Salesforce Data Cloud Pricing and Credit Consumption model can be complex.
You have licenses.
Credit consumption.
Then add-ons.
Complex pricing models are something that some CIOs and CTOs might steer away from at first sight.
In this guide, I will cover every aspect of that pricing and consumption model so that your org can make informed decisions when deciding to go for Salesforce Data Cloud CDP.
The new car purchase model
Purchasing Salesforce Data Cloud can be similar to buying a new car.
When you purchase a car, there are 3 layers or components:
- The car model itself (upfront, fixed cost)
- The accessories or extras (upfront, fixed cost)
- The pay-as-you-go gasoline (variable cost, usage based)
Let’s see an example:
I am a huge fan of the Japanese brand Toyota. Let’s say I want to purchase a new Toyota this year. The 3 layers could be:
- Toyota RAV4 model, standard version.
- As add-ons: 1) door edge guards and 2) extra storage area
- Finally, I’ll spend around 70 EUR on gasoline per month, on a monthly basis
That’s it. Now let’s translate this into Salesforce Data Cloud pricing.
Salesforce Data Cloud Pricing – Overview
Salesforce Data Cloud has the exact same 3 layers:
- Core Package
This is an upfront cost that the org pays at the beginning. It includes the core Salesforce Data Cloud features, some initial entitlements of credits, the license, etc. Type: fixed cost (normally renewed once a year) - Accesories / add-ons
These are extras you can purchase with your license, and they include certains components such as Data Spaces (similar to how Business Units are purchased in Salesforce Marketing Cloud Engagement), more Data Storage, Support levels, etc. Type: fixed cost (usually renewed once a year) - Data Cloud Credits
These are the variable consumption credits that Salesforce Data Cloud bills for certain actions performed on the platform. For instance, creating Segments uses credits, and so does running Identity Resolution rulesets. Type: variable cost (initial entitlement with core license + pay-as-you-go packages)
Now, of course each of those layers has a bit more complexity than just that. Let’s analyse each in detail.
Please take into account that Salesforce might change their pricing, licenses and credit models in the future. When possible, I will link to the official Salesforce Documentation links. Also, you should always check with your Account Executive for the latest and most up to date pricing version, rate cards, etc. The information in this guide is for educational purposes only.
For an introduction to Salesforce Data Cloud licenses, editions and billing, please check the following official documentation links:
– https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&type=5
– https://help.salesforce.com/s/articleView?id=data.c360_a_data_usage_types.htm&type=5
– https://www.salesforce.com/data/rates/multipliers/
Salesforce Data Cloud License and Editions
The first component of the contract is the core package and license you purchase.
First, the editions available for Salesforce Data Cloud are the following ones:
- Developer Edition
- Enterprise Edition
- Performance Edition
- Unlimited Edition
Please keep in mind that these are Salesforce Editions, as Data Cloud is already provisioned in your Salesforce home Org prior to activation.
For a full comparison of Salesforce Editions and their features, limits, etc, please refer to the following official documentation link:
https://help.salesforce.com/s/articleView?id=xcloud.overview_edition.htm&type=5
Then, there are 3 types of Salesforce Data Cloud licenses, each of them with different functionality, entitlements, etc:
Customer Data Platform License
This is a legacy license type, no longer available for renewal or purchase.
As I explained in this article, Salesforce has gone through several naming changes and product re-brands of their Data Cloud. This Customer Data Platform license seems to have been the one issued when the platform was known as Salesforce CDP (Customer Data Platform).
For a detailed list of limits, guidelines and feature availability for this legacy license, use the following documentation link:
https://help.salesforce.com/s/articleView?id=data.c360_a_limits_and_guidelines_cdp.htm&type=5
If your org had this legacy license and has now migrated to the standard Data Cloud license, your admin will need to re-assign Salesforce Permission Sets. The Customer Data Platform Permission Sets no longer provide access to view and use Data Cloud in your org.
Check this official documentation link for more information:
https://help.salesforce.com/s/articleView?id=data.c360_a_license_update_perm_set_migration.htm&type=5
Data Cloud License
This is the standard Salesforce Data Cloud provisioning License. As explained in another guide, Salesforce Data Cloud is provisioned by default in your Salesforce home org. Purchasing this license activates the tool.
