Prepare your data for import

Learn how to prepare your data for successful import.

Keep your data fresh

You must ensure your data is refreshed in the data source before a manual or scheduled connection run in order for that data to be imported for use in the intended destination or use case. For example, if you choose a daily schedule, you need to refresh your data on a daily basis, before the scheduled start time.

Make your data available

When connecting to a data source, each use case you want to implement should have its own dedicated table or a filtered subset of table data within that source. You can reuse the same table from a connected data source for multiple use cases, including a conversion event or audience list, by using different filtered subsets of that table.

Note: You can create filtered subsets for tables directly within Google Ads.

Some data sources require you to have proper credentials in order to make the connection, while others require that the data be accessible by Data Manager's services. See the specific guide for the data source you're using for specific guidance.

Format your data

The following sections show you how to properly format your data, to ensure it can be imported without error.

About file formats

If you are uploading a file, such as a CSV file, the first line of the file must contain the headers.

Ensure that the file has an extension, as files without extensions are rejected.

About date and time formats

Data Manager supports the import and conversion of any approved timestamp formats. These supported timestamps are based on 6 templates using 3 format sets: DATE, TIME, and TIMEZONE.

Upon import, the list may be populated with varying types of data formats. You can then use the “Convert date and time” transformation to automatically standardize timestamps, dates, datetimes, unix epoch, or string representations of that data.

Note: The "Convert date and time" transformation will be added to conversion event time/date columns by default.

For rows of data that are missing a timezone, you can set a fallback timezone for the transformation in the Transformation settings panel. If no fallback timezone is selected, rows without a timezone won’t be imported. The fallback timezone for open-ended file connections is pre-populated as the timezone associated with the account, but this can be changed in the transformation menu.

Learn more about the Convert date and time transformation .

The following are examples of timestamps in supported formats:

2012-08-15T00:01:54Z (UTC ISO 8601 Standard)
2012-08-14T17:01:54-07:00 (ISO 8601 Standard with Offset)
Aug 14, 2012 17:01:54
08/14/2012T5:01:54 PM
2012-08-14 5:01:54 PM
08/14/2012 17:01:54
2012-08-14 17:01:54
08/14/2012 17:01:54*123
2012-08-14T17:01:54-07
08/14/2012T17:01:54-0700
2012-08-14T17:01:54-070000
2012-08-14T17:01:54-07:00:00
2012-08-14T17:01:54 America/Los_Angeles
Aug 14, 2012 17:01:54PST
2012-08-14 17:01:54 PST
2012-08-14 17:01:54 Pacific Standard Time
2012-08-14 17:01:54 GMT-07:00
08/14/2012 17:01:54 GMT-07:00:00

Supported date formats

Format	Example
`MMM dd, yyyy`	`Aug 14, 2012`
`MM/dd/yyyy`	`08/14/2012`
`yyyy-MM-dd`	`2012-08-14`

Supported time formats

Format	Example
`h:mm:ss a`	`5:01:54 PM`
`HH:mm:ss`	`17:01:54`
`HH:mm:ss*SSS`	`17:01:54*633` (fraction of a second)

Supported timezone formats

Description

Example

Localized Offset Text with hour (without leading zero)

GMT-7
GMT+5

Localized Offset Text with 2-digit hour and minute fields, with colons

GMT-07:00
GMT+05:30

Localized Offset Text with 2-digit hour, minute, and seconds fields, with colons

GMT-07:00:00
GMT+05:30:00

Zero (UTC)

Zone ID

America/Los_Angeles
Asia/Kolkata

Offset hour

-07
+05

Offset hour and minute with colon

-07:00
+05:30

Offset hour, minute, and second with colon

-07:00:00
+05:30:00

Offset hour and minute, no colon

-0700
+0530

Offset hour, minute, and second, no colon

-070000
+053000

Short zone name

PST
IST

Long zone name

Pacific Standard Time
Indian Standard Time

About hashing private customer data

To keep your data secure, private customer data that you import should be hashed. Data Manager will hash the data for you using the SHA256 algorithm, which is the industry standard for one-way hashing. The result is hex encoded. You don’t need to pre-format your data. Data Manager will normalize relevant PII (personally identifiable information) fields, perform hashing and encoding for you, and push the data to the API for your use cases.

If you prefer to hash private customer data yourself, check Format your customer data file to ensure it’s formatted correctly. If you upload a hashed data file, don’t hash non-private customer data. Data Manager will push your hashed data to the API.

Note that smart hashing is automatic, meaning you don't need to select anything from the Actions menu.

Schema for first-party data import

Customer Match

Field

Description

Required format before hashing

Email (Required)

Email address of consented user
Must be normalized and SHA256 hashed.

Lowercase, no extra spaces

Phone number (Required)

Phone number of consented user.
Must be normalized and SHA256 hashed.

E.164 format, no extra spaces

Mailing address (Required)

Country code

ISO two-letter or three-letter country codes are expected.

Lowercase, no extra spaces

Postal code

For United States:

5 digit codes are allowed
5 digits followed by 4 digit extension are also allowed and may improve your match rate

For all other countries:

Leave out postal code extensions

String

Hashed first name

Shouldn’t include prefixes.

Lowercase, alphabetical characters only

Hashed last name

Shouldn’t include prefixes.

Lowercase, alphabetical characters only

Device ID (Not required)

Mobile Device IDs, GAID, or IDFA is expected.

