Export Steps: Log in to Google Ads account > Go to Reports or Data View > Select Export Format > Set Export Scope (Optional) > Confirm and Download
Below are the detailed operations

Table of Contens
ToggleLog in to Google Ads Account
Visit the Google Ads official website
First, you need to go to the official Google Ads website:
- URL: https://ads.google.com
- Ensure you log in with the Google account associated with the ad account.
Select the correct account (for multi-account users)
If you manage multiple Google Ads accounts, the system will display a list of accounts after logging in. You need to:
- Click the Account Selector in the upper right corner (usually displayed as the account name or email).
- Select the target account from the drop-down menu.
Example, assuming you manage two accounts:
- Account A: Brand Ads (brand@example.com)
- Account B: Performance Ads (performance@example.com)
You need to select the account from which you want to export data, such as Account A.
Check Account Permissions
Admin Permissions: Ensure your account has “Standard” or “Admin” permissions, otherwise you may not be able to export certain data.
Permission Check Method:
- Click Tools & Settings in the upper right corner.
- Select “Access & Security”.
- Check if your role is “Administrator” or “Standard User”.
Go to Reports or Data View
Google Ads provides multiple ways to export data; you can choose to export directly from the dashboard or use the Reports feature.
Method 1: Export Data from the Dashboard
Suitable for quickly exporting campaign, ad group, or keyword data.
Operation Steps:
On the Google Ads homepage (dashboard), find the data you want to export, such as:
- Campaigns
- Ad Groups
- Keywords
- Audiences
Above the data table, you can customize columns, selecting the metrics you want to export, such as:
- Clicks
- Impressions
- CTR
- Conversions
Click the Download icon (↓) in the upper right corner of the table.
Example, suppose you want to export data for “Search Campaigns” for the last 30 days:
- Click “Campaigns” in the left menu.
- Select the Date Range above the table (e.g., “Last 30 days”).
- Click the Download icon.
Method 2: Export via the “Reports” Feature
Suitable for more complex data analysis, such as custom reports, cross-campaign comparisons, etc.
Operation Steps:
- Click “Reports” in the left menu.
- Select “Predefined Reports” or “Custom Tables”:
- Predefined Reports: Such as “Campaign Performance”, “Device Report”, etc.
- Custom Tables: You can freely choose dimensions (such as time, device, geographic location) and metrics (such as cost, conversion rate).
- Adjust report parameters:
- Date Range (e.g., “Custom date” select January 1, 2024 – January 31, 2024).
- Segmentation Dimension (e.g., split data by “Device” or “Geographic Location”).
- Click the Download icon (↓) in the upper right corner.
Example, if you want to analyze the “Ad performance difference between mobile devices and PC”:
- In “Reports”, select “Device Report”.
- Set the date range to “Last month”.
- Click Download and select Excel format.
Select Export Format
Google Ads supports multiple file formats, suitable for different needs:
| Format | Applicable Scenario | Features |
|---|---|---|
| .csv | Data analysis (Python, R, Excel) | Plain text, strong compatibility |
| .xlsx | Excel analysis | Supports charts, formulas |
| Printing or sharing | Suitable for presentation | |
| .tsv | Database import | Similar to CSV, but tab-separated |
| Google Sheets | Cloud collaboration | Automatically syncs to Google Drive |
Operation Steps:
- After clicking the download icon, a pop-up window will display format options.
- Select the format you need (e.g., .xlsx).
- If you select “Schedule export”, you can set:
- Frequency (Daily, Weekly, Monthly).
- Recipient email (automatically sent to the specified email).
Example, if you want to automatically receive ad data weekly:
- Select “Schedule export”.
- Set to send every Monday morning at 8 am.
- Enter your email (e.g., marketing@example.com).
Set Export Scope (Optional)
Filter Specific Data
Before exporting, you can further filter the data:
- Ad Type (Search ads, Display ads, Video ads).
- Serving Status (Only running ads, paused ads).
- Budget Range (e.g., campaigns that spent over $100).
Example, if you only want to export “High CTR Ads”:
- Above the data table, click “Filter”.
- Select “CTR” > “Greater than” > “5%”.
- Then click download.
Adjust Date Range
Google Ads supports various date options:
- Preset ranges (Yesterday, Last 7 days, This month).
- Custom range (e.g., January 1, 2024 – January 31, 2024).
Confirm and Download
Check Data Accuracy
Before downloading, it is recommended to:
- Confirm the date range is correct.
- Check if all required metrics (such as conversion data) are included.
- Ensure there are no accidental filters (e.g., inadvertently excluding certain campaigns).
Download and Store
- Click “Download”, and the file will be saved to the default download folder.
- It is recommended to name the file by Project + Date, for example:
- “Brand_Campaign_Jan2024.xlsx”
- “Performance_Ads_2024-01-15.csv”
Automatic Export Management
If you have set up a scheduled export, you can manage it at the following location:
- Tools & Settings > Bulk actions > Scheduled exports.
- You can edit, pause, or delete automatic export tasks here.
Use Google Ads API to Export Data (Suitable for Developers)
If your data volume is extremely large, or you need automated export, you can use the Google Ads API.
Operation Steps:
Apply for API access permission:
- Go to the Google Ads API official website.
- Obtain a Developer Token.
Use Python or Google Sheets scripts:
Example Python code (using the google-ads-api library):
from google.ads.google_ads.client import GoogleAdsClient
client = GoogleAdsClient.load_from_storage()
query = “””
SELECT campaign.id, campaign.name, metrics.clicks
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
“””
response = client.service.google_ads.search(query=query)
print(response)
Automate data import to the database:
- You can set up scripts to run automatically every day to store data in MySQL, BigQuery, etc.