It includes:
- Core capabilities and features
- A base number of initial credit entitlement
- A base number of initial storage allocation
Data Cloud One Companion Org
This is the final type of license.
Data Cloud Companion Org is a recently added feature to Data Cloud. The main concept is that x1 Data Cloud Org acts like the home org where Data Cloud is provisioned (with a standard Data Cloud license) and then, on separate orgs, you can use this Data Cloud One Companion Org license so that those extra orgs act as “companions” that can connect to the home Data Cloud and share data, views, etc.
You cannot activate this license in an org where Data Cloud is already provisioned.
Please check this link for the official Salesforce documentation links on Data Cloud Editions and Licenses available:
https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&type=5
Check the following official link to learn more about what Data Cloud One is and how the Data Cloud One Companion license works:
https://help.salesforce.com/s/articleView?id=data.c360_a_data_cloud_one.htm&type=5
Salesforce Data Cloud Add-ons
The second component of your Salesforce Contract will be the Add-on Licenses you decide to include and purchase.
These are extra features you decide to include, paid yearly. At the time of writing this guide, these are the currently available add-ons for both a Production org and a Sandbox Org:
Add-on Licenses for Production Orgs
| Add-on Feature | Available in your account | Description |
|---|---|---|
| Data Spaces | No | You may purchase additional Data Space to partition your data into regions, brands, etc. |
| Segmentation & Activation | Yes | This allows you to create segments and batch activations. |
| Extra Storage Allocation | Yes | You may purchase additional storage on top of your initial allocation. |
| Private Connect for Data Cloud | Yes | This allows you to increase security by providing secured private connectivity with external systems. |
| Platform Encryption for Data Cloud | Yes | You may purchase this add-on to enable encryption of Data Cloud via customer-managed root keys. |
| Sub-Second Real-Time Profile and Entities | No | This feature allows you to leverage Real-Time in other features such as Data Graphs, Identity Resolution, Segments and other processes. |
| Advertising Audiences | Yes | You will need to purchase this add-on to be able to Activate segments to Advertising platforms such as Google Ads or META. |
| Data Cloud One Additional Connection | Yes | This add-on is an extra license to be able to connect other Data Cloud orgs to act as Companion orgs to your Data Cloud home org. The license must be added from your home org. |
Add-on Licenses for Sandbox Orgs
| Add-on Feature | Available in your account | Description |
|---|---|---|
| Data Cloud Sandbox - Data Storage | Yes | This add-on allows you to store data in Data Cloud in a sandbox. |
| Data Cloud Sandbox - Data Services Card | Yes | This, together with the Data Cloud Sandbox - Data Storage license, allows you to provision Data Cloud in a Sandbox Org and be able to use Data Services credits. |
| Data Cloud Sandbox - Segmentation & Activation | No | You need this add-on if you want to be able to segmentate and activate segments in a Sandbox Org. |
| Data Cloud Sandbox - Real-Time Profile & Entities | No | This add-on allows you to use Real-Time features such as Graphs, Profiles, etc. |
Please check this link for the official Salesforce documentation links on Data Cloud Add-ons:
https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&type=5
Salesforce Data Cloud Credits and Credit Consumption model
Credit Consumption Overview
First of all, as I explained, your core package contains an initial entitlement of credits and storage.
Then, you may purchase additional credits in packages, just like Supermessages or Contact packages work in Salesforce Marketing Cloud Engagement (SFMC).
The summary of how it works:
- Certain features and processes in Data Cloud consume credits, they are variable costs, based on usage.
- Salesforce calculates how many credits these actions consume based on a multiplier that the company has defined.
- The multiplier is applied per 1 million rows processed / queried / analyzed during that Data Cloud action or process.
The credit multiplier is applied and credits are consumed every single time that rows are processed / queried / analyzed, not only the first time you perform or configure that action.
