If you have been searching for “Salesforce Data Cloud” and finding more recent results that mention “Data 360” instead, here is the short version. Salesforce rebranded Data Cloud to Data 360 at Dreamforce 2025. The product underneath the name is the same customer data platform you may already be evaluating – the brand position around it has changed substantially.
This guide covers what the rebrand means for eCommerce teams choosing a CDP in 2026, how Data 360 works, what it does that earlier CDPs could not, and how to prepare for a deployment. The way scandiweb frames it for clients is simple: the platform itself is mature, and the Agentforce 360 ecosystem around it is where most of the 2026 decisions actually live.
Overview
- Salesforce Data Cloud was rebranded to Data 360 at Dreamforce 2025 (October 14, 2025) as part of the wider Agentforce 360 platform shift.
- Data 360 is the only data engine native to the Salesforce platform – it ingests, unifies, segments, and activates customer data across Commerce Cloud, Marketing Cloud, Service Cloud, and Sales Cloud in real time.
- The CDP capabilities did not change with the rebrand. The strategic positioning did – Data 360 is now framed as the live context that fuels AI agents (Agentforce), not as a standalone customer data warehouse.
What is a customer data platform?
A customer data platform (CDP) is a system that ingests customer data from multiple sources, unifies that data into a single profile per person, and makes the unified profile available to downstream applications for segmentation, personalization, and analytics. Unlike a CRM (which stores known relationships and interactions) or a data warehouse (which stores historical data for analysis), a CDP is built to serve real-time customer-facing decisions across web, mobile, email, and service channels.
🚀 Quick takeaway
If your team can answer “what is this customer’s lifetime value, last touchpoint, and current intent” in under three seconds across every channel, you have a CDP. If it takes a SQL query or a screen share, you do not.
For a broader treatment of the CDP category, see scandiweb’s guide to customer data platforms for eCommerce.
What is Salesforce Data 360 (formerly Data Cloud)?
Salesforce Data 360 is the customer data platform built natively into the Salesforce ecosystem. It ingests customer data from any source – web events, mobile apps, transactional systems, marketing platforms, in-store POS, third-party data – and unifies it into a single real-time customer profile that every Salesforce cloud (Commerce, Marketing, Service, Sales) can act on. As of October 2025, it falls under the Agentforce 360 umbrella alongside Salesforce’s AI agent platform.
Why the rebrand from Data Cloud to Data 360
Salesforce has renamed this product five times. The lineage runs Customer 360 Audiences, Salesforce CDP, Marketing Cloud Customer Data Platform, Salesforce Genie, Salesforce Data Cloud, and now Data 360. The Dreamforce 2025 rebrand reflects a strategic shift. Salesforce no longer positions the product as a static data warehouse. The 2026 framing is “live context that fuels AI, automation, and decision-making across the enterprise” (per Apex Hours analysis of the rebrand announcement).
For evaluation teams, the rebrand changes nothing functional in the short term. The license, the data model, the integrations, and the segmentation tools work the same way they did under the Data Cloud name. What changes is the roadmap – every new feature in 2026 lands under the Agentforce 360 umbrella, which means AI-agent integration is now a built-in expectation, not an add-on.
🚀 Quick takeaway
Buyers evaluating “Salesforce Data Cloud” in 2026 are evaluating Data 360. The product is the same. Anyone selling against you on Data Cloud terminology is either using older marketing materials or trying to confuse the procurement conversation.
Why use Salesforce Data 360 for eCommerce?
Data 360 is the right CDP choice for eCommerce teams in three specific scenarios.
You already run on Salesforce Commerce Cloud, Marketing Cloud, or Service Cloud
The native integration is the headline benefit. Data 360 talks to other Salesforce clouds without third-party connectors, without ETL middleware, and without API latency. A unified customer profile created in Data 360 is immediately visible in Service Cloud (so agents see real-time context), in Marketing Cloud (so journey builders trigger on live behavior), and in Commerce Cloud (so storefronts personalize on the next page load). For teams already inside the Salesforce ecosystem, this removes the integration tax that an external CDP would charge.
You are running headless or composable commerce and need a real-time customer profile
Headless and composable architectures decouple the storefront from the backend, which means the customer profile cannot live on a monolithic platform. Data 360 acts as the live context layer that any frontend (Magento PWA, Shopify Hydrogen, custom React storefront) can query for personalization and segmentation. scandiweb’s own Läderach Salesforce Data Cloud deployment uses this pattern to unify online and in-store customer signals for the luxury chocolate brand.
