This is the question we field more than any other on data projects, and it deserves a straight answer before the nuance: yes, Salesforce Data Cloud is a CDP. It also does more than a classic CDP, which is where most of the confusion comes from. And since October 2025 it has a different name, which hasn't helped either.
The short version: Data Cloud is a CDP — it resolves identities into unified profiles, segments on them, and activates them downstream. It is now called Salesforce Data 360. The product didn't change; the label did. Where it differs from a marketing CDP is scope: those profiles serve sales, service, commerce, analytics, and Agentforce agents, not just the marketing team.
Below: what the rename actually means for you, what the platform does, how it stacks up against Adobe Real-Time CDP and Segment, where a data lake or warehouse still earns its place, and what the March 2026 pricing overhaul changed. All of it from implementation work rather than datasheets.
First, the name: Data Cloud is now Data 360
At Dreamforce on 13 October 2025, Salesforce renamed Data Cloud to Salesforce Data 360 and folded it under the Agentforce 360 umbrella. If you are searching for one name and finding documentation under the other, that is why. Nothing in your org changed — same data model, same licences, same setup screens. Two capabilities did arrive alongside the rename: Tableau Semantics, which standardises metric definitions so agents and dashboards agree on what “active customer” means, and Intelligent Context, which lets agents read unstructured content like PDFs.
For the record, this is the sixth name the product has carried since 2020: Customer 360 Audiences, then Salesforce CDP, then Marketing Cloud Customer Data Platform, then Genie, then Data Cloud, now Data 360. We mention it not to be snide but because it has a practical cost — half the blog posts and Trailhead modules you will find still use an older name, and vendors quote you against different ones. When you get a proposal, check which era the terminology comes from.
We use “Data 360” from here on, and note the old name where it helps.
What Salesforce Data 360 actually does
Data 360 is Salesforce's real-time data platform. It ingests from every channel — commerce, service, marketing, POS, loyalty, web behaviour — resolves identities into unified customer profiles, and makes those profiles usable inside every Salesforce cloud while the customer is still in the session.
The four jobs it does:
- Unification: identity resolution across every source into one profile
- Segmentation: real-time audience building on unified data
- Activation: pushing segments and signals into Marketing Cloud, Commerce Cloud, Service Cloud, and Agentforce
- Grounding: giving AI agents live customer context to act on, which is the job the Agentforce 360 roadmap is built around
Those first three are the textbook definition of a CDP, which settles the question. The fourth is what a marketing CDP generally does not give you, and it is the reason the “is it really a CDP” argument keeps going. Analysts who define a CDP narrowly — as a marketing tool for building audiences and pushing them to channels — are working from a definition Data 360 outgrew.
Data 360 vs standalone CDPs (Adobe, Segment, Insider)
| Salesforce Data 360 | Standalone CDP | |
|---|---|---|
| Integration with CRM | Native — zero-copy into Salesforce clouds | Connector-based, always syncing |
| Time to first activation | Faster if you run Salesforce | Faster if your stack is heterogeneous |
| Identity resolution | Built in, rules + AI | Varies widely by vendor |
| Real-time triggers | Native events into Flow & Agentforce | Webhooks / reverse ETL |
| AI activation | Direct fuel for Agentforce agents | Depends on integrations |
| Pricing model | Three options since March 2026: flex credits, per-profile, or an enterprise agreement | Typically volume-based contracts |
| Best when | Salesforce is your system of engagement | You are platform-agnostic by design |
The pattern we see in real projects: if Salesforce is already your system of engagement — commerce, service, marketing — a standalone CDP adds an integration layer you will spend the next three years maintaining. If your stack is genuinely multi-platform and Salesforce is one tool among many, a neutral CDP can be the right call.
CDP vs data lake vs data warehouse
This comes up in almost every discovery call, usually phrased as “we already have Snowflake, why would we need this too?” It is a fair challenge, and the answer is that they are built to answer different questions.
A warehouse or lake answers analytical questions for people: what happened last quarter, and which cohort drove it? A CDP answers one operational question for systems: who is this customer, and what should happen next? The second question has a deadline — the answer is worthless if it arrives after the shopper has left. That deadline, not the storage, is the real dividing line.
| Data lake | Data warehouse | CDP / Data 360 | |
|---|---|---|---|
| Holds | Raw everything, schema on read | Modelled, governed tables | Unified customer profiles |
| Answers | Anything, eventually | Known business questions | Who is this person, right now |
| Latency | Batch | Batch to near-real-time | Real-time |
| Serves | Data scientists | Analysts and execs | Channels, agents, and automations |
| Identity resolution | You build it | You build it | Built in |
| Fails at | Governance and speed | Sub-second personalisation | Cheap long-horizon storage |
So it is rarely either/or. Most mature teams run both, and the interesting development is that they no longer have to copy data between them. Data 360's zero-copy federation queries tables that stay in Snowflake, Databricks, BigQuery, or Redshift where they already live. Salesforce reported that of the 32 trillion records Data Cloud ingested in Q3 FY2026, 15 trillion came through zero-copy connectors rather than being duplicated — a pattern that barely existed three years ago.
