Over the past month, the Merkle team has collaborated with Salesforce to run multiple workshops about best practices for deploying Salesforce Data Cloud. These sessions have been compelling and fun opportunities to work with clients across many industries. We’re seeing more clients go live with Data Cloud to solve various use cases, and I wanted to share some key learnings from the first half of 2024.
?One of the first lessons learned is the importance of clear, well-defined use cases. Before diving into the technical aspects of deploying Salesforce Data Cloud, it's essential to understand what you aim to achieve. Are you looking to enhance customer segmentation, improve sales forecasting, or streamline marketing efforts? Defining your use cases helps align the deployment strategy with business objectives, ensuring the implementation delivers tangible value. Without clear use cases, you risk deploying features that may not address your organization's needs, leading to wasted resources and missed opportunities. Use case development might sound obvious, but I'm surprised how often this is skipped due to the distraction of shiny new technology.
?Use the Data You Already Have
?Another critical lesson is the importance of leveraging the data you already have. It's tempting to think you need new data sources or additional data points to make the most of Salesforce Data Cloud. However, the data you need is often already at your disposal, albeit in silos or underutilized. Conduct a thorough audit of your existing data assets and identify how it can be integrated into the Data Cloud. This speeds up the deployment process and maximizes the return on your existing data investments. Starting with familiar data helps validate the system's performance and accuracy before scaling up, giving you a solid foundation upon which to build.
?Your Data Engineers Are Key
?The importance of data engineers in deploying Salesforce Data Cloud cannot be overstated. They are the linchpins who bridge the gap between raw data and actionable insights. Their expertise in data integration, transformation, and pipeline management is crucial for a successful deployment. In my experience, involving data engineers early and often in the deployment process ensures the system is built on a solid foundation. They bring invaluable insights into data structure, quality, and optimization, which are critical for the smooth functioning of the Data Cloud. Moreover, their problem-solving skills are essential when troubleshooting any issues during deployment.
?Identity Resolution is Vital
?Identity resolution is another vital piece to the Data Cloud implementation puzzle that deserves special attention. Customers interact with businesses across various touchpoints across multi-channels, leading to fragmented data. Salesforce Data Cloud's identity resolution capabilities are designed to unify these disparate data points into a single customer view. However, achieving this requires meticulous planning and execution. Establish identity resolution rules that are robust and comprehensive to link data from sources accurately. This not only enhances data quality but also enables more personalized and effective customer engagements.??
?Merkle's Merkury can play a crucial role in your Salesforce Data Cloud deployment. It's built on a reference-based model of billions of customer interaction points, curating 268 million unique individuals with confidence scores to ensure high-quality data. Think of this as your CRM of everyone that you can build from! The best part is that Merkury is built into the Salesforce ecosystem and can be seamlessly integrated into Data Cloud, enhancing your data quality and customer insights.
?Use AI to Make Informed Decisions
One of the most thrilling outcomes of deploying Salesforce Data Cloud is the potential to enable AI-driven insights. Once the data is centralized and cleaned, you can harness Salesforce's powerful AI tools to uncover patterns, predict trends, and drive more intelligent business decisions. For instance, AI can help to identify high-value customers, forecasting sales, and optimizing marketing campaigns. The synergy between clean, unified data and advanced AI capabilities can propel your organization to new heights of efficiency and innovation.
Deploying Salesforce Data Cloud is a transformative journey that requires careful planning, skilled execution, and continuous optimization. By focusing on well-defined use cases, leveraging existing data, involving data engineers, prioritizing identity resolution, and embracing AI enablement, you can unlock the full potential of this powerful platform. The lessons learned from this deployment will streamline your data strategy and drive significant business growth. Reach out to the Merkle team here if you have any questions.
