Data Validation for ACES/PIES Standards Compliance

Data validation is the cornerstone of successful ACES/PIES implementation. Poor data quality leads to rejected catalogs, lost sales, and frustrated trading partners. CatalogBridge's comprehensive validation engine ensures your automotive parts data meets industry standards before it reaches your customers.

Why Data Validation Matters

In the automotive aftermarket industry, data accuracy directly impacts:

• Catalog Acceptance: Trading partners reject non-compliant files
• Customer Experience: Accurate fitment data prevents returns
• Operational Efficiency: Clean data reduces manual corrections
• Business Relationships: Reliable data builds partner trust
• SEO Performance: Consistent data improves search visibility

Understanding ACES/PIES Validation Rules

ACES Validation Requirements

ACES (Aftermarket Catalog Exchange Standard) focuses on vehicle application data:

Required Elements:

<App action="A" id="1">
  <BaseVehicle id="12345"/>  <!-- Required: Valid vehicle ID -->
  <Part>ABC123</Part>         <!-- Required: Part number -->
  <Qty>1</Qty>                <!-- Required: Quantity -->
  <PartType id="1684"/>       <!-- Required: Valid part type -->
</App>

Validation Checks:

1. BaseVehicle Validation

   • Valid vehicle ID from ACES vehicle database
   • Correct year/make/model/engine combinations
   • No discontinued vehicle references

2. Part Number Validation

   • Alphanumeric characters only (with allowed exceptions)
   • No leading/trailing spaces
   • Consistent formatting across catalog

3. Part Type Validation

   • Valid PCdb part terminology ID
   • Appropriate type for vehicle application
   • Consistent categorization

PIES Validation Requirements

PIES (Product Information Exchange Standard) covers product details:

Core Validation Areas:

• Item Records: Part numbers and brand codes
• Descriptions: Length limits and character restrictions
• Pricing: Valid price types and currency codes
• Attributes: Standardized units and values
• Digital Assets: Proper asset linking and types

CatalogBridge Validation Engine

Multi-Level Validation

Our validation system operates at three levels:

Level 1: Syntax Validation

• File format correctness
• XML structure validity
• Character encoding verification
• Required field presence

Level 2: Business Rule Validation

• ACES/PIES compliance rules
• Industry-specific requirements
• Logical consistency checks
• Relationship integrity

Level 3: Data Quality Validation

• Completeness scoring
• Accuracy assessment
• Enrichment opportunities
• Best practice recommendations

Real-Time Validation Features

// Example validation response
{
  "validationResults": {
    "errors": [
      {
        "severity": "ERROR",
        "code": "ACES-001",
        "message": "Invalid BaseVehicle ID: 99999",
        "location": "Row 45, App ID 234",
        "suggestion": "Did you mean BaseVehicle ID: 12345 (2019 Ford F-150)?"
      }
    ],
    "warnings": [
      {
        "severity": "WARNING",
        "code": "PIES-023",
        "message": "Missing long description",
        "location": "Part: BRK-789",
        "impact": "Reduced search visibility"
      }
    ],
    "info": [
      {
        "severity": "INFO",
        "code": "QUALITY-001",
        "message": "Consider adding product images",
        "location": "15 parts without images"
      }
    ]
  }
}

Common Validation Errors and Solutions

Error 1: Invalid Vehicle Applications

Problem: "BaseVehicle ID not found in VCdb"

Root Causes:

• Outdated vehicle database
• Typographical errors
• Regional vehicle variations

Solution:

CatalogBridge Automatic Fix:
1. Fuzzy matching to find correct vehicle
2. Suggestion of valid alternatives
3. Bulk correction for systematic errors
4. VCdb version compatibility check

Error 2: Part Number Format Issues

Problem: "Invalid characters in part number"

Common Issues:

• Special characters (!@#$%^&*)
• Spaces within part numbers
• Inconsistent formatting

Best Practice:

Original: "BRK 123-A/B"
Corrected: "BRK123AB"

Allowed characters: A-Z, 0-9, hyphen (-), period (.)
Maximum length: 45 characters

Error 3: Missing Required Descriptions

Problem: "Item description required but not provided"

PIES Requirements:

• Short Description: Maximum 40 characters
• Long Description: Maximum 2000 characters
• Marketing Description: Optional but recommended

Example Fix:

<!-- Before -->
<Item>
  <PartNumber>BRK456</PartNumber>
  <!-- Missing descriptions -->
</Item>

<!-- After -->
<Item>
  <PartNumber>BRK456</PartNumber>
  <Descriptions>
    <Description DescriptionType="SHO">Premium Ceramic Brake Pads</Description>
    <Description DescriptionType="LON">High-performance ceramic brake pads featuring advanced friction materials for superior stopping power, reduced dust, and extended life. Includes wear indicators and premium shims for quiet operation.</Description>
  </Descriptions>
</Item>

