Leveraging Salesforce Data Cloud with Marketing Cloud empowers your marketing campaigns by providing a “real-time” Customer 360 View.
Marketing Cloud is the industry leader for offering personalized messaging at scale. This article discusses the benefits of using Marketing Cloud with Data Cloud.
For context, Marketing Cloud has historically built market segments after importing customer data through daily warehouse file drops or through synchronizing Salesforce data directly. A key issue faced is structuring a data architecture to prevent duplicates and to ensure data is current. To address these issues, Salesforce introduced Data Cloud as an evolutionary product to harmonize data sources in real-time with a unified data model.
After integrating, the Salesforce CRM will be able to unify data from various sources and to activate the most impactful next steps with the customer.
CMLS can help achieve Data Cloud advantages:
1. Unify Customer Data
Use Data Cloud to create a Customer 360 View by integrating data from multiple sources like CRM, e-commerce, social media, and offline interactions. This allows marketing and all teams to break down silos and centralize data, ensuring a unified customer profile.
Review this link to see the over 270 Data Cloud connectors available at this time. After discussing nine (9) of the advantages of Data Cloud, this article walks through a customer use case with Amazon S3 connector.
2. Real-Time Data Processing
Marketing Cloud can leverage real-time (sub-second) data from the Data Cloud for timely campaign activations. Specifically, marketing may trigger campaigns based on live data inputs, such as abandoned carts, recent purchases, or web/app activity.
Through a short number of steps that are not too technical, one can rapidly publish a segment from Data Cloud into Marketing Cloud for an email and/or SMS journey. This link shows just how simple.
3. AI-Powered Insights
Combine the predictive analytics and machine learning capabilities of the Data Cloud with Marketing Cloud’s tools. Use AI to uncover insights like purchase predictions, churn likelihood, or audience segmentation.
After Data Cloud is integrated and data unified, insights can be created in just a few steps out of box. This trailhead link walks through how to create calculated insights for different industry cases.
4. Segmentation and Targeting
Create granular audience segments in the Data Cloud and push these segments into Marketing Cloud for targeted campaigns. Use dynamic data to continuously refine segments for better engagement.
Though not too technical, segmentation logic can quickly become complicated; one must set up the mapping effectively to maximize Data Cloud’s filtering capabilities. This trailhead link covers the process for creating segments, but we are here to consult/help as you need.
5. Personalization at Scale
Deliver personalized content by syncing data from the Data Cloud to Marketing Cloud’s content personalization tools. Tailor messaging, offers, and recommendations to individual preferences. For marketing teams now using Generative AI (GenAI), the more data the better to learn the best messaging to apply individually.
Data Cloud syncs with Marketing Cloud through Data Extensions (DE). DEs are used not only for the message audience but also for personalizing that message with meaningful data for the individual (first name, sender’s name, previous product purchases). See email screenshot for a simple personalization example.
6. Omnichannel Orchestration
Use Marketing Cloud’s Journey Builder to create omnichannel experiences. Key advantage of omnichannel is the same data is known across channels to make customer interaction seamless as they move from web to email to phone. Leverage Data Cloud’s insights to determine the best channel (email, SMS, social, etc.) and timing for each interaction.
The journey below is an example of using two channels based off Data Cloud’s harmonization of data. This journey also shows an example of an A/B test using Path Optimizer.
7. Compliance and Security
Ensure the data being shared between platforms complies with privacy laws like GDPR, CCPA, and others. Use the Data Cloud to manage customer consent and preferences effectively.
Data Cloud Consent Package has evolved beyond the traditional preference center to include tighter controls for addressing the ever evolving privacy laws. Setting it up involves a few steps, and we can assist.
8. Closed-Loop Analytics
Integrate feedback loops: track campaign outcomes in Marketing Cloud and send performance data back to the Data Cloud for refining models and strategies.
Measure ROI by connecting customer actions to marketing initiatives. The traditional campaign object of Salesforce can be used to bundle these actions and also use for opportunity/revenue attribution (measuring business impact).
9. Scalable Integrations
Use APIs and connectors to integrate the Data Cloud and Marketing Cloud seamlessly. Ensure the infrastructure is scalable to accommodate growing data volumes and complexity.
Out of the box connectors as discussed in item 2 are designed to help companies load data from various DB warehouses such as Amazon, Azure, DataBricks, IBM, Oracle, SAP, Snowflake, etc.
In closing, Harmonizing and unifying the data into the Customer 360 View creates scalable advantages for companies who have customer data streaming from multiple sources.
Use Case: Personalized Email Campaign for E-commerce with Amazon S3
Scenario:
An e-commerce retailer wants to create a personalized email campaign targeting customers who have browsed specific product categories but haven’t completed purchases. They use Amazon S3 to store raw customer interaction data from their website and app.
Implementation Steps:
1. Data Ingestion and Storage in S3:
Website and app interaction logs (e.g., product views, searches, and add-to-cart events) are streamed to an Amazon S3 bucket in real time.
These logs include details such as: Customer IDs, Product categories viewed, Timestamps, Device/browser details
2. Integration with Data Cloud:
The raw data in S3 is ingested into Salesforce Data Cloud using data streams via the S3 Connector into a Data Lake inside Data Cloud for segmentations, activations and insights.
Note that during data ingesting, Data Cloud may also clean/transform these source data in real-time with Streaming Data Transforms. The connector will target an S3 Data Lake Object (DLO) for storage inside Data Cloud
Data Cloud architecture then allows this DLO source data to be mapped to Data Model Objects (DMOs), which are basically structured views of the source data which allow the unified customer profile for precise segmentation.
3. Segmentation in Data Cloud:
Data Cloud uses the unified customer profiles to create dynamic segments with a Customer 360 View. For example: Customers who viewed products in the “Electronics” category within the last 7 days but didn’t complete a purchase.
The segments are updated in real time using the live feed from S3.
4. Sync with Marketing Cloud:
A significant benefit for companies that also use Marketing Cloud is that Data Cloud syncs the segmented audiences and their personalization data directly to Data Extensions and Omnichannel journeys using the native Connector.
With S3 connected to Data Cloud, now Key attributes (e.g., preferred products, last interaction) are mapped for personalization.
5. Campaign Execution in Marketing Cloud:
Use Journey Builder to design an automated email campaign:
Day 1: Send a personalized email featuring the product category the customer browsed.
Day 3: If no response, send a reminder with a discount offer.
Day 5: Highlight similar products or recommendations.
Content personalization is achieved by dynamically pulling customer attributes synced from the data cloud.
6. Advanced Analytics and Optimization:
Use data stored in S3 and processed in the data cloud to run advanced analytics, such as: ROI calculations, Predictive modeling for customer lifetime value (CLV), Identifying high-value customers for exclusive campaigns.
Summarizing the benefits of this S3 Integration with Data Cloud exemplifies the why.
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- Scalability: S3 handles vast amounts of raw data cost-effectively.
- Real-Time Personalization: Dynamic updates ensure campaigns are timely and relevant.
- Enhanced Analytics: The data cloud aggregates insights for better decision-making.
- Seamless Orchestration: Marketing Cloud ensures smooth execution across multiple channels.