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GET
/
stores
/
{store_id}
/
menu-rules
/
{rule_id}
Get Menu Rules by ID
curl --request GET \
  --url 'https://api.example.com/stores/{{store_id}}/menu-rules/{{rule_id}}'
{
  "rule": {},
  "execution_status": {},
  "execution_history": [
    {}
  ],
  "impact_analysis": {}
}
This endpoint provides comprehensive details about a specific menu rule, enabling detailed analysis, troubleshooting, and optimization of individual rule configurations and their business impact.
Individual rule retrieval provides deep insights into rule behavior, execution patterns, and business impact, supporting data-driven optimization and troubleshooting of menu automation logic.

​
Path Parameters

​
store_id
string
required
The unique identifier of the store containing the menu rule
​
rule_id
string
required
The unique identifier of the menu rule to retrieve

​
Query Parameters

​
include_history
boolean
default:"false"
Include rule execution history and performance metrics
​
include_impact_analysis
boolean
default:"false"
Include business impact analysis and effectiveness metrics
​
date_range
string
Date range for historical data (format: YYYY-MM-DD,YYYY-MM-DD)

​
Response

​
rule
object
Complete rule configuration and metadata
​
execution_status
object
Current rule status and next scheduled evaluation
​
execution_history
array
Historical execution records and outcomes (if requested)
​
impact_analysis
object
Business impact metrics and effectiveness analysis (if requested)

​
Response Example

{
    "rule": {
        "rule_id": "rule_456",
        "rule_name": "Happy Hour Beverage Pricing",
        "rule_type": "pricing",
        "is_active": true,
        "priority": 10,
        "conditions": {
            "time_range": {
                "start": "15:00",
                "end": "18:00"
            },
            "days_of_week": ["monday", "tuesday", "wednesday", "thursday", "friday"],
            "date_exceptions": ["2024-12-25", "2024-01-01"]
        },
        "actions": {
            "adjust_pricing": {
                "type": "percentage",
                "value": -25,
                "round_to": 0.05
            },
            "apply_promotional_tag": "happy_hour"
        },
        "scope": {
            "apply_to_categories": ["beverages", "appetizers"],
            "exclude_items": ["premium_wine", "specialty_cocktails"],
            "affected_item_count": 23
        },
        "effective_date_range": {
            "start_date": "2024-02-01",
            "end_date": "2024-03-31"
        },
        "created_at": "2024-01-15T10:30:00Z",
        "updated_at": "2024-01-20T14:45:00Z",
        "created_by": "manager_user_123"
    },
    "execution_status": {
        "current_status": "inactive",
        "last_execution": "2024-01-19T17:00:00Z",
        "next_evaluation": "2024-01-22T15:00:00Z",
        "execution_count_today": 0,
        "total_executions": 45,
        "last_execution_result": "success"
    },
    "execution_history": [
        {
            "execution_time": "2024-01-19T17:00:00Z",
            "execution_result": "success",
            "items_affected": 23,
            "duration_ms": 125,
            "conditions_met": true,
            "actions_executed": ["adjust_pricing", "apply_promotional_tag"]
        }
    ],
    "impact_analysis": {
        "revenue_impact": {
            "total_discount_applied": 1250.75,
            "affected_orders": 89,
            "average_order_increase": 15.5
        },
        "customer_engagement": {
            "happy_hour_orders": 89,
            "repeat_customers": 34,
            "customer_satisfaction_score": 4.2
        },
        "operational_metrics": {
            "kitchen_efficiency": "improved",
            "inventory_turnover": "increased",
            "staff_feedback": "positive"
        }
    }
}
Configuration Details
  • Complete rule setup including conditions and actions
  • Scope definition and affected items/categories
  • Priority and conflict resolution information
  • Effective date ranges and scheduling details
Execution Information
  • Current rule status and evaluation schedule
  • Historical execution patterns and success rates
  • Performance metrics and execution timing
  • Error logs and troubleshooting information
Business Impact Analysis
  • Revenue impact from rule applications
  • Customer behavior changes and engagement metrics
  • Operational efficiency improvements
  • Competitive positioning and market response
Performance Metrics
  • Rule execution frequency and patterns
  • System performance impact and optimization opportunities
  • Integration effectiveness across platforms
  • Customer satisfaction and experience metrics
Data Availability: Historical and impact analysis data may have retention limits. Specify appropriate date ranges to ensure you receive the data you need for analysis.
Performance Monitoring: Use the execution history to identify optimization opportunities and troubleshoot rule performance issues for better business outcomes.

