Metadata Type: PricingRecipe
PricingRecipe is a metadata type in Salesforce Revenue Cloud that represents a predefined or custom pricing model used by the pricing data store during both design time and runtime. It defines how products, price dimensions, and pricing strategies are packaged for execution in CPQ and other pricing engines.
Overview
The PricingRecipe metadata type enables administrators and developers to define and deploy modular pricing models via the Metadata API. It outlines the data models or collections of objects (such as product rate plans, pricing rules, and charge definitions) that the pricing engine consumes to calculate prices accurately across quotes and orders :contentReference[oaicite:0]{index=0}.
Key Features
- Definition of pricing data models and recipe structures
- Support for bundling product‑related pricing components
- Integration with the Salesforce Revenue Cloud pricing engine
- Deployable via Metadata API for CI/CD and version control
Structure and Components
A PricingRecipe typically includes the following elements:
- Recipe Name: Unique identifier for the pricing recipe metadata
- Product Models: Collections of rate plans, pricing rules, and charges
- Data Model References: Links to product, pricing, and charge objects used in calculations
- Configuration Parameters: Settings that determine how pricing calculations are applied
Deployment Considerations
When deploying PricingRecipe metadata, pay attention to these factors:
1. Dependency Management
Ensure all referenced product rate plans, pricing rules, and related metadata exist and are included in the deployment package to prevent broken references.
2. API Compatibility
Use a Metadata API version that supports Salesforce Revenue Cloud pricing types to ensure PricingRecipe is recognized and properly handled.
3. Payload Size & Complexity
PricingRecipe definitions can be extensive. Monitor Metadata API payload limits and consider splitting complex recipes into multiple, modular components.
4. Permissions
Deploying user needs proper access to CPQ, Revenue Cloud, and Metadata API to avoid permission errors during deployment.
5. Consistency with Runtime Data
Verify that the deployed recipe aligns with runtime pricing schema and engine expectations to ensure accurate price calculations.
Best Practices for Salesforce Administrators
1. Document Recipe Intent and Structure
Record the purpose, applicable products, and key pricing rules of each PricingRecipe to facilitate ongoing maintenance and audits.
2. Use Version Control
Maintain PricingRecipe XML files in a version control system (e.g., Git) to track changes, collaborate, and enable clean rollbacks.
3. Modular Deployment
Group related recipes and dependent objects in deployment packages to minimize missing-component issues and simplify deployments.
4. Sandbox Testing
Test PricingRecipe deployments in sandbox environments to validate reference integrity, pricing accuracy, and engine integration before production rollout.
5. Monitor Engine Performance
Review pricing calculation performance after deployment and optimize recipes by refining rule complexity or data model structures as needed.
6. Collaborate with Stakeholders
Work closely with pricing analysts and CPQ teams to ensure recipes reflect business pricing strategies and correctly calculate quotes.
7. Maintain Dependency Documentation
Track which product models, pricing rules, and data components each recipe uses. This helps during debugging, upgrades, or scaling.
8. Audit Recipes Regularly
Periodically review PricingRecipe configurations to remove unused recipes and update obsolete pricing models in line with business changes.
9. Log Errors and Outcomes
Capture deployment and runtime errors related to pricing recipes and integrate logging into your deployment pipelines or monitoring tools.
10. Train Team Members
Ensure team members understand the structure, deployment process, and purpose of PricingRecipe metadata to maintain consistency and accuracy.
Conclusion
PricingRecipe metadata enables Salesforce administrators and developers to define, version-control, and deploy pricing models for Revenue Cloud programmatically. By following best practices—such as modular deployments, sandbox validation, documentation, and stakeholder collaboration—you can ensure pricing is configured accurately and maintained effectively across environments.