What Data 360 actually is
Salesforce Data 360 - called Data Cloud until its 2025 rename, and before that Genie and Salesforce CDP - is Salesforce’s customer data platform. Many teams still call it Data Cloud, and the two names refer to the same product, so if you are looking for a Salesforce Data Cloud consultant, this is the same work. 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 customer data platform. 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 modeling
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 360 gives you a modeling layer to express that, and getting it wrong is expensive to unwind later.
We map your source systems to Data 360’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 360 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 behavioral 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 license. Identity resolution, which most documentation still calls Data Cloud 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 ZIP code 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 360 | 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 360 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 360 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 360-native. Its audiences and personalization come from the unified profile, so a weak Data 360 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 360 engagement
Whether you call it a Data 360 project or a Salesforce Data Cloud implementation, it is led by a certified Salesforce Data 360 consultant and scoped around the one use case worth proving first. Licensing and credit consumption shape that scope too: what you ingest, how often segments refresh and how much has to run in real time all affect what the platform costs to run, so we design for the volume you actually need.
A typical first phase, six to twelve weeks
Data 360 questions we get asked
What is Data 360?
Data 360, Salesforce's customer data platform, brings customer data from all of your systems into one unified profile and makes that profile available across Sales Cloud, Service Cloud, Marketing Cloud and Agentforce. It was called Data Cloud until its 2025 rename.
Is Data 360 the same as Data Cloud?
Yes. Salesforce renamed Data Cloud to Data 360, and it is the same platform with the same capabilities. Older documentation, job posts and RFPs still use the Data Cloud name, so a request for Salesforce Data Cloud consulting is a request for exactly this work.
Is Data 360 the same thing as a CDP?
Broadly yes, with an important difference. Data 360 (formerly 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 360 before Marketing Cloud Next?
Marketing Cloud Next is built on Data 360 rather than its own data model, so you will need it, and its quality shapes what MC Next can do for you. How much data work has to come first depends on your data and your use cases, which is what an assessment establishes.
Can Data 360 read our data warehouse without copying it?
In many cases yes. Zero-copy integration lets Data 360 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 360 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 [email protected], 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 often the most valuable part of a Data 360 implementation.
Ready to make your customer data work as hard as you do?
Request a free 30-minute discovery call. Suggest three times that suit you and Paula confirms one. We’ll look at where your Salesforce and your data stand today, and where the fastest wins are.
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