Dreamforce 2024 made one thing very clear: transitioning to Data Cloud is no longer optional for organizations using Salesforce. The power of Data Cloud lies in its ability to serve as the backbone for customer data, providing a unified and accessible view across platforms. With this capability, Salesforce users can achieve more precise segmentation, efficient data handling, and real-time insights, making it a game-changer for Marketing Cloud users looking to leverage data at scale.
While implementing Marketing Cloud on Core might be an eventual necessity, the immediate focus for most teams should be shifting away from Marketing Cloud Connect and moving toward Data Cloud as a single source of truth for customer segments. This transition enables Salesforce Core and Marketing Cloud Engagement to function in greater harmony, unlocking new levels of personalization and engagement with customers.
Transitioning from Marketing Cloud Connect to Data Cloud: What to Expect
For teams currently relying on Marketing Cloud Connect, this shift may seem daunting. If you’re in this situation, you’ve likely built numerous automations in Marketing Cloud Engagement, many of which depend on SQL queries pulling data from synchronized data extensions, Salesforce data entry events, and distributed marketing workflows. Moving to Data Cloud means reconfiguring these established workflows to interact with an entirely different data source. This shift impacts data structure, segmentation strategies, and automation logic, and requires a strategic, thoughtful approach.
The question then becomes: how do you begin this migration effectively? The transition to Data Cloud calls for a series of decisions around data organization, integration setup, and automation adjustments. I’m navigating this transition myself and will be sharing insights, challenges, and solutions on this blog over the coming months.
Data Quality and the Problem of Duplicates
One of the first areas to consider in this transition is data quality, specifically how to manage duplicate records. As any Salesforce admin knows, maintaining clean data is critical, but the need for this becomes even more urgent when Data Cloud is involved. So, what does it mean to have duplicates in Salesforce Core when Data Cloud is the new data source?
In Sales Cloud, duplicates have historically created issues for Marketing Cloud users. With Marketing Cloud Connect, for instance, any duplicate contact records in Sales Cloud result in multiple contacts being created in Marketing Cloud. This duplication inflates your contact count, which directly increases costs as Salesforce charges based on the total number of contacts. In such cases, you have a few options. You can accept the higher cost of retaining these duplicates, which can escalate over time, or you can pay a developer to write a script that prunes duplicates in Marketing Cloud.
Data Cloud offers some solutions for managing duplicate records through its profile unification features, but these also come at a cost. Data Cloud operates under a consumption-based pricing model, meaning you’re billed for resources used in real-time profile unification and data processing. While this model enables powerful data processing capabilities, it also means that every duplicate costs money in terms of both processing power and storage.
In short, addressing duplicates early is crucial. Data unification has financial implications in Data Cloud, so it’s wise to implement a deduplication strategy in Salesforce Core before you fully transition. Deduplication tools, manual merge processes, and regular data audits can help you reduce costs and ensure that Data Cloud has clean data to work with, optimizing your use of its resources.
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