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.
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 converting dates and times of various formats into a logical timestamp, based on six templates using three format sets: DATE, TIME, and TIMEZONE. Data Manager does not support the DATETIME type. DATETIME fields need to be converted to the STRING type in the data source, using the supported formats described in this article.
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 17:01:5408/14/2012T5:01:54 PM2012-08-14 5:01:54 PM08/14/2012 17:01:542012-08-14 17:01:5408/14/2012 17:01:54*1232012-08-14T17:01:54-0708/14/2012T17:01:54-07002012-08-14T17:01:54-0700002012-08-14T17:01:54-07:00:002012-08-14T17:01:54 America/Los_AngelesAug 14, 2012 17:01:54PST2012-08-14 17:01:54 PST2012-08-14 17:01:54 Pacific Standard Time2012-08-14 17:01:54 GMT-07:0008/14/2012 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 |
|
Supported timezone formats
|
Description |
Example |
|
Localized Offset Text with hour (without leading zero) |
|
|
Localized Offset Text with 2-digit hour and minute fields, with colons |
|
|
Localized Offset Text with 2-digit hour, minute, and seconds fields, with colons |
|
|
Zero (UTC) |
|
|
Zone ID |
|
|
Offset hour |
|
|
Offset hour and minute with colon |
|
|
Offset hour, minute, and second with colon |
|
|
Offset hour and minute, no colon |
|
|
Offset hour, minute, and second, no colon |
|
|
Short zone name |
|
|
Long zone name |
|
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 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, see 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) |
|
Lowercase, no extra spaces | |
| Phone number (Required) |
|
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:
For all other countries:
|
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) |
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: [email protected] |
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 |
|
|
The date and time at which the conversion occurred. Note: It is recommended to add “parse timestamp” transformation. This transformation will require you to determine the default timezone in the UI, and this will 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.
Offline conversion import also supports these additional formats:
|
Required |
Required |
|
|
Conversion value |
Used in Value-based Bidding Strategies. Learn more About conversion values. |
Optional |
Optional |
|
Order ID |
Unique identifier for the transaction, such as an order confirmation number. Learn more about order ID. |
Optional |
Optional |
| GBRAID | The click identifier for clicks associated with app conversions and originating from iOS devices starting with iOS14. |
Optional |
Optional |
|
WBRAID |
The click identifier for clicks associated with web conversions and originating from iOS devices starting with iOS14. |
Optional |
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 data stage of setup:
- From the Select data step of setup, click Filter to expand it.
- Select the field to use to filter your data.
- Select an operator.
- Enter a value.
- Optional: Create additional conditions, by clicking And or 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
- 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