Build Your Data Cloud Usage Strategy
Summary
Data Cloud introduces challenges around managing and optimizing usage-based credits within the Salesforce ecosystem. The key is to align usage strategy with business priorities by quantifying the value of different use cases and balancing cost and benefits through KPIs and stakeholder input. Building clear roadmaps for both technical and business teams helps sequence features and monitor credit consumption over time. Incorporating usage governance ensures efficient credit spending with controls, monitoring, and ROI tracking. This approach enables architects to deliver high-value, sustainable Data Cloud implementations that align tech spend with business goals.
Takeaways
- Prioritize Data Cloud use cases based on measurable KPIs and stakeholder input.
- Develop dual roadmaps—business and technical—to align usage and credit planning.
- Embed usage considerations into governance via approval workflows and access controls.
- Regularly monitor credit consumption with dashboards and audit trails.
- Calculate and review ROI of credit usage to ensure value-driven investments.
Credit: iStock Data Cloud presents a new and interesting challenge for architects working in the Salesforce ecosystem: How do we consider and design for usage-based products in our solutions? We want to architect the best possible solution for our stakeholders, while making it clear to those same stakeholders that they are getting optimal value from their investment. According to the Well-Architected framework,“ strategy in architecture means systems are thoughtfully planned and delivered. It means delivery and maintenance teams have a clear view of the work to be done today and in the future, and everyone is aligned around the “why” of the work to be done. It means urgent requests can be triaged effectively and efficiently, and stakeholders can clearly understand the impacts and trade-offs of requests.” This post will walkthrough how to leverage the basics of a well-architected approach to strategy, and apply those principles to credit usage patterns in Data Cloud.