TYPE_INT64"
      },
      {
        "name": "clicks",
        "type": "COLUMN_TYPE_INT64"
      },
      {
        "name": "ad_spend",
        "type": "COLUMN_TYPE_DOUBLE"
      },
      {
        "name": "sales_7d_on_click_date",
        "type": "COLUMN_TYPE_DOUBLE"
      },
      {
        "name": "roas_7d_on_click_date",
        "type": "COLUMN_TYPE_DOUBLE"
      }
    ]
  },
  "data": {
    "rows": [
      {
        "values": [
          "2025-11-04T00:00:00Z",
          "4f7e2a91-b3c8-4d5e-a6f1-9c0d8e7b2a34",
          "9d1c5e3f-7a2b-4f8d-b6e0-3c9a8d5f1e72",
          "b2e7d4a1-6f3c-4890-a5d8-1c9e0b7f3a62",
          "4214",
          "253",
          "79.68",
          "1125",
          "14.119861939127706"
        ]
      },
      {
        "values": [
          "2025-11-03T00:00:00Z",
          "4f7e2a91-b3c8-4d5e-a6f1-9c0d8e7b2a34",
          "9d1c5e3f-7a2b-4f8d-b6e0-3c9a8d5f1e72",
          "b2e7d4a1-6f3c-4890-a5d8-1c9e0b7f3a62",
          "3339",
          "229",
          "55.96",
          "1100.63",
          "19.668155825589707"
        ]
      }
    ]
  }
}

¶ Related Reports

• Ad Performance - Overall campaign performance analysis
• Ad Performance by Audience Tenure - Customer segment analysis