has been moved to 'Data manager' under Tools 
. Google Ads Data Manager is a data import and management tool with a point-and-click experience that lets you bring your customer data from outside of Google and activate it in Google Ads. Learn more About Data manager.The Salesforce integration with Google Ads allows for transformation actions to help with field mapping while setting up conversions. This article describes the available transformations for the Salesforce integration and how they work.
How it works
Some transformations are automatically recommended. For instance, you may notice recommended compute hash transformations on automatically mapped hashed_email and hashed_phone_number fields. You can modify the automatically recommended transformation or add additional ones as needed. You can specify a series of transformation actions on an input field, and they’ll be applied from top to bottom.
Before you begin
To apply transformations during field mapping, click on the 3-dot menu 
Available transformation actions
Compute hash
Transformations are applied on an input column to convert the column to some result. When you compute a hash for a column, the SHA256 algorithm is supported. The result is hex encoded.
The Salesforce integration also does special normalisation for hashed email and phone number fields.
- Email: Learn how to normalise and hash an email address.
- Phone number: Pull digits out and append '+' as the prefix.
Multiply
Make sure to multiply the column by a constant floating number. The input column must have a numerical type.
Transform case
Change the column to uppercase, lowercase or titlecase. The input column can be any type. The transformation action will convert it to a string first.
Merge fields
You can combine two columns with a separator. The input field is the source field from the row where you click the 'transform' button. This transform will add the value from the 'column to merge' field to the source field after a specified separator string.
Parameters:
- Separator
- Another column name
The result is {input_column}{separator}{another_column}.
Split
Split a string column per delimiter and extract one part.
Parameters:
- 'Delimiter' must be a single character.
- 'Occurrence' indicates the k-th occurrence of the delimiter to split the string. Start from one.
- 'Before' indicates to extract the part before the delimiter or after the delimiter.
Example:
If the input column holds 'FirstName MiddleName LastName'.
- delimiter=' ', occurrence=1, before=true
- result="FirstName"
- delimiter=' ', occurrence=1, before=false
- result="MiddleName LastName"
- delimiter=' ', occurrence=2, before=true
- result="FirstName MiddleName"
- delimiter=' ', occurrence=2, before=false
- result="LastName"
Cast type
| What type do you want to cast to? | Source field type | Note |
| STRING | ANY | Any type can be casted to string. |
| Real number | String |
Real number is of data type double. If string values can’t be parsed as a double at import time, you’ll notice an error in the 'Runs' table. |
| Real number | Integer | |
|
Integer |
String | If a string can't be parsed as an integer, the row is marked as error ('rows with errors'). |
| Integer | Real number/Per cent |
