Salesforce Inbound Connector
Suite
Customer Experience
Product
Qualtrics
What's on this page
About the Salesforce Inbound Connector
You can use the Salesforce inbound connector to load operational reporting data from your Salesforce account into XM Discover.
Attention: Salesforce is deprecating its legacy chat product on February 14, 2026. You can request an extension to this deprecation by contacting your Salesforce account team. In XM Discover, the ‘Salesforce Chat’ data type continue to work for any customers granted an extension by Salesforce. Data ingested before this date will still be available, and this Connector will continue to support other data types beyond that date. Please contact your XM Discover account team with any questions.
Required Setup in Salesforce
To connect XM Discover to Salesforce, you will need the following information about your Salesforce account:
- Your Salesforce Consumer Key (client ID)
- Your Salesforce Consumer Secret (client secret)
- Your Salesforce username and password
- Your Salesforce organization’s environment URL
- A valid Salesforce Object Query Language (SOQL) query to retrieve feedback or chat interactions Qtip: SOQL enables you to search your organization’s Salesforce data for specific information. SOQL is similar to the “SELECT” statement in the widely used Structured Query Language (SQL) but is designed specifically for Salesforce data. For an introduction to SOQL, please see this Salesforce help page.
Additionally, you must perform the following in your Salesforce account:
Setting Up a Salesforce Inbound Job
Qtip: The “Manage Jobs” permission is required to use this feature.
Default Data Mapping
Attention: As field names are case-sensitive in Connectors, the first letter of the field name must be upper-case as displayed in the Data Sample to ensure data mappings are accurate and the job succeeds. The field names for Salesforce’s SOQL queries are case-insensitive.
This section contains information on the default fields for Salesforce inbound jobs.
- natural_id: A unique identifier of a document. It is highly recommended to have a unique ID for each document to process duplicates correctly. For Natural ID, you can select any text or numeric field from your data. Alternatively, you can automatically generate IDs by adding a custom field.
- document_date: The primary date field associated with a document. This date is used in XM Discover reports, trends, alerts, and so on. By default, this is mapped to the date field selected after specifying the SOQL query. You can choose one of the following options:
- CreatedDate (default): The date when the Salesforce object was created.
- ClosedDate (for chat data): The date when the case was closed.
- If your source data contains other date fields, you can choose one of them.
- You can also set a specific document date.
- feedback_provider: Identifies data obtained from a specific provider. For Salesforce uploads, this attribute’s value is set to “Salesforce” and cannot be changed.
- source_value: Identifies data obtained from a specific source. This can be anything that describes the origin of data, such as the name of a survey or a mobile marketing campaign. By default, this attribute’s value is set to “Salesforce.” Use custom transformations to set a custom value, define an expression, or map it to another field.
- feedback_type: Identifies data based on its type. This is useful for reporting when your project contains different types of data (for example, surveys and social media feedback). By default, this attribute’s value is set “Operational Reporting”. Use custom transformations to set a custom value, define an expression, or map it to another field.
- job_name: Identifies data based on the name of the job used to upload it. You can modify this attribute’s value during the setup via the Job Name field that is displayed at the top of each page during the setup.
- loadDate: Indicates when a document was uploaded into XM Discover. This field is set automatically and cannot be changed.
Qtip: See Mapping Conversational Fields for information on how to map conversational data.
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