Connect Salesforce to Google Cloud Storage — GCP Data Lake Foundation

Log into the Supermetrics Hub, create a new data transfer, select Salesforce as the source and Google Cloud Storage as the destination. Authenticate with your Google Cloud account, choose your GCS bucket and folder prefix, select your file format and fields, set a schedule, and start the transfer. Supermetrics writes structured files to your bucket automatically — no Cloud Functions or Dataflow pipelines required. For the fastest path to SQL analytics, choose Parquet format and create a BigQuery external table pointing at your GCS prefix: you get instant, zero-copy queries over your marketing data without any loading step.

Supermetrics is SOC 2 Type II certified and GDPR compliant. All data transfers use TLS encryption in transit. In GCS, your data is encrypted at rest by default with Google-managed keys, but you can also use customer-managed encryption keys (CMEK) stored in Cloud KMS or customer-supplied encryption keys (CSEK) that Google never retains. IAM policies and bucket-level permissions control who can read or write, and VPC Service Controls can create a security perimeter that prevents data exfiltration. GCS also supports retention policies and bucket lock for regulatory compliance. Supermetrics does not retain your data after delivery.

Absolutely. GCS is the central storage layer for the entire Google Cloud analytics stack. Transfer Salesforce alongside GA4 exports, Google Ads, CRM data, and any other source into the same bucket. Create BigQuery external tables for ad-hoc cross-source queries without loading data, or use Dataflow (Apache Beam) and Dataproc (Spark/Hadoop) for heavy transformations. You can also wire Cloud Functions or Cloud Run to trigger automatically via Eventarc whenever Supermetrics delivers a new file — enabling real-time enrichment, validation, or alerts. Supermetrics supports 170+ sources, all deliverable to the same GCS bucket.

All standard Salesforce reporting metrics and dimensions are available, including Opportunity count, Amount won, Hit rate, Average amount per opportunity, Age (days), Leads count, and more. You select exactly which fields to include during setup. Data arrives as clean, structured files in CSV, JSON, or Parquet. Parquet is the recommended choice for GCS-based analytics: BigQuery external tables, Dataflow, and Dataproc all leverage its columnar layout for predicate pushdown and column pruning, which means faster queries and lower processing costs — especially valuable when scanning months of campaign history.

Transfers can run hourly, daily, weekly, or monthly. Daily is the most common choice — yesterday's Salesforce data is ready in your bucket each morning. Incremental delivery means only new and updated records are written, keeping file sizes manageable and storage costs near zero. To minimize costs further, enable GCS Autoclass on your bucket: it automatically moves each object between Standard, Nearline, Coldline, and Archive tiers based on access frequency, so recent campaign data stays fast to query while historical data shifts to cheaper storage without any manual lifecycle rules.

Yes. All opportunity fields including stage, amount, probability, and close date are available in the structured file exports.

Yes. Lead counts, lead sources, and campaign attribution data are all included.