What this means for your store
External data connectors pull non-Salesforce sources - S3 CSV, Snowflake, GCS - into CRM Analytics on a schedule. Wholesale teams often close in Salesforce and fulfil through Shopify Plus or BigCommerce; without blending, “revenue” means different things to sales and ecommerce. Match on AccountId, external order ID, or whatever key your MDM actually maintains.
Scenario on a real storefront
A trade-only US storefront exports nightly B2B orders to S3. A dataflow ingests the CSV and joins to Account on ShopifyCompanyId__c:
# Dataflow - S3 connector (conceptual)
s3Digest shopify_orders from s3://analytics-bucket/shopify/b2b_orders.csv
delimiter: ','
header: true
sfdcDigest Account as acct
augment orders_acct = shopify_orders, acct,
shopify_orders.CompanyExternalId == acct.Shopify_Company_ID__c
@source = 'leftouter'
# Recipe: MatchRate, flag unmatched orders
# Lens: Salesforce Amount vs Shopify OrderTotal by Account
# Setup: CRM Analytics → External Data → IAM role → test → schedule after exportWhat to do next
- Normalize currency and timezone before joining - GBP storefront totals plus USD Opportunity amounts will fool leadership.
- Upstream exports that shift column order break connectors quietly; use dated file paths and schema checks.
- Keep a quarantine lens for unmatched rows so ops fixes Account keys instead of hiding gaps in blended revenue.
Bottom line
External connectors unite storefront orders with Salesforce pipeline. Schedule after your ecommerce export, join on a stable business key, review unmatched rows weekly.