Here are some examples:
#1
Action: ingest data (configure a Data Stream for the first time)
Multiplier: 400
Rows processed: 2.000.000
Total credits consumed: 800 credits (400 x 2)
#2
Action: run a Calculated Insight (first time you run it)
Multiplier: 1000
Rows processed: 15.000.000
Total credits consumed: 15.000 credits (1000 x 15)
#3
Action: the Calculated Insight is refreshed (runs again based on a schedule)
Multiplier: 1000
Rows Processed: 16.000.000 (data increased from last run)
Total credits consumed: 16.000 credits (1000 x 16)
Now, there are a lot of actions to monitor and calculate consumption for, each of them with a different multiplier, etc so this might become complex to track.
To help your Org with this monitoring and to simplify things, Salesforce:
- Groups these variable usage actions in categories or consumption cards
- Offers a free tool called Salesforce Digital Wallet so that you can monitor consumption in near-real-time for each category.
Credit Usage Category: Data Services Credits
This is the first group or type of credit consumption. Data Services includes the following Data Cloud actions:
- Data Ingestion
- Data Mapping
- Identity Resolution
- Calculated Insights
- Data Queries
- Streaming
- Unification
Basically, anything that has to do with processing data in Data Cloud.
Every time you configure a Data Stream, perform a query to access data, run a Calculated Insight, ingest data sources, unify, etc, you’re using credits of this group.
Credit Usage Category: Segmentation & Activation Credits
This is the second group of credit usage. It includes:
- Segmentation
- Activation
This means that every time you publish a segment or activate to an Activation Target, Data Cloud consumes credits.
Credit Usage Rate Cards
As explained before, Salesforce applies a different multiplier or credit rate card to each type of process, action or feature use in Data Cloud.
As this is a key aspect to consider when deploying Data Cloud in your organization, let’s look at it in detail over the next section.
Please check this link for the official Salesforce documentation links on Data Cloud Billable Usage Types:
https://help.salesforce.com/s/articleView?id=data.c360_a_data_usage_types.htm&type=5
Data Cloud Credit Usage Multipliers
The two tables below show the Data Cloud Credit Usage Multipliers for the 2 credit categories that the tool has: Data Services credits and Segmentation & Activation credits.
Data Services Credit Multipliers
| Data Cloud Service | Type | Credits Multiplier | Record Unit | Explanation / Example |
|---|---|---|---|---|
| External Data Pipeline | Batch | 2000 | Per 1 million rows processed | Structured Data Streams and Ingestion from all data sources and connectors except for structured data via Internal Data Pipeline. E.g: Data Streams from external sources such as SAP CRM, Amazon S3 files, etc. |
| External Data Pipeline | Streaming | 5000 | Per 1 million rows processed | Same as Batch External Data Pipeline, but for Streaming data streams or ingestion. E.g: Web SDK streaming data ingestion from a wordpress site. |
| Internal Data Pipeline | Batch | 500 | Per 1 million rows processed | Structured and Batch Data Streams and Ingestion from all native Salesforce data sources and connectors: Marketing Cloud connector, Salesforce CRM connector, Salesforce Commerce Cloud connector, Marketing Cloud Personalization connector. E.g: Data streams configured via starter bundle from your SFMC org, native connector. |
| Internal Data Pipeline | Streaming | 500 | Per 1 million rows processed | Structured and Streaming Data Streams and Ingestion from all native Salesforce data sources and connectors: Marketing Cloud connector, Salesforce CRM connector, Salesforce Commerce Cloud connector, Marketing Cloud Personalization connector. E.g: Streaming web SDK data stream from your Salesforce Commerce Cloud org. |
| Data Transforms | Batch | 400 | Per 1 million rows processed | Batch Data Transformations for DLOs and DMOs. E.g: Deduplication batch data transfroms on ingested DLOs. |
| Data Transforms | Streaming | 5000 | Per 1 million rows processed | Streaming Data Transformations, same as above but for near real-time transforms. |
| Data Federation or Sharing Rows Accessed | Zero Copy | 70 | Per 1 million rows processed | Structured Data Records returned from the external Data Deferation Datalake system. Shared rows returned to the external Datalake. E.g: Data Stream Ingesting zero copy data from Google BigQuery. |
