Salesforce Docs Portal

Create an API Data Stream Using the Marketing Cloud Intelligence Data Pipelines Connector for B2C Commerce

Create an API data steam to connect your Commerce Cloud site data to Marketing Cloud Intelligence Data Pipelines. You can bring in either product-level or order-level data. Product-level data includes revenue generated for each product (SKU) according to the date range. Order-level data is aggregated order revenue over time without the details of specific products.

Required Editions

User Permissions Needed
To create an API data stream: Admin

Before you can use the connector, set up B2C Commerce API access by generating an API client ID. See Generate an API Client for Marketing Cloud Intelligence Data Pipelines.

  1. On the Import tab expand Data Streams.
  2. Click Add New.
  3. Select the Salesforce Commerce Cloud B2C connector.
  4. In the General section, enter your Commerce Cloud credentials.
  5. Select the site that you’re pulling data for. In the Initial data fetch section, select the dates you want to pull data for. The default is 30 days. You can process data up to 180 days prior, queried in 90-day intervals.
  6. If you want to bring in order-level data, under Extended Properties, deselect Bring only product (SKU) level data. Select this option to bring in product-level data.
  7. To change the mapping, on the bottom of the Create New Stream page, select Map to Model. To learn more about mapping, see Mapping Your Source Data in Marketing Cloud Intelligence Data Pipelines.
  8. To define advanced settings for the data stream, on the bottom of the Create New Stream page, select Advanced Settings. To learn more about defining advanced settings, see Advanced Settings in Data Streams.
  9. Click Create.
  10. Quality check your data:
    1. Create a report in Commerce Cloud for the date range, and then process the relevant data stream in Marketing Cloud Intelligence Data Pipelines for the same date range.
    2. For order-level data, compare the number of orders and revenue generated.
    3. For product level data, compare the total number of units and revenue.
    4. In Marketing Cloud Intelligence Data Pipelines, create a report, or pivot table containing the same dimensions and measurements for the same report and date range.
    5. Compare the measurement totals and make sure that they align.