Marketers / Analytics / Data Cloud / Marketing Cloud

What is Salesforce Data Cloud? Data Cloud vs Salesforce CDP

By Lucy Mazalon

Announced at Dreamforce ’22, Salesforce Genie was declared the greatest Salesforce innovation in the company’s history. Now known as Data Cloud, it ingests and stores real-time data streams at massive scale, and combines it with Salesforce data. This paves the way for highly personalized customer experiences.

“Isn’t this what Data Cloud (Salesforce CDP) does?” I hear you asking. Unifying versions of the same individual across applications, delivering customer experiences based on data sources beyond Salesforce?

Data Cloud shares the same purpose and benefits that CDPs deliver – however Data Cloud is not the same as the technology that was formerly Salesforce CDP.

Data Cloud takes CDP’s capabilities, and extends the benefits right across the “Customer 360” (i.e. Salesforce’s product portfolio). That’s the data unification, identity resolution, and activation that Salesforce CDP customers have already been taking advantage of.

“With [Data Cloud], we moved the real-time data capabilities into the [Salesforce] platform so we can ingest, manage and activate data from anywhere. It’s also nested with Einstein for AI and Flow for automation.” Eric Stahl, EVP Marketing, Salesforce

Salesforce CDP is very much still “alive and kicking”, and there are several key differences between it and Data Cloud that we’ll clear up in this guide.

READ MORE: How Salesforce Uses Salesforce CDP (“Genie”)

What Does Data Cloud Do?

Data Cloud (Salesforce CDP) has been the fastest-growing, organically-grown product Salesforce has ever brought to market. To understand the vision for Data Cloud, it’s best to understand the foundation of what CDPs do.

Here’s what Salesforce CDP has been providing:

  • Build a single source of truth/create a unified customer profile across all touchpoints,
  • Match data to a person: To build unified profiles with advanced data linking capabilities, eg. fuzzy matching,
  • Bring all your data under one roof: Unify data from anywhere with a high-scale data ingestion service (plus MuleSoft’s industry-leading APIs),
  • Make every interaction relevant to the customer by connecting marketing to sales, service, commerce, and more.

If you consider a typical customer, they are leaving a data trail behind. We can split this data into two pots:

  • ‘Engagement’ data, as in, how they interact with your marketing journeys, adverts, mobile apps, even what they purchased in-store.
  • From the engagement data, Salesforce CDP generates ‘insight’ data, such as the won revenue from that customer organization, purchase intent, and privacy management.

This handful of examples only scratches the surface; consider the world’s leading enterprises and how many data points they are tasked with aggregating, from platforms such as AWS, or eCommerce platforms.

The guide below explains how CDP is used practically, in more depth:

READ MORE: Complete Guide to Customer Data Platforms (and Salesforce CDP)

Data Cloud vs. Salesforce CDP: The Differences

Data Cloud takes Salesforce CDP’s capabilities, and extends the benefits right across the “Customer 360” (i.e. Salesforce’s product portfolio). That’s the data unification, identity resolution, and activation that Salesforce CDP customers have already been taking advantage of.

From our research, we’ve narrowed down the key differences as follows:

Marketing Cloud Customer Data Platform (formerly Salesforce CDP) Data Cloud
Use CasesMarketing segmentation and “activation”For the entire Salesforce product suite (sales, service, marketing, etc.)
Data Unification, Identity Resolution
Enhanced Segmentation*X
Segment Activation*X
Flow AutomationX
Einstein AI (Next Best Action)X
Requires HyperforceX
Zero-copy ArchitectureX
Bring Your Own AIX
Integration with MuleSoft
Integration with Tableau

*Related to Marketing Cloud’s product suite.

1. Target Use Cases

While both CDP and Data Cloud handle data unification and identity resolution (i.e. matching up disparate data about the same individual, intelligently deduplicating data), there are differences in how they are meant to be used within organizations:

  • Salesforce CDP: A Marketing Cloud product designed for audience segmentation and “activation”. This means that with their segment, marketers can kick-start campaigns (across multiple channels), or run Einstein optimization tools that recommend engagement tactics.

“The big pivot for Salesforce is that customer data isn’t just in marketing systems. It’s also not just used by marketers. Customer data is spread across dozens (or hundreds, or thousands) of systems run by sales, service, marketing, commerce, finance, IT and more.” Eric Stahl, EVP Marketing, Salesforce

  • Data Cloud: Data Cloud spans the whole Salesforce platform (Customer 360). Data is collated from all data sources your organization has, and can be used to drive any action, interaction, or insight across sales, service, marketing, commerce, MuleSoft, Tableau and more.

2. Enhanced Segmentation & Segment Activation

Data Cloud opens up a world of use cases. Following on from the previous point, it’s important to clarify how the data will be used – in other words, “activated”.

It’s not just about the segmentation. Activation is crucial – as in, activating personalized engagement across marketing, sales, service, commerce, etc. – in a way that’s efficient. Traditionally, marketers would need to do ‘heavy lifting’ afterward to activate segmentation in a meaningful way. Segmentation + activation is what differentiates Marketing Cloud CDP from its competitors in this crowded market.

