CRM Data Cleanup Before Migration: The Step-by-Step Process

Why Data Cleanup Is Critical

Migrating dirty data to a new CRM is one of the most expensive mistakes in CRM projects. Duplicate records, incomplete fields, outdated contacts, and inconsistent formats undermine user adoption, reporting accuracy, and workflow automation from day one.

Step 1: Data Audit

Record Count Audit

Count total records by object type:

• Contacts
• Accounts/Companies
• Leads
• Opportunities/Deals
• Cases/Tickets
• Activities/Tasks
• Custom objects

Data Quality Audit

Assess data quality across these dimensions:

• Completeness: Percentage of records with required fields filled
• Accuracy: Correctness of data values
• Consistency: Uniform formats for phone numbers, addresses, dates
• Timeliness: Currency of data (last updated dates)
• Uniqueness: Absence of duplicate records

Step 2: Deduplication

Remove duplicate records before migration:

• Identify duplicates using email address as primary key
• For contacts: match on email + phone + company name
• For accounts: match on name + website + phone
• Merge duplicates preserving the most complete record
• Document merge rules for consistent handling

Step 3: Standardization

Standardize data formats:

• Phone numbers: Choose a standard format (e.g., +1 (555) 123-4567)
• Addresses: Standardize street, city, state, zip, country
• Dates: Use consistent date format (YYYY-MM-DD)
• Names: Consistent capitalization (First Last, not ALL CAPS)
• Picklist values: Map variations to standard values

Step 4: Enrichment

Fill missing data where possible:

• Use email validation services to verify and correct email addresses
• Use address validation to standardize and complete addresses
• Research missing phone numbers for key accounts
• Assign default values for required fields that cannot be filled

Step 5: Validation

Validate cleaned data before migration:

• Spot-check random samples for accuracy
• Verify deduplication results (no remaining duplicates)
• Confirm standardization applied consistently
• Validate required fields are 100% complete
• Get business stakeholder sign-off on data quality

Tools for Data Cleanup

Common tools used for CRM data cleanup:

• Excel/Google Sheets with formulas for basic deduplication
• OpenRefine for advanced data transformation
• Dedicated data quality platforms
• CRM-native deduplication tools

How AavishkarIT Helps

Data cleanup is included in every migration project we undertake. Our team uses structured processes and tools to audit, deduplicate, standardize, and validate your data before migration to ensure a clean start in your new CRM.