String

User_id (Not required)

The unique customer identifier by which an advertiser chooses to identify a user visiting their website.

String

Use a template or create your own file using a combination of the following header names in English: "Email," "Phone," "First Name", "Last Name", "Country", and "Zip”. Learn more about formatting your customer data file .

Offline conversion import and enhanced conversions for leads

Notes:

To have access to enhanced conversion for leads, you need to accept the terms of service under Goals> Conversions> Settings. After you accept the terms of service for enhanced conversions for leads, personally identifiable information such as email and phone will be accessible for conversion attribution in addition to Google Click ID (GCLID).
To maximize the performance of your enhanced conversions for leads, import all available data, including both Google Click ID and personally identifiable information. The more data you provide, the better we can match and attribute your conversions.
For Google Cloud Storage (GCS), Amazon S3, HTTP, SFTP, and gSheets, Google Ads Data Manager imports conversions from 90 days ago in every run. For Salesforce and HubSpot, Data Manager imports the last 14 days of data in the first successful run, and in every new run after that, it imports all changes that occurred and were reported between the last successful run and the current one. For BigQuery, Amazon Redshift, Snowflake, MySQL, and PostgreSQL, Data Manager imports the last 14 days of data in every run.

Field

Description

Enhanced conversions for leads

Offline conversion import

Conversion action

The name of the event you wish to import as a conversion.

Optional (To filter conversion actions)

GCLID

The Google click ID (GCLID) associated with this conversion.

Optional if Tag is configured for User-Provided Data. Required if customer is not using Tag with User Provided Data

Required

Email Address

The user email address

Example: abc@email.com

At least one of either email address or phone number should be mapped

N/A

Phone number

User phone number. Must be in E.164 format, which means it must be 11 to 15 digits including a plus sign (+) prefix and country code with no dashes, parentheses, or spaces.

Example: ‘+11231234567’

N/A

Conversion date and time

The date and time at which the conversion occurred.

Note: It is recommended to add “convert date and time” transformation. With this transformation, we recommend that you determine a fallback timezone in the UI, to cover all rows of data with missing timezones. In addition to transformation, you are able to include timezone in your data as well.

The offline conversion import supports the same formats as Data Manager.

2012-08-15T00:01:54Z - UTC ISO 8601 Standard
2012-08-14T17:01:54-07:00 - ISO 8601 Standard with Offset
Aug 14, 2012 17:01:54
08/14/2012T5:01:54 PM
2012-08-14 5:01:54 PM
08/14/2012 17:01:54
2012-08-14 17:01:54
08/14/2012 17:01:54*123
2012-08-14T17:01:54-07
08/14/2012T17:01:54-0700
2012-08-14T17:01:54-070000
2012-08-14T17:01:54-07:00:00
2012-08-14T17:01:54 America/Los_Angeles
Aug 14, 2012 17:01:54PST
2012-08-14 17:01:54 PST
2012-08-14 17:01:54 Pacific Standard Time
2012-08-14 17:01:54 GMT-07:00
08/14/2012 17:01:54 GMT-07:00:00

Offline conversion import also supports these additional formats:

2012-08-14 17:01:54GMT-7
Aug 14, 2012 17:01:54 GMT-7

Required

Conversion value

Used in Value-based Bidding Strategies. Learn more About conversion values .

Optional

Order ID

Unique identifier for the transaction, such as an order confirmation number. Learn more about order ID .

Optional

GBRAID

The click identifier for clicks associated with app conversions and originating from iOS devices starting with iOS14.

Optional

WBRAID

The click identifier for clicks associated with web conversions and originating from iOS devices starting with iOS14.

Optional

User IP address

The user's IP address. It's recommended to use IPv6 for better accuracy. However, using IPv4 is acceptable.

Optional

User agent

Identifies the browser and type of device that sent the conversion.

Optional

Session attributes

Provides additional context about the user's interaction with your website, which can enhance conversion measurement. gad parameters are sent through session attributes. Learn more About session_attributes .

Optional

You can add more columns aside from the ones listed above and the added columns can be used to filter your data in Google Ads.

Define the scope of your data import using filters

Data Manager lets you set filter conditions directly in the UI, eliminating the need to create custom data pipelines or write complicated SQL queries within your data source. When you create a filter, Data Manager only imports data from your data source (for all use cases) that satisfies all of the filter conditions.

Use filters to define audience segments for Customer Match or conversion events for Offline Conversion Import. For example, define an audience segment from your Salesforce data based on attributes such as user consent, average order value, or opportunity stage. You can apply one filter with up to 25 conditions per connection.

Create a filter

To create filters for a new data connection, add them during the Select datastage of setup:

From the Select datastep of setup, click Filterto expand it.
Select the field to use to filter your data.
Select an operator.
Enter a value.
Optional: Create additional conditions, by clicking Andor Or.
Continue the setup process.

To create and edit filters for an existing data connection:

From the Data manager screen, click on the connection name to edit it.
Under Filter, click Edit.
Make your changes and click Save.

Supported operators

AND (Salesforce doesn't support the AND operator)
OR
Doesn’t contain (strings, integer, date, time, Boolean)
Contains (strings, integer, date, time, Boolean)
Greater than (integer)
Equal to (integer, string, date)
Less than (integer)
Before (date, time)
After (date, time)
Does not equal
Starts with
Ends with
Does not start with
Does not end with

Supported data types

Currency
Date
Time
Boolean
Integer
Dropdown (for example, a Salesforce picklist type)
String

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