Data 360 (formerly Data Cloud) has been center stage of Salesforce’s product offerings; however, it cannot be denied that the tool has been under scrutiny for many issues, including high prices, failed implementations, and low adoption rates. It is no wonder many people ask: “How does Data 360 actually compare in terms of functionality with other customer data platforms (CDPs) in the market?”
This article will aim to answer exactly that by highlighting key attributes that make Data 360 a strong contender, without ignoring the other ways in which it is not, by comparing it with other popular CDPs in the market to help you understand the strengths and weaknesses of the platform itself in relation to similar tools.
CRM Data Ownership – Native Salesforce Integration
Perhaps the most obvious way Data 360 compares to other CDPs is its native integration with Salesforce products. While other CDPs in the market also offer out-of-the-box API integrations with various popular marketing and data vendors (including Salesforce), many are also reliant on having an established enterprise data warehouse/ data platform to house the bulk of their customer data for ingestion.
This ultimately creates a dependency on having a well-established data warehousing solution, which may not be the case for many businesses. In this way, Data 360 enables organizations that master their customer data mainly within Salesforce itself to have more ownership over their own data.
The native integration functionalities with Salesforce apps offer such as lower latency, easier maintenance, better compatibility with Salesforce workflows, and support for bi-directional activation and event or streaming (real-time) integrations. Moreover, Data 360 is built on/top of Salesforce’s infrastructure, meaning that the data model, metadata, permissions, and object relationships are intrinsically aligned with the Salesforce platform.
More Than a Customer Data Platform
While often described as a CDP, in reality, Data 360 goes beyond the traditional scope of the CDP, which is often more focused on marketing use cases, such as marketing audience and journey orchestration.
Unlike standalone CDPs that primarily unify data for segmentation and campaign activation, Data 360 functions as a hyperscale data engine that underpins the entire Salesforce ecosystem. Since it is natively integrated into the Salesforce metadata model, Data 360 harmonizes and activates data across Sales, Service, Marketing, and Commerce, ensuring that a “single source of truth” is available at every touchpoint.
This enables Data 360 to be used for more than just marketing use cases – it also enables sales reps to have more precise upsell opportunities by providing them with enriched customer profiles, purchase history, and calculated insights directly within Agentforce Sales (formerly Sales Cloud). It can also provide service agents access to behavioral data in Agentforce Service (formerly Service Cloud) to personalize resolutions and deflect cases more efficiently.
Enabling AI Across the Full CRM Stack
Moreover, with the introduction of Agentforce, Data 360 serves as the data engine that natively empowers CRM users beyond marketers to leverage AI to generate insights into directly actionable steps in opportunity management, case handling, and agent productivity. While other CDPs also offer AI-powered capabilities like predictive audiences or journey optimization, their activation usually stops at marketing or requires additional integrations to surface insights in sales and service workflows.
In this sense, Data 360 is not just another CDP – it is the backbone of Customer 360 for CRM, ensuring that data and AI flow seamlessly into every part of the Salesforce platform.
Over-Reliance on Data Modeling
This being said, one important distinction to make when comparing Data 360 with some other CDPs is the way data is ingested and modeled. Many leading CDPs offer schema-less or schema-flexible ingestion, meaning that raw event data can flow in with minimal modeling, which accelerates initial implementation and integrations, enabling organizations to begin using the tool almost immediately.
By contrast, Data 360 requires customer data to be mapped into its standardized Customer 360 Data Model before it can be used. While this normalized model provides long-term consistency across Salesforce applications, it introduces challenges in practice: implementations often take longer, making it less flexible when businesses need to adapt quickly to new data sources or evolving schemas, as every change must be reconciled with the normalized model. This additional complexity can make Data 360 less user-friendly for non-technical marketers or analysts compared to CDPs with lighter-weight ingestion pipelines.
In short, Data 360’s reliance on its standardized schema delivers strong alignment with the Salesforce ecosystem, but at the trade-off of slower onboarding and reduced agility compared to schema-less CDPs.
Total Costs of Ownership
Additionally, a recurring concern around Data 360 has been its price tag and total cost of ownership, particularly given its credit-based pricing model that can add up quickly, making experimentation costly and creating hesitation to scale usage. However, with recent announcements – including the introduction of Data 360 sandboxes for all editions, discounted credit consumption in sandbox environments, and free data ingestion via Salesforce native connectors – the cost burden of bringing CRM data into Data 360 has been reduced. These enhancements demonstrate a commitment to making Data 360 more cost-effective and easier to adopt at scale.
Final Thoughts
In conclusion, while Salesforce Data 360 (formerly Data Cloud) shares surface-level similarities with other CDPs, its true strength lies in being far more than a marketing activation tool. As a data engine embedded within the Salesforce platform, it enables marketing, service, and sales in ways that standalone CDPs cannot natively replicate.
That said, we can also not ignore how it may not compete with other CDP vendors in the market. Such as its reliance on a normalized schema and ongoing concerns around the cost of ownership.
Nevertheless, for businesses already invested in Salesforce and whose customer data mainly sits within Salesforce, Data 360 represents a strategic opportunity to unlock a true Customer 360 – where data, AI, and customer engagement converge seamlessly across every function across the full CRM stack.
Comments: