Salesforce Data Cloud vs. the CDP Market

Salesforce’s own customer data platform (CDP) could be considered a latecomer to the party. Previously going by different names, when the offering arrived in 2021, the CDP market had become saturated with established players like Segment, Tealium, Exponea, and Voyado. 

The rise of CDPs was spurred on by both the COVID-19 pandemic (the urgency for digital transformation projects) and the sunsetting of third-party cookies. By 2021, the CDP market had undergone segmentation, with some service providers targeting so-called enterprise-level customers, and others aiming at small and medium-sized businesses.

Despite being aware of the CDP market situation, Salesforce decided to enter the market with their own platform. Why did Salesforce decide to build, versus buy a suitable candidate, and integrate them into the Salesforce suite? After all, mergers and acquisitions had been a tried-and-true strategy for many years. This time was different, and I wondered why – right up until the second half of 2023. This was when Salesforce renamed the CDP “Data Cloud”, and shared its plans to incorporate Data Cloud with the core platform. With the introduction of many AI capabilities, the core platform became the Einstein 1 platform. 

Data Cloud: A Pivotal Year 

Leading up to the announcement, Data Cloud took leaps in terms of development throughout 2023. Salesforce literally poured data into research and development (R&D). 

However, before this point, Salesforce’s CDP was rough around the edges – to say the least. Salesforce CDP wasn’t matching its competitors in terms of performance, features, usability, or versatility. While it did have a strong company brand, community, and future roadmap going for it, to be honest, I believe that without Salesforce’s strategic shift and major developments to the platform’s capabilities in 2023, Data Cloud would have fallen short against competitors.

Now in 2024, Salesforce claims it is “the year of the Data Cloud”. But what does this mean for customers, partners, and competitors? I believe that we need to look past the marketing jargon and look at the features. Let’s look at the pros and cons of Data Cloud against other well-known CDPs in the market. 

Data Cloud’s Advantages

• Out-of-the-box integrations with the Salesforce platform and Einstein AI.
• Compatible with the standard Salesforce data model.
• Fully customisable data model (i.e. to include Salesforce custom objects).
• Ability to enrich Salesforce CRM records with data.
• Calculated insights.
• Visually represent your data model and data relationships.
• Robust identity resolution and profile unification.
• Compatible with Salesforce user permissions (i.e. Identity and Access Management).
• The first account-based CDP.
• Data Cloud-Triggered Flow to extend automation, using Salesforce’s primary process automation tool.

There’s plenty to like about Data Cloud. I feel that Salesforce did a decent job in setting up the data model mapping interface – it’s visual, intuitive, and functions in a drag-and-drop way. Furthermore, as Data Cloud is linked with Salesforce CRM, the out-of-the-box data sources to ingest data from Salesforce make getting started a breeze.

Having worked with several other CDPs in the past, the majority of Data Cloud’s merits come from its close linkage with the core platform. The focus is placed on ingesting, transforming data from the CRM, and then activating data to marketing automation or analytics platforms. 

Pushing insights to the CRM is generally not in the scope of a CDP, however, Data Cloud can do that effectively (a key differentiator). With the Winter ‘24 release, Data Cloud now supports showing Data Cloud data directly as fields and related lists within the Core Platform, enabling CRM users to benefit from the fabled “360° customer view”.

Talking of differentiators, Data Cloud is what I’d call an account-based CDP. In the Winter ‘24 release, Data Cloud also gained the ability to build unified account profiles, in addition to unified individuals. This is significant because CDPs have generally had a tough time handling account hierarchies and data relations (since everything has focused on the individual).

Data Cloud allows you to combine account-level insights from various systems, e.g. ERPs, PLMs, OMSs, and Salesforce CRM. Furthermore, with calculated insights and Data Cloud-triggered flows, you can fuel processes that would otherwise require complex and not scalable integrations.

Data Cloud’s Limitations 

• The segmentation interface can be challenging to use. 
• Lack of real-time data ingestion and activation.
• Data updates limited to once an hour.
• Cannot be used without the Salesforce core platform.
• Activation is executed on a separate platform.
• Content creation occurs on a separate UI/platform.
• Built-in analytic capabilities are limited.

When considering the wider CDP market, Data Cloud has some shortcomings. For one, I find the segmentation process and interface overly complicated. Even a marketer experienced in technology and data could struggle making sense of some aspects – including the ”segment on” choice, container paths, and the intricacies between DLOs, DMOs, and attributes. 

Once you manage to set up your desired segment, you then run into another hurdle: there are delays in data ingestion, and latency in data activation. Data Cloud’s less-than-real-time data handling can severely hamper your marketing efforts.

Perhaps the most obvious limitation is you cannot (and should not) use Data Cloud as a standalone solution or alongside other CRMs. And while it is safe to say that Data Cloud works well with the Salesforce core platform, its integration with other Salesforce products is not entirely seamless.

For example, triggering a marketing journey is a complex process from creating a segment, activating the segment, adding additional attributes, and then setting up an entry source in Journey Builder. There are plenty of CDPs out there that handle segmentation, personalization, engagement, and content all within the same UI – but unfortunately, Data Cloud isn’t one. However, Salesforce’s newest entry into the marketing automation family, Marketing Cloud Growth, promises to change all this.

Summary

Overall, I’d say that even with the limitations I’ve mentioned, Data Cloud is a solid choice as a customer data platform. I’d see it as a top choice in these scenarios:

• If you have a significant Salesforce footprint spanning several products (i.e. ‘clouds’ in the Salesforce suite (and possibly MuleSoft). 
• If you do business primarily in the B2B sphere and want to leverage the 360° account view features. 
• If you want a CDP that works just as well for sales and customer service, just like others do for marketing and commerce.