Every action in Salesforce Data Cloud runs on credits. Think of them like digital fuel—each time you ingest, process, or activate data, you burn through your credit stash. Some actions sip credits gently, while others guzzle them like a thirsty camel in the desert. The key? Use them wisely.
How Pricing Works
Data Cloud pricing has three main parts:
Storage: How much data you store (measured in terabytes).
Data Services: Actions like connecting, harmonizing, and activating data, which consume credits.
Add-Ons: Fancy extras like Data Spaces, Advertising Audiences, and Segmentation (because who doesn’t love a good upgrade?).
Credit Consumption Breakdown
Every action in Data Cloud has a compute cost, which means:
Connecting data: Ingesting info from different sources.
Harmonizing data: Cleaning and unifying profiles.
Activating data: Sending it where it needs to go for marketing, sales, or other use cases.
For example, let’s say you:
Import 1 million customer records – that’s 2,000 credits.
Apply transformations to clean them – another 2,000 credits.
Ingest 2 million e-commerce interactions – 10,000 credits.
Total? 14,000 credits gone.
Right now, you have to ask your Salesforce Account Executive for a consumption report, which is a little old-school. However, the Digital Wallet will let you track credits and storage inside the platform.
Smart Strategies to Save Credits
Since credits are precious, here’s how to make them last:
Be Selective with Data Ingestion
Import only what’s needed for segmentation and analytics.
Limit historical data—9 months might be enough instead of years.
Use incremental refresh instead of full refresh.
Optimise Data Processing
Pre-transform data before ingesting it using ETL tools.
Combine calculated insights to reduce redundant calculations.
Refresh data only as often as necessary—if the source updates weekly, don’t refresh daily.
Master Segmentation & Activation
Shorten lookback periods to avoid processing years of unnecessary data.
Use nested segments to reuse existing segment members.
Filter data efficiently—merge filters to avoid multiple queries.
Opt for incremental refresh instead of full refresh for activations.
Identity Resolution: Handle with Care
This process eats credits fast, so:
Start with a small data sample to check accuracy.
Validate unified profiles using Data Explorer before full-scale ingestion.
Anonymous profiles don’t count—ensure the ‘Is Anonymous’ field is mapped.
Leverage ‘Bring Your Own Lake’ (BYOL) Wisely
Data federation can help avoid unnecessary data movement, but:
- Only share the specific objects needed from Snowflake, BigQuery, or Redshift.
- Use acceleration for static attributes to avoid repeatedly querying external data.
- If your Data Cloud org and BYOL platform share an AWS region, shared rows are free.
The Takeaway
Salesforce Data Cloud credits are a powerful resource—but they can vanish fast if you’re not careful. By monitoring usage, optimizing ingestion, and fine-tuning processing, you can stretch your credits further and make the most of your Data Cloud investment.
Need help optimizing your Data Cloud setup? Let’s chat! We love helping businesses make Salesforce work smarter, not harder.
