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How to export data from Google Ads | Follow 5 steps to complete the export

作者:Don jiang

Export Steps: Log in to Google Ads account > Go to Reports or Data View > Select export format > Set export range (optional) > Confirm and download

Below are detailed operations

How to export data from Google Ads

Log in to Google Ads Account

Visit Google Ads Official Website

First, you need to access the Google Ads official website:

  • URL: https://ads.google.com
  • Make sure you are logged in with the Google account associated with your advertising account.

Select the Correct Account (For Multi-Account Users)

If you manage multiple Google Ads accounts, after logging in the system will display an account list. You need to:

  1. Click the account selector in the upper right corner (usually displays account name or email).
  2. Select the target account from the dropdown menu.

Example, assuming you manage two accounts:

You need to select the account from which you want to export data, such as Account A.

Check Account Permissions

Admin Permissions: Make sure 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 “Admin” or “Standard User”.

Go to Reports or Data View

Google Ads provides multiple data export methods. You can choose to export directly from the dashboard or use the Reports feature

Method 1: Export Data from Dashboard

Suitable for quickly exporting campaign, ad group, or keyword data.

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 and select 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, if you want to export data from “Search Campaigns” for the past 30 days:

  1. Click “Campaigns” in the left menu.
  2. Select the date range above the table (such as “Last 30 days”).
  3. Click the download icon.

Method 2: Export via “Reports” Feature

Suitable for more complex data analysis, such as custom reports and cross-campaign comparisons.

Steps:

  • Click “Reports” in the left menu.
  • Choose “Predefined Reports” or “Custom Tables”:
    • Predefined Reports: Such as “Campaign Performance,” “Device Reports,” etc.
    • Custom Tables: You can freely select dimensions (such as time, device, geographic location) and metrics (such as spend, conversion rate).
  • Adjust report parameters:
    • Date Range (such as “Custom Date” selecting January 1, 2024 – January 31, 2024).
    • Breakdown Dimensions (such as by “Device” or “Geographic Location”).
  • Click the download icon (↓) in the upper right corner.

Example, if you want to analyze the “Advertising Performance Difference Between Mobile Devices and PC”:

  1. In “Reports,” select “Device Report”.
  2. Set the date range to “Last Month”.
  3. Click Download and choose Excel format.

Select Export Format

Google Ads supports multiple file formats for different needs:

Format Use Case Features
.csv Data analysis (Python, R, Excel) Plain text, high compatibility
.xlsx Excel analysis Supports charts, formulas
.pdf Printing or sharing Suitable for presentations
.tsv Database import Similar to CSV but tab-separated
Google Sheets Cloud collaboration Auto-syncs to Google Drive

Steps:

  • After clicking the download icon, a popup window will display format options.
  • Select the format you need (such as .xlsx).
  • If you select “Scheduled Export”, you can set:
    • Frequency (daily, weekly, monthly).
    • Receiving email (auto-send to specified email).

Example, if you want to receive advertising data automatically every week:

  1. Select “Scheduled Export”.
  2. Set to send every Monday at 8 AM.
  3. Enter your email (such as [email protected]).

Set Export Range (Optional)

Filter Specific Data

Before exporting, you can further filter the data:

  • Ad Type (Search ads, Display ads, Video ads).
  • Delivery Status (Only running ads, Paused ads).
  • Budget Range (Such as campaigns with spend over $100).

Example, if you only want to export “High CTR Ads”:

  1. Click “Filter” above the data table.
  2. Select “CTR” > “Greater than” > “5%”.
  3. Then click download.

Adjust Date Range

Google Ads supports multiple date options:

  • Preset Ranges (Yesterday, Last 7 days, This month).
  • Custom Range (Such as January 1, 2024 – January 31, 2024).

Confirm and Download

Check Data Accuracy

Before downloading, it is recommended to:

  1. Confirm the date range is correct.
  2. Check if all required metrics are included (such as conversion data).
  3. Ensure no incorrect filtering (such as accidentally excluding certain campaigns).

Download and Store

  1. Click “Download” and the file will be saved to the default download folder.
  2. It is recommended to name the file using Project + Date, for example:
    • “Brand_Campaign_Jan2024.xlsx”
    • “Performance_Ads_2024-01-15.csv”

Manage Auto Export

If you have set up a Scheduled Export, you can manage it in the following location:

  1. Tools & Settings > Bulk Operations > Scheduled Exports.
  2. You can edit, pause, or delete auto-export tasks here.

Export Data Using Google Ads API (For Developers)

If you have a large amount of data or need automated export, you can use the Google Ads API.

Steps:

Apply for API Access:

  • Go to the Google Ads API Official Website.
  • Get your Developer Token.

Using Python or Google Sheets Scripts:

Example Python code (using 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)

Automated Data Import to Database:

  • You can set up the script to run automatically daily, storing data to MySQL, BigQuery, etc.
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