Data Cloud acts as a unified customer data platform, bringing together CRM data, e-commerce behavior, service history, and external sources into a single, harmonized profile. It supports real-time insights and calculated metrics like customer lifetime value and churn propensity.
Marketing Cloud Engagement then leverages this rich, centralized data to drive highly targeted cross-channel campaigns via email, SMS, mobile push, and advertising platforms. Together, they turn raw data into engaging, personalized customer journeys.
This article explores how an established solution like Marketing Cloud Engagement works together with Data Cloud, and what the current state of Data Cloud is when it comes to marketing automation. We’ll also explore how the long-awaited updates for Marketing Cloud Engagement ended up in a different platform altogether.
The Features We Expected in MCE But Found in Data Cloud
Segmentation
Drag-and-drop segmentation in Marketing Cloud Engagement (MCE) had been one of those long-standing wishlist items. For anyone new to the platform, it came as a bit of a shock to realize that “real” segmentation required knowing SQL. That usually meant either bringing in external consultants or layering on third-party tools – neither of which was ideal for a marketing team trying to move fast.
The need for a no-code, intuitive way to segment audiences had been talked about for years. And while many of us hoped it would land in MCE eventually, it never really did. Of course, we remember Audience Builder, but for the sake of this article, we’re focusing on the core functionality of the platform itself without mentioning add-ons.
Then came Data Cloud.
Right from the start, Data Cloud positioned segmentation as a core feature and delivered on it. For MCE users, it was a bit of a mixed feeling: Salesforce heard the feedback, but instead of building it into MCE, they rolled it out in a completely different product. Still, the logic became clear: let Data Cloud handle data management and unification, while MCE focuses on campaign orchestration and delivery.
So what did we finally get, and what makes it different?
Data Cloud lets you build dynamic, highly targeted segments based on a full, unified customer view. You’re no longer limited to basic demographics or standard engagement data. Now you can segment using:
- Demographics: Age, location, gender, and more.
- Behavioral Data: Website visits, email clicks, app usage, purchase history, abandoned carts, service cases (all unified from your connected sources).
- Calculated Insights: CLV, RFM scores, engagement levels, or product affinity calculated directly in Data Cloud.
- Consent and Preferences: Easily filter based on opt-ins, channel preferences, and communication rules.
Segment types include:
- Standard Segments: Based on fixed criteria
- Real-Time Segments: Updated dynamically as data changes
- Einstein Lookalike Segments: AI-powered audiences that resemble your high-value customers
Best of all? You can build everything visually using a drag-and-drop interface. For more advanced use cases, SQL formulas are still an option, but the drag-and-drop experience has been significantly elevated in Data Cloud.
Einstein Segment AI: Segmentation via Natural Language
One of the most exciting innovations in segmentation is Einstein Segment AI, Salesforce’s generative AI tool. Instead of clicking through filters or writing code, marketers can now type a natural-language request like: “Create a segment of females interested in outdoor activities.”
Einstein will generate a draft segment, which you can review and fine-tune before use. It’s still important to verify the results, but this feature cuts down significantly on the time and effort needed to build segments.
Adding AI to the mix can be a real game-changer, especially for marketers who aren’t as technical but should still use it carefully to ensure your data is accurate and current.
Waterfall Segmentation: Exclusive Prioritized Targeting
Waterfall Segmentation, a feature many marketers hoped would arrive in MCE, was never implemented there. Now, it’s available in Salesforce Data Cloud in pilot testing mode and requires enablement by Salesforce. Even in pilot, it’s already a big step toward making advanced segmentation more accessible.
This feature allows you to assign customers to only one segment at a time, based on a defined priority order. Once a customer qualifies for a higher-priority segment, they’re excluded from all lower ones, helping reduce fatigue and ensuring the most relevant message is delivered.
You can build waterfall segments visually using drag-and-drop or Einstein AI, then activate each subsegment independently.
Use case: A retailer runs three campaigns:
- Segment A: VIP customers with high lifetime value.
- Segment B: Recent purchasers.
- Segment C: Newsletter subscribers with no recent engagement.
A VIP customer would be placed in Segment A and excluded from B and C automatically.
This targeting model ensures smarter resource allocation, better customer experience, and less message fatigue, which is a capability that MCE users had long needed but could previously only achieve with custom logic and manual workarounds.
Engagement Frequency Monitoring: Smarter Outreach Limits
In MCE, Einstein Engagement Frequency (EEF) helps analyze each contact’s email activity, like sends, opens, clicks, and unsubscribes over the past 90 days, as well as recommending an ideal send frequency.
This helps identify oversaturated and undersaturated subscribers. However, it’s limited to email and doesn’t provide a holistic, cross-channel view, nor does it predict churn risk.
Data Cloud takes this to the next level with :
- Calculated Insights and Predictive Modeling: Define or import AI predictions (like churn risk) and tie them to frequency triggers.
- Unified Multi-Channel Tracking: Monitor engagement across all touchpoints like email, web, app, purchase, service, and unify them into one customer profile.
- Automated Actions: Use insights to segment, suppress, or activate customers across channels, ensuring outreach is timely and relevant.
Data Activation
Data Cloud isn’t just about managing data – it also acts as a central activation hub, instantly connecting your segments to a broad range of destinations, including:
- Marketing Cloud Engagement (email, SMS, journeys).
- Google Ads and Meta (Facebook, Instagram).
- WhatsApp, a newly added native mobile messaging channel.
- Custom platforms via API integrations.
This means your segments can be activated in real-time across multiple marketing touchpoints, not just email or SMS, like in MCE.
The result? More consistent and personalized engagement across your entire ecosystem.
Final Thoughts
Some of the features now available in Data Cloud are likely the ones you were hoping would eventually land in Marketing Cloud Engagement. Whether due to shifting priorities or the fact that MCE isn’t a core Salesforce platform, those features were never fully realized. For years, marketers worked around these gaps, hiring MCE specialists or relying on third-party tools from AppExchange.
Now, it’s clearer than ever: Data Cloud and MCE are built to work together. When combined, they unlock the full 360° customer view and marketing automation capabilities we’ve all been waiting for.
We hope this article helped you understand how these platforms connect and how using them together can make marketing not only more powerful but a little less stressful, too.