You want to deploy AI agents (Agentforce) on top of the CDP
This is the Dreamforce 2025 thesis in operational form. Agentforce agents (sales assistants, service agents, marketing strategists) need live customer context to be useful. Data 360 is the data engine that gives them that context. If your 2026 roadmap includes any of Agentforce’s eCommerce-relevant agents, you are committing to Data 360 whether you call it a CDP decision or an AI decision. The same logic applies if you are building out the analytics layer underneath – scandiweb’s eCommerce data analytics practice threads Data 360 into the reporting stack so the CDP is not a black box to the analytics team.
What Data 360 actually does
| Capability | Practical use in eCommerce |
| Ingest raw data | Pull events from storefront, email, mobile app, POS, ad platforms, and third-party data providers into one place |
| Clean and transform data | Standardize formats, resolve duplicates, fill missing attributes from related sources |
| Map and model data | Apply the Customer 360 Data Model so attributes from different sources connect to one profile |
| Identify and unify profiles | Match anonymous web traffic to known customers via deterministic and probabilistic identity resolution |
| Segment and activate audiences | Build segments from the unified profile and push them into Marketing Cloud, Commerce Cloud, ad platforms, or any downstream channel in real time |
What is the Customer 360 Data Model?
The Customer 360 Data Model is the structural foundation underneath Data 360. It is the standardized schema that lets data from any source (CRM, ERP, web, mobile, POS) connect to a single customer profile. Without a shared model, every new data source would require custom mapping, and the integration would collapse under its own complexity within a year.
How the model handles fragmented data
Most enterprises have customer data scattered across five to fifteen systems – the CRM has contact records, the ERP has order history, the web platform has anonymous session data, the email tool has engagement signals, and the loyalty system has redemption activity. The Customer 360 Data Model provides standardized entities (Individual, Account, Order, Engagement, Loyalty Program Member) so that any source can map into them without bespoke ETL logic.
Components of the model
- Subject area: a logical grouping of related data objects (Sales, Service, Marketing, Loyalty, Commerce).
- Data stream: a single source feeding data into Data 360 (a web SDK, an S3 bucket, a Salesforce connector).
- Data Model Object (DMO): a structured grouping of data derived from streams and ready for use in segmentation, calculated insights, or activation.
🚀 Quick takeaway
The Customer 360 Data Model is the reason Data 360 deployments do not turn into multi-quarter data engineering projects. If you try to skip the standardized model and roll your own schema, you are buying Data 360 to use it like a data warehouse – which is the most expensive way to use it.
How to prepare for a Data 360 implementation
scandiweb runs every Data 360 (and previously Data Cloud) project through the same six preparation steps. The order matters, and skipping the first three is the most common cause of a deployment that ships on time but does not deliver value.
1. Define the business outcome before the technical scope
Data 360 is a means, not an end. The first conversation with stakeholders should answer one question: what decision becomes easier when the unified profile exists? “Personalize the homepage hero by RFM segment” is a usable answer. “Implement a CDP” is not. The technical scope flows from the business outcome.
2. Identify all stakeholders, not just the technical sponsors
Data 360 touches Marketing, Service, Sales, Commerce, Legal (data privacy), IT (integration), and Operations (loyalty, fulfillment). Missing one stakeholder typically surfaces three months into the project as a blocker. Identify them at kickoff, document their use cases, and confirm their availability for design review.
3. Inventory your data sources
List every system that holds customer data, the format it holds it in, and the cadence it can deliver it (real-time stream, hourly batch, nightly export). The integration approach for each source depends on this inventory. Real-time use cases (web personalization, service-agent context) require streaming sources – batch sources cannot drive them.
4. Decide identity resolution rules early
Identity resolution is the heart of every CDP deployment. Decide which attributes you trust as a match (email is high-trust, phone is medium-trust, first-last-name combinations are low-trust without a second factor) and which order you apply them. The rules you set here drive the unified profile quality for every downstream use case. See scandiweb’s deeper treatment of unifying data for omnichannel personalization.
5. Plan the activation channels
A CDP that ingests data without activating it is shelfware. Map every segment to a destination at design time. Marketing Cloud journeys, Commerce Cloud personalization rules, ad-platform audiences, service-agent context cards – each destination needs its own activation contract. For the loyalty-side activation in particular, scandiweb’s Loyalty Program Accelerator is the downstream surface that turns a Data 360 segment into a tiered reward.
6. Set evaluation criteria before go-live
The first 90 days after Data 360 go-live should run against pre-agreed KPIs. Typical examples: time to launch a new audience, share of personalized customer-facing surfaces, lift in repeat-purchase rate on personalized vs control segments, agent handle time with vs without the unified profile.
🚀 Quick takeaway
The data engineering work is the easier half of a Data 360 implementation. The harder half is stakeholder alignment, identity rules, and activation contracts. Budget 40% of the project for the data side and 60% for the operating-model side.
Salesforce Data 360 vs other CDPs in 2026
The CDP category has consolidated since the Salesforce-Evergage acquisition in 2020. In 2026 the meaningful competitors to Data 360 are Adobe Real-Time CDP, Tealium AudienceStream, Segment (Twilio), and Bloomreach Engagement. The decision is rarely about pure CDP capability – the differentiation lives in which adjacent ecosystem the buyer already runs.
- Choose Data 360 when you already run Salesforce Commerce, Marketing, or Service Cloud – the native integration eliminates the integration tax.
- Choose Adobe Real-Time CDP when your stack centers on Adobe Experience Manager, Adobe Analytics, or Adobe Commerce.
- Choose Tealium or Segment when you need a vendor-neutral CDP that talks to many ecosystems equally.
- Choose Bloomreach Engagement when personalization and search are your primary use cases and CDP is the supporting layer rather than the centerpiece.
For a deeper comparison of personalization tools that sit on top of any of these CDPs, see scandiweb’s 9 best website personalization tools.
🚀 Quick takeaway
The CDP shortlist in 2026 is short. If you already run Salesforce, Data 360 is the default. If you already run Adobe, Real-Time CDP is the default. The harder cases are vendor-neutral stacks where Tealium, Segment, or Bloomreach win on specific personalization or routing strengths.
Frequently asked questions
Is Salesforce Data Cloud the same as Data 360?
Yes. Salesforce rebranded Data Cloud to Data 360 at Dreamforce 2025 on October 14, 2025. The underlying product, license, integrations, and data model are the same. The rebrand reflects a strategic shift toward the Agentforce 360 platform, not a functional change in the CDP.
Is Salesforce Data 360 a CDP?
Yes. Data 360 (formerly Data Cloud) is a customer data platform built natively into the Salesforce ecosystem. It ingests, unifies, segments, and activates customer data across Salesforce clouds (Commerce, Marketing, Service, Sales) and external channels in real time.
How is Data 360 different from a CRM?
A CRM (like Salesforce Sales Cloud or Service Cloud) stores known customer relationships and interactions. A CDP like Data 360 unifies data from many sources – including the CRM – into a single real-time customer profile that downstream applications can act on. The CRM is one input to the CDP, not a replacement for it.
What does Salesforce Data 360 cost?
Salesforce does not publish standardized public pricing for Data 360. Pricing scales with the number of unified profiles, the volume of data ingested, and the activation destinations enabled. Enterprise deployments typically start in the low six figures annually, with implementation services running 1.5 to 3 times the first-year license. For an accurate quote, engage Salesforce or a partner with current pricing visibility.
How long does a Data 360 implementation take?
A focused Data 360 deployment with two to four data sources and one activation destination ships in 10 to 16 weeks. Enterprise deployments with five or more data sources, complex identity resolution rules, and multiple downstream Salesforce clouds run 4 to 9 months. The variable is rarely the CDP itself – it is the upstream data preparation and the downstream activation contracts.
Can I use Data 360 with non-Salesforce systems?
Yes. Data 360 ingests from any source (web SDKs, S3, Snowflake, BigQuery, Kafka streams, REST APIs) and activates to any destination (ad platforms, third-party email tools, custom storefronts). The native integration is the strongest advantage when you already run Salesforce, but Data 360 is not locked to the Salesforce stack.
What is the difference between Data 360 and Agentforce?
Data 360 is the customer data platform – the live data engine. Agentforce is the AI-agent platform built on top of that data engine. Agentforce agents use Data 360 as their source of truth for customer context. The two products are sold and licensed separately, but the 2026 product roadmap assumes you use them together.
About this guide
Maintained by the scandiweb data and analytics team. Reviewed by Alina Draichuk, Analytics Engineer.
Related reading from the scandiweb blog:
- What is CDP? Guide to customer data platforms for eCommerce
- Läderach Salesforce Data Cloud success story
- How to increase your eCommerce revenue with CDPs
- Unifying data for omnichannel retail personalization
- 9 best website personalization tools
If you are mapping Data 360 against the other CDPs on your shortlist, that comparison is worth doing with someone who has deployed it. Get in touch and we will walk through where Data 360 fits your Salesforce stack – and where it does not.
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