sf-agent-framework/sf-core/data/salesforce-cloud-data-models.md

AI Agent Orchestration Framework for Salesforce Development - Two-phase architecture with 70% context reduction

# Salesforce Cloud-Specific Data Models & Architecture (Summer '25)

## Overview

This document provides a comprehensive breakdown of data models, objects, and
architectural patterns specific to each Salesforce Cloud, updated for Summer '25
with Data Cloud Native integration.

## 🔷 Sales Cloud Data Model

### Core Objects

```yaml
sales_cloud_objects:
  Account:
    purpose: 'Company/Organization records'
    key_fields: [Name, Type, Industry, AnnualRevenue]
    relationships: [Contacts, Opportunities, Cases]

  Contact:
    purpose: 'Individual person records'
    key_fields: [FirstName, LastName, Email, Phone]
    relationships: [Account, Opportunities, Cases]

  Opportunity:
    purpose: 'Sales deals and revenue tracking'
    key_fields: [Name, Amount, CloseDate, StageName]
    relationships: [Account, Contact, OpportunityLineItems]

  Lead:
    purpose: 'Unqualified prospects'
    key_fields: [Name, Company, Email, Status]
    conversion: [Account, Contact, Opportunity]

  Quote:
    purpose: 'Formal pricing proposals'
    key_fields: [Name, ExpirationDate, Status, TotalPrice]
    relationships: [Opportunity, QuoteLineItems]
```

### Sales Cloud Specific Features

```yaml
einstein_features:
  - Opportunity Scoring
  - Lead Scoring
  - Account Insights
  - Email Insights
  - Activity Capture

sales_processes:
  - Lead Assignment Rules
  - Web-to-Lead
  - Lead Conversion Process
  - Opportunity Teams
  - Split Revenue
  - Forecasting
  - Territory Management 2.0
```

### Best Practices

1. **Lead Management**
   - Implement lead scoring with Einstein
   - Use assignment rules for distribution
   - Define clear conversion criteria
   - Track lead sources meticulously

2. **Opportunity Management**
   - Use Sales Path for guided selling
   - Implement validation rules for stages
   - Configure Products and Price Books
   - Enable collaborative forecasting

## 🔶 Service Cloud Data Model

### Core Objects

```yaml
service_cloud_objects:
  Case:
    purpose: 'Customer service requests'
    key_fields: [CaseNumber, Subject, Status, Priority]
    relationships: [Account, Contact, Asset]

  Asset:
    purpose: 'Products owned by customers'
    key_fields: [Name, SerialNumber, InstallDate, Status]
    relationships: [Account, Contact, Cases]

  Entitlement:
    purpose: 'Service contracts and SLAs'
    key_fields: [Name, StartDate, EndDate, Type]
    relationships: [Account, Asset, ServiceContract]

  ServiceContract:
    purpose: 'Service agreements'
    key_fields: [ContractNumber, StartDate, EndDate]
    relationships: [Account, Entitlements]

  Knowledge__kav:
    purpose: 'Knowledge base articles'
    key_fields: [Title, Summary, ArticleBody]
    features: [Versioning, Translation, Approval]
```

### Service Cloud Features

```yaml
service_features:
  - Omni-Channel Routing
  - Service Console
  - Knowledge Management
  - Live Agent Chat
  - Field Service Lightning
  - Einstein Case Classification
  - Einstein Article Recommendations

automation:
  - Auto-Response Rules
  - Assignment Rules
  - Escalation Rules
  - Milestone Tracking
  - Entitlement Process
```

### Service Agent Force Integration

```yaml
service_agents:
  - Customer Service Agent
  - Technical Support Agent
  - Field Service Agent
  - Knowledge Agent

capabilities:
  - Auto-resolve common issues
  - Suggest knowledge articles
  - Schedule appointments
  - Update case status
  - Escalate complex issues
```

## 🟣 Marketing Cloud Data Model

### Core Data Extensions

```yaml
marketing_cloud_de:
  Subscribers:
    purpose: 'Email subscriber list'
    key_fields: [SubscriberKey, EmailAddress, Status]

  Journey_Activity:
    purpose: 'Customer journey tracking'
    key_fields: [ContactKey, JourneyID, ActivityID]

  Email_Analytics:
    purpose: 'Email performance metrics'
    key_fields: [JobID, Opens, Clicks, Bounces]

  SMS_Subscribers:
    purpose: 'Mobile messaging contacts'
    key_fields: [MobileNumber, OptInStatus, Locale]
```

### Marketing Cloud Connect

```yaml
synchronized_objects:
  from_sales_cloud:
    - Lead
    - Contact
    - Account
    - Campaign
    - CampaignMember

  to_sales_cloud:
    - Email Send Results
    - Journey Status
    - Engagement Scores
```

### Einstein Features

```yaml
einstein_marketing:
  - Send Time Optimization
  - Content Selection
  - Engagement Frequency
  - Engagement Scoring
  - Copy Insights
  - Subject Line Testing
```

## 🟡 Commerce Cloud Data Model

### Core Entities

```yaml
commerce_objects:
  Product:
    purpose: 'Product catalog'
    fields: [SKU, Name, Price, Inventory]

  Category:
    purpose: 'Product organization'
    fields: [Name, ParentCategory, SortOrder]

  Customer:
    purpose: 'Shopper profiles'
    fields: [Email, FirstName, LastName]

  Order:
    purpose: 'Purchase transactions'
    fields: [OrderNumber, Total, Status]

  Cart:
    purpose: 'Shopping sessions'
    fields: [SessionID, Items, Subtotal]
```