​
Use Cases

Rule Performance Optimization
  • Analyze execution patterns to optimize rule timing
  • Identify performance bottlenecks in rule evaluation
  • Optimize rule conditions for better targeting
  • Improve rule effectiveness through data-driven adjustments
Business Impact Assessment
  • Measure revenue impact of pricing and promotional rules
  • Analyze customer response to availability changes
  • Evaluate operational efficiency improvements
  • Assess competitive positioning and market response
Troubleshooting and Debugging
  • Investigate unexpected rule behavior or conflicts
  • Analyze execution failures and error patterns
  • Validate rule logic against business requirements
  • Identify integration issues with external systems
Compliance and Auditing
  • Review rule changes and approval history
  • Validate rule compliance with business policies
  • Generate audit reports for regulatory requirements
  • Document rule effectiveness for business reviews

​
Execution Status Details

Current Status Values
  • active: Rule is currently executing actions
  • inactive: Rule conditions are not met
  • scheduled: Rule is waiting for next evaluation time
  • disabled: Rule is manually disabled
  • error: Rule has encountered execution errors
  • expired: Rule has passed its effective date range
Execution Timing
  • last_execution: When the rule was last evaluated
  • next_evaluation: When the rule will be evaluated next
  • execution_count_today: Number of executions in the current day
  • total_executions: Lifetime execution count for the rule
Performance Metrics
  • execution_duration: Time taken for rule evaluation and action execution
  • success_rate: Percentage of successful rule executions
  • error_frequency: Rate of execution errors and failures
  • system_impact: Resource utilization during rule execution
Result Information
  • items_affected: Number of items impacted by the rule
  • actions_executed: List of actions successfully completed
  • conditions_met: Which conditions triggered the rule execution
  • conflict_resolution: How conflicts with other rules were resolved

​
Historical Analysis

Execution Patterns
  • Daily, weekly, and monthly execution frequency
  • Seasonal patterns and trends in rule activation
  • Correlation between rule execution and business events
  • Peak execution times and system load patterns
Success and Failure Analysis
  • Success rates and common failure modes
  • Error patterns and system integration issues
  • Performance degradation trends over time
  • Recovery patterns after system issues
Business Impact Trends
  • Revenue impact trends over time
  • Customer behavior changes and adaptation patterns
  • Operational efficiency improvements and challenges
  • Competitive response and market dynamics
Optimization Opportunities
  • Timing optimization based on execution patterns
  • Condition refinement for better targeting
  • Action optimization for improved effectiveness
  • Performance improvements through better rule design

​
Impact Analysis Metrics

Revenue Impact
  • total_discount_applied: Cumulative discount amount from pricing rules
  • revenue_increase: Revenue growth attributed to rule optimization
  • average_order_value_change: Impact on customer spending patterns
  • profit_margin_impact: Effect on business profitability
Customer Engagement
  • affected_orders: Number of orders impacted by the rule
  • repeat_customers: Customer retention and repeat business
  • customer_satisfaction_score: Customer experience metrics
  • new_customer_acquisition: Attraction of new customers through rule benefits
Operational Metrics
  • kitchen_efficiency: Impact on food preparation and service
  • inventory_turnover: Effect on inventory management and waste
  • staff_productivity: Impact on staff efficiency and workload
  • delivery_performance: Effect on delivery and fulfillment operations
Market Position
  • competitive_advantage: Competitive positioning improvements
  • market_share_impact: Effect on market position and customer capture
  • brand_perception: Impact on brand image and customer perception
  • pricing_competitiveness: Positioning relative to market pricing

