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
All use cases require one table or dataview per conversion event or audience list. To use the same data source for an additional conversion event or audience list, you need to create an additional table or dataview.
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. Check 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. Keep them in mind 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 |
17:01:54*633 (fraction of a second) |
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 (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 will not need to select anything from the Actions menu.
Row count limits
Data imports shouldn’t exceed 1,000 rows. If your source data has more than 1,000 rows, you should create separate, smaller files for import or filter the data so it falls under the 1,000 row limit.
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.
You can apply one filter with up to 25 conditions per connection. To set up or edit these filters, learn more in Manage your connections.
Search Ads 360 specific Identifiers
To successfully upload offline first-party data to Search Ads 360 using the Search Ads 360 / Data Manager integration, your conversion data needs to include specific identifiers. For Search Ads 360 to correctly attribute these conversions, you must provide at least one of the following: dclid, gclid, matchId, mobileDeviceId, or impression_id.
| Field | Description | Required (Y/N) for mapping |
| gclid | A Google Click Identifier generated by Google Ads or Search Ads 360. |
Exactly one of the fields in the first column must be mapped. For Search Ads 360 purposes, you should prefer the matchId option, or barring that, the gclid option. |
| matchId | A unique advertiser created identifier passed to Campaign Manager 360 via a Floodlight tag. | |
| mobileDeviceId | An unencrypted mobile ID in the IDFA or AdID format or a Connected TV Identifier for Advertising (IFA) from a supported CTV device platform (Roku, Fire TV, Android TV, Apple TV, Xbox, Samsung, Vizio). Note that Google does not support YouTube Connected TV IFAs. | |
| impression_id | The impression_id is primarily used for VTC measurement use case on SA3. | |
| dclid | A Display Click Identifier generated by Campaign Manager 360 or Display & Video 360. |