During 2023 and the beginning of 2024, I sensed a common theme in the ecosystem – a spark of curiosity about Salesforce Data Cloud. The users see the potential and power to unlock a whole new level of customer understanding. But when I speak with my clients about it, they all ask the same questions: “What kind of data does it take?”, “How can we actually use it?”, and the ever-present worry, “Isn’t this just adding another complex tool to our already overflowing toolbox?”.
That’s why I decided to write this post; a chance to demystify Data Cloud with real-world examples and answer the data question. We’ll ditch the technical jargon and focus on the “why” behind the tool, using a simple principle: a picture is worth a thousand words.
We’ll focus on a common marketing goal across many industries – super-targeted social media campaigns. Imagine unifying all your customer data – purchase history, website behavior, social media preferences – to craft social media campaigns tailored to specific customer needs.
Let’s move from brainstorming to action! We will consider the telecommunications industry for this specific use case. We will target heavy data users, specifically those who stream videos frequently on their mobile devices but are on low-data plans. Once we have them identified, we will target them in social media with a personalized campaign that incentivizes them to upgrade to a plan like “Mobile Data Gold”, which better suits their usage patterns.
Our Data Journey: From Source to Action
For this exercise, we’ll leverage five tables (Contacts, Contracts, Products, Payments, and Watch History) from two sources: Salesforce CRM and Amazon S3. The process involves these key steps:
- Connect: We’ll seamlessly ingest all five tables into the Data Cloud from both CRM and third-party cloud storage (Amazon S3).
- Harmonize: Data streams will be mapped to the Data Cloud’s unified model, ensuring consistency.
- Unify: Using advanced matching rules, we’ll create a single customer identity by consolidating data from various sources.
- Analyze: We’ll effortlessly leverage drag-and-drop functionality to create customer segments based on specific criteria.
- Act: The enriched customer data will then be activated and readily available for use in Meta campaigns.
1. Connect
Connecting the Dots: Data Ingestion Made Easy
To get started, navigate to the Data Stream tab within Data Cloud. This central hub provides a comprehensive overview of all connectable sources. Data Cloud boasts a vast array of native integrations. In the telecommunications industry, you can seamlessly ingest data from various sources, such as Salesforce CRM for contacts, SAP or Oracle for payments and contracts, and cloud platforms like AWS or Azure for watch history tracking.
Here, we’ll demonstrate how to establish a connection between Data Cloud, Salesforce Service Cloud, and Amazon Web Services (AWS) as a third-party tool.
Salesforce CRM
Here, we dive into the Data Stream tab and demonstrate how to connect Data Cloud to your Salesforce Service Cloud or Sales Cloud instance.
Third-Party Tool Data Ingestion
In this second video, we focus on how to connect Data Cloud to a third-party tool. For this example, we will use Amazon Web Services (AWS).
2. Harmonize
Once data is ingested into Data Cloud, it resides in the Data Lake. However, it’s not yet connected or usable. This is where data harmonization comes in. You can either map your data objects to the standard Data Cloud Model (Customer 360 Data Model) or create a custom model. This process essentially translates your data into a format Data Cloud can understand, allowing it to establish relationships between each table.
Shaping the Data: From Raw to Ready
Let’s explore an example of how to map fields from your Data Lake objects to the standard model. This will focus on data that aligns easily with the existing Customer 360 Data Model. For a comprehensive reference, you can access the full model details in Salesforce Help.
This approach highlights the specific task of mapping and clarifies its purpose in creating a match between your data and the standard model.
Beyond the Standard: Building Custom Models
Real-world data often requires flexibility. Data Cloud empowers you to create custom data model objects when your information doesn’t perfectly align with the standard model. Here, we’ll explore an example of how to build these custom models within Data Cloud.
Weaving the Web: Building Relationships Between Data
Once each Data Lake object is mapped to its corresponding Data Model object, it’s time to establish relationships between them. This creates a comprehensive data web, similar to a spider net, that connects all the information and unlocks the true value of your model.
3. Unify
Unveiling the Magic: Creating a Unified Customer View
Now that our data web is established, it’s time for the real magic – unifying all the information into a single customer profile. While the specifics might be hidden (like a magician’s secrets!), Data Cloud offers transparency in the unification process. You can even define your own custom rules to tailor how data is brought together. This level of control allows you to create a truly unified view of your customer.
4. Analyze
Turning Insights Into Action: Identifying High-Value Customers
With our unified customer profiles in place, it’s time to unlock their true potential. Imagine squeezing the juice from a lemon, but instead of just refreshment, we’re extracting valuable customer insights.
For our specific use case, In the telecommunications industry, this allows us to identify heavy data users who are currently on low data plans. This valuable information empowers us to create highly personalized messages, inviting them to upgrade their plans based on their actual usage patterns. And the best part? This entire process can be achieved through a user-friendly drag-and-drop functionality.
The beauty of this approach is that the segment you create can be dynamic. By setting up automatic refreshes every 12 or 24 hours, you ensure your target audience remains highly relevant and up-to-date. This translates to a consistently optimized recurrent audience for your campaigns.
5. Act
Taking Action: Reaching Your Audience on Meta
We’ve reached the final stage of our journey – activating our data! Now it’s time to leverage the power of Meta. Navigate to the Activation tab, click “New,” and seamlessly select the segment and desired Activation Target (e.g., Meta, Google) for your campaign. It’s that simple!
Within the New Activation window, the second step involves selecting the specific contact point for your segment. This could be an email address, phone number, or another relevant identifier. Additionally, assign a clear and descriptive name to your activation for easy reference later. With these details in place, you’re ready to launch your targeted campaign!
Conclusion: Unleashing the Power of Unified Data
We’ve explored the exciting journey of transforming raw data into actionable insights, focusing on how Data Cloud empowers you to connect, harmonize, and unify customer data from various sources, creating a powerful single customer view. This unified profile unlocks a treasure trove of possibilities, allowing you to identify high-value customers and personalize your marketing efforts.
We hope this use case has been insightful, helped you solve some doubts, and demonstrated the power of Data Cloud.
What use cases do you envision in your own industry? How can unified data empower your business? Share your comments below – we’d love to hear your ideas!