​
Error Handling

Rule Not Found
{
  "error": "Rule not found",
  "message": "The specified rule ID does not exist for this store",
  "details": {
    "store_id": "store_123",
    "rule_id": "invalid_rule_id"
  }
}
Permission Denied
{
  "error": "Permission denied",
  "message": "Insufficient permissions to view detailed rule information"
}
Invalid Date Range
{
  "error": "Invalid date range",
  "message": "The specified date range is invalid or exceeds maximum allowed period",
  "details": {
    "provided_range": "2024-01-01,2025-01-01",
    "maximum_days": 90
  }
}
Data Not Available
{
  "error": "Data not available",
  "message": "Historical data for the requested period is not available",
  "details": {
    "requested_date_range": "2023-01-01,2023-12-31",
    "available_from": "2024-01-01"
  }
}

​
Best Practices

Regular Monitoring
  • Schedule regular reviews of rule performance and impact
  • Monitor execution patterns for optimization opportunities
  • Track business impact metrics consistently
  • Identify and address performance issues promptly
Data-Driven Optimization
  • Use execution history to optimize rule timing and conditions
  • Analyze impact metrics to improve rule effectiveness
  • Identify successful patterns for replication across other rules
  • Use performance data to guide rule design decisions
Troubleshooting Strategy
  • Review execution history when investigating issues
  • Analyze error patterns to identify systematic problems
  • Use impact analysis to assess the severity of rule issues
  • Implement monitoring alerts for critical rule failures
Business Intelligence Integration
  • Integrate rule data with broader business analytics
  • Use rule impact metrics in business performance dashboards
  • Correlate rule effectiveness with broader business outcomes
  • Support strategic decision-making with rule performance data

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Analytics and Reporting

Performance Dashboard Creation
  • Create visualizations of rule execution patterns
  • Monitor business impact trends over time
  • Track customer satisfaction and engagement metrics
  • Display operational efficiency improvements
Comparative Analysis
  • Compare rule effectiveness across different time periods
  • Analyze performance variations by day of week or season
  • Compare similar rules across different stores or locations
  • Benchmark rule performance against business objectives
Predictive Analytics
  • Forecast rule impact based on historical patterns
  • Predict optimal timing for rule modifications
  • Anticipate customer response to rule changes
  • Model business impact of proposed rule modifications
ROI Analysis
  • Calculate return on investment for rule automation
  • Measure cost savings from operational efficiency
  • Analyze revenue impact relative to implementation costs
  • Evaluate long-term business value of rule strategies

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Integration with Business Intelligence

Data Export and Integration
  • Export rule data for integration with BI tools
  • Create data pipelines for real-time analytics
  • Integrate with existing business intelligence platforms
  • Support custom reporting and analysis requirements
Real-time Monitoring
  • Implement real-time rule performance dashboards
  • Create alerts for rule performance anomalies
  • Monitor business impact in real-time
  • Support rapid response to rule issues
Strategic Planning Support
  • Use rule data to inform menu strategy decisions
  • Support competitive analysis and positioning
  • Guide investment in menu automation capabilities
  • Inform customer experience optimization strategies
Compliance and Governance
  • Generate compliance reports for audit requirements
  • Track rule changes and their business justification
  • Monitor adherence to business policies and guidelines
  • Support regulatory reporting and documentation needs

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Rule Optimization Workflow

Regular Review Process
  1. Performance Assessment: Analyze execution patterns and success rates
  2. Impact Evaluation: Measure business impact and customer response
  3. Optimization Identification: Identify opportunities for improvement
  4. Testing and Validation: Test proposed changes in controlled environments
  5. Implementation: Deploy optimized rules with monitoring
  6. Monitoring and Feedback: Track improvements and gather feedback
Data-Driven Decision Making
  • Use historical execution data to guide optimization decisions
  • Leverage impact analysis to prioritize optimization efforts
  • Apply statistical analysis to identify significant patterns
  • Test hypotheses through controlled rule modifications
Continuous Learning
  • Document lessons learned from rule optimization efforts
  • Share best practices across teams and locations
  • Build organizational knowledge about effective rule design
  • Develop expertise in menu automation and optimization