Data Management
Ensure your CRM data is high-quality, unbiased, and compliant for AI implementation
Data Quality Scanner
Analyze your CRM data for completeness, consistency, and relevance
Completeness
Missing data assessment
72%
28% of customer records have missing fields that could impact AI performance
Consistency
Data format and value consistency
85%
Most data follows consistent formats, with some exceptions in address fields
Relevance
Data usefulness for AI models
90%
Most collected data is relevant for AI use cases, with good historical depth
Data Quality Issues
Critical issues that need to be addressed before AI implementation
| Issue | Affected Records | Severity | Impact on AI | Actions |
|---|---|---|---|---|
| Missing Email Addresses | 2,145 records (12%) | Medium | Reduced accuracy in customer communication models | |
| Duplicate Customer Records | 543 records (3%) | High | Skewed analytics and personalization | |
| Inconsistent Phone Formats | 1,876 records (10%) | Low | Minor impact on contact analytics | |
| Outdated Customer Data | 3,254 records (18%) | High | Significant impact on prediction accuracy |