| Data Share Rows Shared | N/A | 800 | Per 1 million rows shared | Data Rows new and updated processed in a Data Cloud Data Share. E.g: Creating a Data Share to share a Calculated Insight and its records with an external 3rd party. |
| Data Queries | N/A | 2 | Per 1 million rows processed | An SQL structured request for specific information and data from Data Cloud. E.g: Using Data Cloud Query Editor to run custom ad-hoc queries on your Data Cloud data. |
| Accelerated Data Queries | N/A | 2 | Per 1 million rows processed | E.g: Using Accelerated SQL Queries to access Data Cloud rows from CRM Analytics. |
| Unstructured Data Processed | Batch | 60 | Per 1 MegaByte (MB) Processed | Total processed file size of unstructured data sources (e.g: audio, video) into Data Cloud Vector Database, for vector search queries. E.g: Ingesting all your customer support call audio files so Agentforce agents can leverage that data in outputs. |
| Private Connect Data Processed | N/A | 500 | Per 1 GigaByte (GB) of data Processed | Total processed file size of data processed connected via Private Connect for Data Cloud. E.g: Connecting a data source from Snowflake using private connect. |
| Calculated Insights | Batch | 15 | Per 1 million rows processed | Total rows processed from all objects involved in running a Calculated Insight for each run, in batch. E.g: Creating and running a batch CI that leverages data from 3 Data Cloud objects. |
| Calculated Insights | Streaming | 800 | Per 1 million rows processed | Same as the above, but for Streaming calculated insights. E.g: Running a streaming CI every 24 hours. |
| Profile Unification | Batch | 100.000 | Per 1 million rows processed | Total number of source profiles processed by an Identity Resolution ruleset. After the first run, only the deltas (new and updated) profiles are counted towards credits. x1 Source Profile = x1 source profile and its related linked DMOs. E.g: We run IR on 1.000.000 source profiles (each with related records), so total credit usage is 100.000 |
| Real-Time Profile API | N/A | 900 | Per 1 million rows processed | Total rows processed when retrieving Profile data using the Real-Time Profile API via external 3rd parties. E.g: Your Wordpress site uses Profile API to retrieve Individual DMO data from Data Cloud. |
| Sub-second Real-Time Events | N/A | 70.000 | Per 1 million rows combining events, actions and API | Use of Sub-Second Real-Time Events such as real-time Identity Resolution, Real-Time Data Graphs, etc. Requires additional license payment for the add-on Sub-Second Real-Time Service Usage. |
| Inferences | N/A | 3500 | Per 1 million inferences | Inferences are the output of AI predictions in Salesforce, irrespective of whether the Predictive AI is native Einstein Studio AI or external BYOM (Bring Your Own Model). x1 Inference = x1 prediction and, optionally, x1 or more prescriptions and x1 or more top predictors. |
| Data Actions | Streaming | 800 | Per 1 million rows processed | Streaming data actions to act on data. |
Segmentation and Activation Credit Multipliers
| Data Cloud Service | Credits Multiplier | Record Unit |
|---|---|---|
| Segment Rows Processed | 20 | Per 1 million rows processed |
| Activation (batch, with or without related attributes) | 10 | Per 1 million rows processed |
| Activate DMO (streaming) | 1600 | Per 1 million rows processed |
Please always refer to your Salesforce Account Executive to request and confirm information about Editions, Licenses, Add-ons and Billing. This includes credits multipliers and rate cards, which might change in the future.
The Usage Rate Cards described above have been taken from the following 2 official links shared by Salesforce as of April 2025 (Data Services) and October 2024 (Segmentation and Activation):
Data Services Rate Card – April 2025
Segmentation and Activation Rate Card – October 2024
Please use the following official Salesforce link to view the most up to date rate cards and multipliers as provided on Salesforce website:
https://www.salesforce.com/data/rates/multipliers/
Salesforce Digital Wallet – Monitoring consumption
As you’ve seen, there is a lot to consider when calculating the credit consumption of your org.
For that reason, Salesforce recently released the Salesforce Digital Wallet application.
Salesforce Digital Wallet is a free Account Management tool to monitor usage of consumption-based Salesforce products. It allows you to see near real-time consumption so that you can keep an eye on overuse, spot usage patterns, plan credit package renewals, etc.
Let’s see how it works.
Salesforce Digital Wallet – Overview
The Salesforce Digital Wallet application is free and provisioned in your Salesforce home Org if you’re an Admin. There are 2 ways you can access it:
1) Consumption Cards app
- Go to your Salesforce Home Org App Launcher
- Type “Consumption Cards”
- Click on it and the app will launch
2) Your Account app
- Go to your Salesforce Home Org App Launcher
- Type “Your account”
- Click on it and from there, select the “View Consumption Cards” button
Digital Wallet Consumption Cards
Each Salesforce product that is consumption-based comes with a unit and what counts as usage. For instance, storage is measured in GB, and Data Services are counted with Data Cloud credits, as explained earlier.
The types of usage, grouped by Salesforce as usage types, are organised into what you will see as Consumption Cards in the Digital Wallet.
E.g:
Consumption Card #1
Usage Type: Data Services Credits
Consumption Card #2
Usage Type: Segmentation & Activation Credits
Consumption Card #3
Usage Type: Data Storage Allocation
For each of these cards, you can monitor:
- Contract details
- Total allocation of credits
- Start and End Date for entitlement expiration
- Consumption Insights: view consumption by date ranges, check multipliers applied, view bar charts for pattern analysis, etc.
Some of the Salesforce Products that are consumption-based and enabled for Salesforce Digital Wallet are:
- Agentforce
- Commerce Cloud Pay-As-You-Go
- Data Cloud
- Einstein Personalization
- Flex Credits
- Salesforce Messaging
For a full documentation and knowledge articles on how to use the Salesforce Digital Wallet, please visit the following official documentation link:
https://help.salesforce.com/s/articleView?id=xcloud.wallet_about.htm&type=5
Credit Usage Recommendations
Salesforce Data Cloud is a very recent product, and new changes, multipliers and considerations keep on being added with every new official release.
Also, it is important to note that Salesforce Data Cloud is an enterprise product, aimed at organizations with enough budget and strategy to drive a high ROI from it.
Having said that, here are some common sense considerations regarding Data Cloud Credit Consumption:
- Plan a conservative Data Strategy first
When it comes to consumption-based products, designing the right strategy, architecture and data modelling before any implementation work is key. Having the right consulting partner is a must here. You should consider aspects such as volume needed, frequency of data changes for your use cases, plan your data ingestion and modelling way in advance, consider credit multipliers and calculate estimations, take into account data profiling, integrations, etc. - Account for Data Processing Runs
As I said earlier in this guide, please take into account the fact that the credit multipliers are applied per X million rows processed each time that a process runs. Every refresh of Identity Resolution, every publishing of a segment, every refresh of a Calculated Insight, any change in a record in a DLO, etc. It all counts towards processing data and consuming credits. - Anticipate Identity Resolution risks
Identity Resolution is the most expensive credit multiplier by far (100.000 credits per 1 million rows processed). Carefully consider how often you will run IR, frequency needed depending on the Use Cases you’re designing, database volume, etc. Changing the rules in an Identity Resolution require a refresh, for example. - Use Case driven approach
Reverse engineer your Data Cloud implementation and configuration based on what Use Cases your org will design and deploy. E.g: perhaps you do not need all your historical data for a given Use Case, so why pay for additional rows in each Data Cloud process? - Water > Plumbing Pipes
As used in a popular Thomas Davenport metaphor when talking about technology and business alignment, what’s the use of highly complex and ellaborate plumbing pipes if no one is thinking of the water that will run through them. Water is Information here. Always remember that data is only valuable if you can drive a positive ROI from it. If not, do not ingest, connect, harmonize or process it. - Consider Volume Deltas
Delta incrementals can really add up to Data Cloud credit usage. Say you ingested 1.000.000 rows initially, and you expect to have a 10% daily incremental delta. Try to do the forecasting exercise to see how credit usage will develop over X months. Also, note that there are multiple Data Cloud processes that will use those new rows, not only ingestion (e.g: related Calculated Insights that query that DLO). - Pre-transform as much as possible
If your tech stack allows it, consider preparing the data before you even ingest it into Data Cloud. Your organization is already paying for X tools in the stack (e.g: a Data Warehouse), so try to leverage those as much as possible so that you do not have to run every single data process in Data Cloud with its corresponding credit usage.