Advanced Validation Strategies

Custom Validation Rules

Configure business-specific validation:

{
  "customValidation": {
    "rules": [
      {
        "field": "price",
        "condition": "mustBeGreaterThan",
        "value": 0,
        "severity": "ERROR"
      },
      {
        "field": "brand",
        "condition": "mustBeInList",
        "values": ["BrandA", "BrandB", "BrandC"],
        "severity": "WARNING"
      }
    ]
  }
}

Validation Profiles

Different validation strictness levels:

Standard Profile:

• All ACES/PIES required fields
• Basic format validation
• Critical error prevention

Strict Profile:

• Enhanced data quality checks
• Best practice enforcement
• Trading partner specific rules

Custom Profile:

• Industry-specific requirements
• Company standards
• Regional compliance

Building a Validation Workflow

Step 1: Pre-Upload Validation

Before uploading to CatalogBridge:

Pre-Upload Checklist:
□ Remove empty rows and columns
□ Verify column headers match expected format
□ Check file encoding (UTF-8 recommended)
□ Ensure no corrupted data
□ Validate basic data types

Step 2: Upload and Initial Scan

CatalogBridge performs immediate validation:

1. File Format Check: Verify CSV/Excel structure
2. Header Recognition: Map columns to ACES/PIES fields
3. Data Type Detection: Identify numeric, text, date fields
4. Quick Stats: Row count, unique parts, brands

Step 3: Comprehensive Validation

Full validation process includes:

• Field-Level Validation: Each data point checked
• Cross-Reference Validation: Relationships verified
• Business Logic Validation: Industry rules applied
• Enhancement Suggestions: Improvement opportunities

Step 4: Error Resolution

Systematic error resolution approach:

Priority Order:
1. Critical Errors (blocks file processing)
   - Fix immediately
   - Usually format or structure issues

2. Major Errors (affects data usability)
   - Address before distribution
   - Often missing required fields

3. Warnings (quality improvements)
   - Review and fix if possible
   - May impact search/display

4. Suggestions (optimization opportunities)
   - Implement for better results
   - Enhances user experience

Validation Reports and Analytics

Understanding Validation Reports

CatalogBridge provides detailed validation reports:

Validation Summary Report
========================
File: automotive-parts-june-2025.csv
Total Records: 5,000
Validation Date: 2025-06-24

Results Summary:
- Critical Errors: 0
- Major Errors: 12
- Warnings: 47
- Suggestions: 156

Compliance Score: 94/100

Top Issues:
1. Missing vehicle engine data (8 occurrences)
2. Invalid part type codes (4 occurrences)
3. Incomplete descriptions (35 occurrences)

Tracking Validation Metrics

Monitor data quality over time:

• Compliance Trends: Track improvement
• Common Error Patterns: Identify systematic issues
• Vendor Scorecards: Compare supplier data quality
• ROI Metrics: Measure quality improvement impact

Best Practices for Maintaining Compliance

1. Regular Validation Cycles

• Daily: New product additions
• Weekly: Full catalog validation
• Monthly: Comprehensive quality audit
• Quarterly: Standards update review

2. Team Training

Ensure your team understands:

• ACES/PIES standards basics
• Common validation errors
• Resolution procedures
• Quality metrics

3. Automated Monitoring

Set up automated alerts for:

• Validation score drops
• New error types
• Compliance threshold breaches
• Standards updates

4. Continuous Improvement

• Review validation reports regularly
• Identify patterns in errors
• Update source data processes
• Implement preventive measures

Industry-Specific Validation

Heavy-Duty Parts

Additional validation for commercial vehicles:

• Class 4-8 vehicle applications
• Heavy-duty specific attributes
• Commercial pricing tiers

Performance Parts

Enhanced validation for aftermarket performance:

• Modification compliance notes
• Performance specifications
• Installation complexity ratings

Collision Parts

Specific requirements for body shops:

• OEM cross-references
• Paint codes and finishes
• Certification requirements

Getting Started with Validation

Ready to ensure your automotive parts data meets industry standards?

1. Upload your CSV or Excel file
2. Review the instant validation report
3. Correct any critical errors
4. Download your compliant ACES/PIES files

For businesses requiring custom validation rules or high-volume processing, our Enterprise plans include:

• Custom validation profiles
• API access for automated validation
• Dedicated support team
• Training and consultation

Conclusion

Data validation isn't just about meeting technical requirements—it's about ensuring your automotive parts data serves its purpose effectively. With CatalogBridge's comprehensive validation engine, you can confidently distribute ACES/PIES compliant data that enhances your business relationships and drives sales.

Start validating your data today with our free trial and experience the difference that quality validation makes.