### Commerce Cloud Features

```yaml
b2c_features:
  - Einstein Product Recommendations
  - Einstein Search Dictionaries
  - Dynamic Pricing
  - Inventory Management
  - Promotion Engine

b2b_features:
  - Contract Pricing
  - Quote Management
  - Approval Workflows
  - Reorder Capabilities
  - Account Hierarchies
```

## 📊 Analytics Cloud (Tableau CRM) Data Model

### Core Objects

```yaml
analytics_objects:
  Dataset:
    purpose: 'Data storage for analytics'
    types: [CSV, SFDC_Local, SFDC_Remote]

  Lens:
    purpose: 'Data exploration views'
    features: [Filters, Groups, Measures]

  Dashboard:
    purpose: 'Visual analytics'
    components: [Widgets, Filters, Layouts]

  Dataflow:
    purpose: 'ETL processes'
    nodes: [Extract, Transform, Load]
```

### Einstein Analytics Features

```yaml
einstein_analytics:
  - Smart Data Prep
  - Auto-generated Insights
  - Predictive Analytics
  - What-If Analysis
  - Natural Language Queries
  - Conversational Analytics
```

## 🌐 Experience Cloud Data Model

### Core Components

```yaml
experience_cloud:
  Network:
    purpose: 'Community container'
    fields: [Name, UrlPathPrefix, Status]

  NetworkMember:
    purpose: 'Community users'
    relationships: [User, Contact, Account]

  Topic:
    purpose: 'Content categorization'
    features: [Featured, Navigational]

  FeedItem:
    purpose: 'Community posts'
    types: [TextPost, ContentPost, PollPost]
```

### Experience Features

```yaml
community_features:
  - Custom Themes
  - Page Variations
  - Audience Targeting
  - CMS Connect
  - Knowledge Integration
  - Case Deflection
  - Peer-to-Peer Support
```

## 🔵 Platform & App Cloud Data Model

### Custom Object Framework

```yaml
custom_object_structure:
  naming: 'ObjectName__c'
  fields:
    custom: 'FieldName__c'
    standard: [CreatedBy, LastModifiedDate, OwnerId]

  relationships:
    lookup: 'RelatedObject__c'
    master_detail: 'Parent__c'
    junction: 'Object1__c + Object2__c'
```

### Platform Features

```yaml
platform_capabilities:
  - Custom Objects
  - Custom Apps
  - Lightning Platform
  - Apex Classes
  - Visualforce Pages
  - Lightning Web Components
  - Platform Events
  - Custom Metadata Types
```

## 🟢 Data Cloud Architecture (Summer '25)

### Unified Data Model

```yaml
data_cloud_objects:
  Individual:
    purpose: 'Unified person profile'
    sources: [CRM, Marketing, Commerce, Service]

  Unified_Event:
    purpose: 'Cross-system events'
    types: [Web, Mobile, Email, Transaction]

  Calculated_Insight:
    purpose: 'AI-derived metrics'
    examples: [CLV, ChurnRisk, NextBestAction]

  Segment:
    purpose: 'Dynamic audiences'
    activation: [Marketing, Sales, Service]
```

### Data Cloud Features

```yaml
native_capabilities:
  - Zero-copy architecture
  - Real-time streaming
  - Identity resolution
  - Calculated insights
  - Audience activation
  - Privacy compliance
  - Data spaces
```

## 🔄 Cross-Cloud Integration Patterns

### Integration Architecture

```yaml
integration_patterns:
  sales_to_service:
    - Case creation from Opportunity
    - Asset tracking from Orders
    - Entitlement from Contracts

  marketing_to_sales:
    - Lead scoring synchronization
    - Campaign influence tracking
    - Engagement history

  commerce_to_service:
    - Order to Case automation
    - Product registration
    - Warranty tracking

  platform_events:
    - Real-time data synchronization
    - Event-driven automation
    - Microservices communication
```

### Best Practices for Cross-Cloud

1. **Data Governance**
   - Single source of truth definition
   - Master data management
   - Duplicate prevention
   - Data quality rules

2. **Integration Strategy**
   - Use platform events for real-time
   - Batch for large volume sync
   - CDC for incremental updates
   - APIs for on-demand access

3. **Performance Optimization**
   - Selective field sync
   - Archival strategies
   - Caching patterns
   - Async processing

## 📈 Data Volume Considerations

### Large Data Volume (LDV) Patterns

```yaml
ldv_strategies:
  skinny_tables:
    when: 'Frequent queries on few fields'
    benefit: 'Faster query performance'

  custom_indexes:
    when: 'Specific query patterns'
    benefit: 'Optimized data retrieval'

  big_objects:
    when: 'Historical data storage'
    benefit: 'Cost-effective archival'

  external_objects:
    when: 'Data stays in external system'
    benefit: 'Real-time access without storage'
```

### Performance Guidelines

```yaml
performance_thresholds:
  standard_objects:
    optimal: '< 5 million records'
    careful: '5-10 million records'
    architect: '> 10 million records'

  custom_objects:
    optimal: '< 2 million records'
    careful: '2-5 million records'
    architect: '> 5 million records'
```

## 🔐 Security Model by Cloud

### Access Control Patterns

```yaml
security_layers:
  sales_cloud:
    - Role hierarchy
    - Sharing rules
    - Team selling
    - Territory management

  service_cloud:
    - Service territories
    - Skill-based routing
    - Article visibility
    - Portal access

  marketing_cloud:
    - Business units
    - User permissions
    - Data extensions access
    - Journey permissions

  platform:
    - Profiles
    - Permission sets
    - Custom permissions
    - Apex sharing
```

---

_This guide provides cloud-specific data model knowledge for SF-Agent SF-Agent
Framework agents. Updated for Summer '25 release._