CRM Data Quality Scorecard: Measuring and Improving Your CRM Data

Why Data Quality Matters

Poor data quality undermines every CRM function: inaccurate reporting, failed automation, missed opportunities, and frustrated users. A data quality scorecard helps you measure, track, and improve your CRM data systematically.

Data Quality Dimensions

Completeness

Percentage of records with required fields populated:

• Contacts: Name, email, phone, company
• Accounts: Name, website, industry, size
• Deals: Name, value, stage, close date

Accuracy

Correctness of data values:

• Valid email addresses
• Working phone numbers
• Correct company names
• Accurate deal values

Consistency

Uniform formats and values:

• Standardized phone formats
• Consistent address formatting
• Uniform picklist values
• Consistent naming conventions

Timeliness

Currency of data:

• Last activity date within 90 days
• Contact information updated within 6 months
• Deal stages reflect current reality

Building Your Scorecard

Create a weighted scorecard:

Improving Data Quality

Preventive Measures

• Required fields on key objects
• Validation rules for email and phone formats
• Picklist constraints instead of free text
• Duplicate prevention rules

Corrective Measures

• Quarterly data cleanup campaigns
• Automated deduplication jobs
• Data enrichment services
• User training on data entry standards

How AavishkarIT Helps

We help businesses measure and improve CRM data quality. Our services include data quality assessment, scorecard design, cleanup execution, and ongoing monitoring through Managed Excellence.