What Data Cloud actually is
Salesforce Data Cloud (previously marketed as Customer 360 / Data 360, and before that Genie) is Salesforce’s customer data platform. It ingests data from every system you own, resolves the same human being across all of them into a single unified profile, and then makes that profile available — in near real time — to everything else in your Salesforce estate.
That last part is what separates it from a standalone CDP. The unified profile is not sitting in a separate tool waiting to be exported. It is available directly to Sales Cloud, Service Cloud, Marketing Cloud and Agentforce, which is precisely why Marketing Cloud Next is built on top of it.
If you take one thing from this page: most of what companies call a marketing problem is a data problem wearing a costume. Fix the foundation and a surprising number of downstream problems stop existing.
Architecture and data modelling
Before a single record moves, somebody has to decide what a customer is in your business. A patient, a member, a household, an account with twelve contacts attached? Data Cloud gives you a modelling layer to express that, and getting it wrong is expensive to unwind later.
We map your source systems to Data Cloud’s data model — data streams, data lake objects, data model objects and calculated insights — against how your business actually operates rather than a reference diagram from a keynote.
From source system to activated audience
Ingestion and integration
Data Cloud is only as good as what you feed it. In practice that means a mixture of approaches, chosen per source rather than applied uniformly:
- Native Salesforce connectors for CRM, Marketing Cloud Engagement and Commerce data
- Zero-copy federation with Snowflake, BigQuery, Databricks and Redshift, so large datasets stay where they already live and stay governed by the team that owns them
- Web and mobile SDKs for behavioural events that never existed in a CRM record
- Ingestion APIs and MuleSoft for the systems that will never have a tidy connector
- Batch and streaming chosen per source, because not everything needs to be real time and paying for real time you do not use is a waste
Identity resolution and unified profiles
This is the part that earns the licence. Identity resolution decides which records refer to the same person and merges them into one profile, using rulesets you define and control.
The work is rarely technical — it is deciding what your business is comfortable with. Is a shared household email enough to merge two people? Is a fuzzy name and postcode match good enough for marketing but not for service? We build match and reconciliation rulesets that reflect those decisions, test them against your real data, and show you what merged and what did not before anything goes live.
| Before Data Cloud | After identity resolution |
|---|---|
| Four records for one customer across four systems | One unified profile, with every source still traceable |
| Marketing counts them as four contacts | Accurate audience sizes and honest reporting |
| Service sees only the case history in their system | Full picture at the point of contact |
| AI trained on contradictions | Agents answering from one consistent record |
Segmentation and activation
Once profiles are unified, segmentation gets dramatically easier — you are querying one clean object rather than reconciling four systems in a spreadsheet. Segments built in Data Cloud can be activated into Marketing Cloud journeys, advertising platforms, core CRM and Agentforce, and refresh on a schedule you choose.
We build segments that are maintainable: named clearly, documented, and owned by somebody on your team who understands them. A segment nobody can explain in six months is technical debt.
Governance, consent and trust
Unified data raises the stakes on consent. We implement consent and preference handling in the data model itself rather than bolting it onto individual campaigns, so a suppression means something everywhere. For regulated clients we set up the data spaces, field-level controls and audit trail their compliance team is going to ask about — ideally before they ask.
How it feeds MC Next and Agentforce
Data Cloud is the foundation of the Trifecta™ for a practical reason: the two layers above it are only as good as the profile underneath.
- Marketing Cloud Next is Data Cloud-native. Its audiences and personalization come from the unified profile, so a weak Data Cloud foundation caps what MC Next can ever do for you.
- Agentforce grounds its answers in the same profile. This is the difference between an agent that knows a customer’s history and one that confidently invents it.
How we run a Data Cloud engagement
A typical first phase, six to twelve weeks
Data Cloud questions we get asked
Is Data Cloud the same thing as a CDP?
Broadly yes, with an important difference. Data Cloud is Salesforce's customer data platform, but because it is native to the Salesforce platform it can make the unified profile available directly inside Sales Cloud, Service Cloud, Marketing Cloud and Agentforce rather than pushing exports between systems.
Do we need Data Cloud before Marketing Cloud Next?
Effectively yes. Marketing Cloud Next is built on Data Cloud rather than its own data model, so the quality of your Data Cloud foundation directly determines what MC Next can do for you. This is why we sequence data work first.
Can Data Cloud read our data warehouse without copying it?
In many cases yes. Zero-copy integration lets Data Cloud query data in Snowflake, BigQuery, Databricks and Redshift where it already lives, which avoids duplicating large datasets and the governance headaches that come with it.
How long does a Data Cloud implementation take?
A focused first phase - ingestion from your core systems, a working data model, identity resolution and one activation use case - typically runs six to twelve weeks. We would rather deliver one working use case quickly than boil the ocean.
What does identity resolution actually do?
It decides that jsmith@work.com, J. Smith on the phone list and the loyalty record ending 4471 are the same human being, and collapses them into one profile using rules you control. It is the single highest-value thing most organizations get out of Data Cloud.
Ready to make your customer data work as hard as you do?
Book a free 30-minute discovery call. We’ll look at where your Salesforce and your data stand today, and where the fastest wins are.
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