In practice this is the architecture we recommend most often: the warehouse stays the system of record for history and analytics, Data 360 federates what it needs for identity and activation, and nobody maintains a nightly sync job that silently breaks in December.
What the March 2026 pricing change means
Cost unpredictability was the single most common complaint about Data Cloud, and it was justified — teams could not forecast a bill that moved with every ingestion job. Salesforce restructured the model effective March 2026. Three things are worth knowing before you build a business case.
- There are now three ways to buy: flex credits (pay per operation, around $500 per 100,000 credits), per-profile pricing (a fixed tier that covers unlimited operations for that profile count), or an enterprise agreement for multi-business-unit rollouts
- Batch ingestion moved to zero cost — you pay when data is used, not when it arrives, which removes the perverse incentive to under-ingest
- Volume tiers step the rate down hard as usage grows, so the unit economics of a pilot look nothing like the unit economics at scale — model both
There is no forced migration, so if you are already on the old Data Services credit model you can stay there. Whether you should depends on your ingestion-to-activation ratio — orgs that ingest heavily and activate lightly generally win by moving. Treat the figures above as the shape of the model rather than a quote; consumption pricing moves, and your rep will have the current rate card.
Where it earns its keep — and where it doesn't
Clear wins, from projects we have delivered:
- Real-time personalisation in Commerce Cloud — recommendations that reflect what the shopper did five minutes ago rather than last week
- Service agents seeing full commerce and marketing history without an integration layer in between
- Segments built once and activated across email, ads, onsite, and support instead of rebuilt per channel
- Agentforce agents grounded in live customer context, which is the difference between an agent that resolves a case and one that guesses
- Zero-copy federation retiring the nightly-sync architecture and the on-call rota that came with it
Cases where we have told clients not to buy it:
- Salesforce is a minor system in the stack and the real customer record lives elsewhere — you would be paying for native depth you cannot use
- The underlying data quality is poor. Identity resolution amplifies bad data rather than fixing it, and a cleanup project is the cheaper first step
- There is no owner for segmentation. Without someone accountable for audience strategy, it becomes an expensive place to store duplicate records
- The actual requirement is reporting. If nobody needs to act on a profile inside a live session, a warehouse and a BI tool will do the job for less
The bottom line
Data 360 is a CDP, and then some. What it trades away is vendor neutrality; what it buys is native depth inside the platform your revenue already runs through. If that describes your stack, the trade is usually worth it. If it doesn't, evaluate it honestly against Adobe Real-Time CDP or Segment rather than assuming the Salesforce answer because you are already a Salesforce shop. We have recommended both ways.
Weighing Data 360 for your stack? Talk to our Salesforce architects — or see our Salesforce Commerce Cloud services.
Deciding between Data 360 and a CDP?
Tell us what you are trying to activate and where the data lives now. We will tell you whether Data 360 is the right buy, or whether you already have what you need.
Four fields, no call required. We reply within one business day.
Frequently asked questions
Is Salesforce Data Cloud a CDP?
Yes. It does the three things that define a customer data platform — identity resolution into unified profiles, segmentation on that unified data, and activation into downstream channels. It also goes past a classic marketing CDP, because those same profiles are available to sales, service, commerce, analytics, and Agentforce agents rather than to marketing alone.
Is Data 360 the same as Data Cloud?
Yes, it is the same product. Salesforce renamed Data Cloud to Data 360 at Dreamforce on 14 October 2025, when it moved under the Agentforce 360 umbrella. Your existing org, data model, and licences did not change with the rename. It is the sixth name the product has carried since 2020, after Customer 360 Audiences, Salesforce CDP, Marketing Cloud Customer Data Platform, Salesforce Genie, and Data Cloud.
What is the difference between a CDP and a data warehouse or data lake?
A warehouse or lake stores large volumes cheaply and answers analytical questions for analysts, usually in batch. A CDP answers one operational question in real time — who is this customer, and what should happen next — and pushes that answer into a channel. They are complements, not substitutes. Most mature teams run both, and zero-copy federation means the data no longer has to be duplicated between them.
How does Salesforce Data 360 compare to Adobe Real-Time CDP or Segment?
Data 360 trades vendor neutrality for native depth. If your sales, service, and commerce already run on Salesforce, it activates faster and skips an integration layer you would otherwise maintain for years. If your stack is genuinely multi-platform and Salesforce is one tool among several, a neutral CDP such as Adobe Real-Time CDP or Segment is a fair and often better choice.