Salesforce CDP gives users the ability to query data and build complex audience segments with ease (designed for non-technical users). The segment builder suggests values that surface new attributes and lets users easily enhance, replicate, and share previous segments to speed up their work. This can then be injected into Journey Builder.

On the other hand, Data Cloud is designed for a wider range of activation uses – for Salesforce users to absorb information (see image below), to trigger Flow automation, or to inform the Einstein Next Best Action engine.

“[Data Cloud] opens up a world of use cases. You can access data from anywhere with native connectors, third-party plug-ins, or MuleSoft. You can build segments with Cases, Opportunities, abandoned shopping carts, license utilization, and more. You can build custom Workflows and AI models. You can active segments on your website, email, chat and paid media. You can send Slack alerts to your sales, service, marketing or other employees. You do deep analytics on the data with Tableau.” Eric Stahl, EVP Marketing, Salesforce

3. Underlying Architecture

Salesforce CDP has a direct link to the Marketing Cloud product suite. Data Cloud works with all Salesforce Customer 360 products, sending data into multiple “cloud” products:

Out-of-the-box connectivity is something that Salesforce are keenly aware needs to be the default. In reality, Marketing Cloud, CDP, Datorama, and Salesforce aren’t a seamless toolset; between some of the tools listed above, customers resort to developing custom integrations.

Salesforce’s internal Digital Experiences team have been “eating their own dog food” and implementing their own products. Throughout the process, they’ve been feeding back integration sticking points to the product teams – likely some of these improvements have already made their way into the GA product.

READ MORE: How Salesforce Uses Salesforce CDP (“Genie”)

4. Zero-copy Architecture

Zero-data copy architecture means that Data Cloud can directly access data stored in data lakes (and vice-versa) without moving or duplicating data. In other words, data can be fetched on-demand without having to store it all somewhere on the Salesforce platform.

The Salesforce Genie launch (now Data Cloud) brought zero-data copy architecture and Bring Your Own Lake (BYOL) technology with Snowflake, a highly popular data lake.

READ MORE: Snowflake: The Hottest Data Lake for Salesforce

5. Bring Your Own AI

Data Cloud has open data capabilities, so you can “bring your own” AI. SageMaker, Amazon’s cloud machine learning platform, can be used directly with Salesforce’s AI engine, Einstein – for example, to use models built in SageMaker with Einstein Prediction Builder or Einstein Discovery.

Overall, Data Cloud promises to have more extensibility capabilities than Salesforce CDP had.

6. MuleSoft and Tableau Integrations

Salesforce CDP offers the following integrations with MuleSoft and Tableau:

  • MuleSoft “Data from Anywhere”: Enables marketers to securely connect to any external app and data source, such as ERP, loyalty, and point of sale systems, to build a comprehensive view of the customer.
  • Tableau (the world’s leading analytics platform): Visualize, understand and explore customer data at a deeper level. Calculated Insights further enrich unified profiles with calculated metrics such as customer lifetime value and engagement scores.

Data Cloud offers this, at a higher level of functionality.

The Origins of Data Cloud (Salesforce CDP)

Salesforce knew that to remain competitive, Marketing Cloud needed to extend beyond its own four walls. The volume of data, and the number of data points consumers are generating proliferated over the past decade, and martech innovation accelerated to supersede traditional marketing automation.

The origins of Salesforce CDP can be traced back to late 2016, with Salesforce’s acquisition of Krux, rebranded as Salesforce DMP. The investment paid off, as Salesforce DMP was crowned a market leader less than one year later.

Above: Salesforce DMP post-acquisition, the CDP in its infancy.

Salesforce CDP began its pilot autumn 2019, which essentially swallowed up Salesforce DMP. CDPs (customer data platforms) go beyond DMPs (data management platforms) with a broader range of use cases; DMPs are associated with aggregating engagement data related to digital advertising.

Since then, other smart acquisitions Salesforce made – Datorama, MuleSoft, Tableau, Evergage (now Interaction Studio) – have all contributed to bolstering out Salesforce CDP’s offering to what it is today…

Above: a dashboard with CDP data, in Datorama.
READ MORE: How Salesforce Uses Salesforce CDP (“Genie”)

Summary

Data Cloud shares the purpose and benefits that CDPs deliver – but goes beyond the traditional definition of CDP:

  • Beyond marketing use cases: CDPs are typically targeted at marketers. Data Cloud unifies data for use across all Customer 360 products, and therefore, the plethora of use cases every department will have.
  • Faster: With a zero-data copy architecture, instead of syncing data to records (i.e. duplicating it), Data Cloud can “read” data sources without moving or duplicating data into Salesforce. You could think of this as a new generation of integrations. This speeds up the whole process – after all, milliseconds matter!

Salesforce Data Cloud is not a replacement for formerly Salesforce CDP – you will still be able to purchase, and use, Salesforce CDP. No doubt that there’s plenty on the horizon for Data Cloud, arguably Salesforce’s hottest product.

READ MORE: The History and Future of Salesforce Data Cloud

The Author

Lucy Mazalon

Lucy is the Operations Director at Salesforce Ben. She is a 10x certified Marketing Champion and founder of The DRIP.

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