Every system, one real-time profile of each customer
Data Cloud implemented to unify customer data from Salesforce, your warehouse, commerce, web and back office — resolved into one profile, segmented, activated and ready to ground your AI.
Customer data rarely lacks volume; it lacks agreement. Data Cloud gives every team the same answer to “who is this customer?” — and gives your AI agents a trustworthy place to find it.
From scattered records to one profile
The four areas every Data Cloud engagement covers, starting from the use cases worth paying for.
Data ingestion & zero-copy integration
Data streams from the Salesforce clouds, web and mobile, and connectors to other systems — plus zero-copy access to warehouses such as Snowflake, Databricks, BigQuery and Redshift, so data is used where it already lives.
Identity resolution & unified profiles
Match and reconciliation rules that recognize one person across emails, devices, accounts and systems, producing a unified profile every team can read.
Calculated insights & real-time segments
Lifetime value, propensity and engagement measures computed on the unified data, and segments that update as customers act.
Activation & AI grounding
Segments and insights sent to Marketing Cloud, advertising platforms and the CRM record — and the same data used to ground Agentforce answers in fact.
From use case to activated data
Choose the use cases
Start from outcomes — personalization, service context, agent grounding — because Data Cloud is priced on consumption and every data stream should earn its place.
Map sources and the data model
Which systems hold what, and how it maps to Data Cloud's data model objects.
Ingest and resolve
Data streams and zero-copy connections set up, and identity rules tuned against real records.
Build insights and segments
The calculated insights and segments the use cases need, validated with the teams that will use them.
Activate and monitor
Profiles and segments delivered to the systems that act on them, with consumption and data quality monitored from then on.
Where the data comes from, and where it goes
Data Cloud is only as complete as the systems feeding it, and only as useful as the ones it feeds.
- Sales, Service, Marketing and Commerce Cloud
- Snowflake, Databricks, Google BigQuery and Amazon Redshift
- Web and mobile behavioral data
- ERP and back-office systems, via MuleSoft or APIs
- Advertising platforms for audience activation
- Agentforce and Prompt Builder for grounding
Before you start
Do we have to copy our warehouse into Data Cloud?
No. Zero-copy integration lets Data Cloud work with supported warehouses in place, and share its results back to them, so you avoid a second copy and another pipeline to maintain.
How is Data Cloud priced?
On consumption — the data you process, store and activate. That is why we start from the use cases, and design streams and refresh schedules that keep consumption predictable.
Do we need Data Cloud for Agentforce?
Agents can answer from knowledge articles and records on their own. Grounding them in unified Data Cloud profiles is what lets them answer with a customer's full context rather than one system's view of it.
Keep reading
All 8 Salesforce products →Agentforce
AI agents for service, sales and operations — grounded in your data, given the actions they need and the boundaries they must not cross, and handing off to people when they should.
Read moreSellSales Cloud
Leads, accounts, opportunities, activities and sales operations brought into one connected Salesforce platform — built around how your team actually sells.
Read moreServeService Cloud
Case management, omni-channel routing, knowledge and field service — so every agent sees the whole customer, on every channel.
Read moreGrow faster than you ever imagined
Tell us which platform you are standing up, migrating off or trying to make behave. We will come back with the engineers, the model and a realistic sequence.