8 CRM Data Migration Challenges That Sabotage Your Project (And How to Fix Them)

Your sales team can’t find their leads. Customer service has no order history. Reports show different numbers depending on which system you check. If this sounds familiar, you’ve experienced the aftermath of a botched CRM data migration.

Organizations consistently underestimate what’s involved in moving data between systems.

We’ve guided hundreds of CRM migrations over the past decade. Here are the eight most common data migration challenges we see, plus the practical solutions that actually work.

Challenge 1: Dirty Data Multiplication

The Problem: Bad data doesn’t stay contained during migration—it spreads throughout your new CRM like a virus. Incomplete customer records, duplicate entries, and inconsistent formatting become magnified when they’re moved to a clean system.

Common Symptoms:

• Customer records missing critical information
• Multiple entries for the same contact or company
• Inconsistent address and phone number formats
• Sales reps spending hours cleaning data instead of selling

Best Practices:

1. Audit your data before migration begins. Run data quality reports to identify incomplete, duplicate, or inconsistent records.
2. Implement data cleansing as a separate project phase. Don’t expect migration tools to fix fundamental data quality issues.
3. Establish data standards for your new system. Define acceptable formats for addresses, phone numbers, and other critical fields.
4. Create validation rules that prevent bad data from entering your new CRM.

Bonus Tip: At Faye, we use a three-phase approach: assess, cleanse, then migrate. This prevents the “garbage in, garbage out” problem that derails so many CRM projects.

Challenge 2: Legacy System Lock-In

The Problem: Your old system wasn’t designed to export data easily. Maybe it lacks APIs, uses proprietary formats, or simply crashes when you try to extract large datasets.

Common Symptoms:

• Limited export capabilities from your current system
• Data stuck in formats that modern systems can’t read
• System performance issues during data extraction
• Missing documentation about data structures

Best Practices:

1. Document your current data structure thoroughly. Map out where different types of information live and how they’re connected.
2. Use intermediate staging areas rather than direct system-to-system transfers.
3. Extract data in smaller batches to avoid overwhelming legacy systems.
4. Test extraction processes multiple times before the final migration.

Bonus Tip: We often create custom extraction tools for legacy systems, ensuring complete data retrieval without compromising system stability during business hours.

Challenge 3: Mismatched Data Models

The Problem: Your old CRM organizes customer information completely differently than your new one. What was a single record might need to become multiple records, or vice versa.

Common Symptoms:

• Customer hierarchies that don’t translate between systems
• Product categories organized differently
• Conflicting definitions of basic entities like “account” or “opportunity”
• Data that fits logically in the old system but has no clear place in the new one

Best Practices:

1. Create detailed field mapping documentation showing exactly how each piece of data will translate.
2. Identify data transformation requirements early. Some data will need to be restructured, not just copied.
3. Establish clear data ownership rules. When the same information exists in multiple places, which version is correct?
4. Plan for data that doesn’t have a direct equivalent in your new system.

Bonus Tip: We use visual mapping tools to help clients understand how their data will be restructured, preventing surprises during migration.

Challenge 4: Timing and Sequencing Problems

The Problem: Data has relationships and dependencies. Migrating information in the wrong order can break these connections, leaving you with orphaned records and missing links.

Common Symptoms:

• Customer records without associated contact information
• Opportunities disconnected from their parent accounts
• Activities that reference deleted or missing records
• Broken relationships between different data types

Best Practices:

1. Map data dependencies before migration. Understand which records reference others and in what order they need to be created.
2. Use a staged migration approach. Move master data first, then transactional data that references it.
3. Implement relationship validation to ensure connections are maintained.
4. Plan for data that spans the migration window. How will you handle new information created during the migration process?

Bonus Tip: Our migration plans include detailed sequencing charts that show exactly what data moves when, preventing dependency conflicts.

Challenge 5: User Access and Security Complications

The Problem: Your new CRM has different security models, user roles, and permission structures than your old system. Data that was accessible to certain users might become restricted, or vice versa.

Common Symptoms:

• Users can’t access data they previously could see
• Sensitive information exposed to users who shouldn’t have access
• Permissions that don’t align with actual job responsibilities
• Inconsistent access controls across different data types

Best Practices:

1. Audit current user permissions before migration to understand who has access to what.
2. Design new permission structures based on actual business needs, not just replicating old patterns.
3. Test user access scenarios with real users before going live.
4. Document permission changes and communicate them clearly to affected users.

Bonus Tip: We recommend implementing role-based security from day one, even if it means some users need training on new access patterns.

Challenge 6: Integration Breakdowns

The Problem: Your old CRM connects to other business systems. These integrations often break during migration because connection points, data formats, or system behaviors change.

Common Symptoms:

• Marketing automation systems can’t sync contact information
• Accounting software shows different customer data than the CRM
• E-commerce platforms can’t update order status
• Reporting tools missing critical data feeds

Best Practices:

1. Inventory all current integrations before beginning migration planning.
2. Test integration compatibility with your new CRM early in the process.
3. Plan integration updates as part of your migration project, not an afterthought.
4. Coordinate with owners of integrated systems to ensure they’re prepared for changes.

Bonus Tip: At Faye, we maintain an integration library for common business systems, allowing us to quickly reconnect your CRM with minimal downtime.

Challenge 7: Historical Data Handling

The Problem: You have years of valuable historical data, but your new CRM handles historical information differently. Some data might not migrate at all, or it might lose important context.

Common Symptoms:

• Lost sales history or customer interaction records
• Activities without proper timestamps or attribution
• Missing attachments or related documents
• Incomplete audit trails for compliance purposes

Best Practices:

1. Define data retention requirements clearly. What historical information is actually needed in the new system?
2. Plan for data archiving if some historical information doesn’t need to be actively accessible.
3. Preserve audit trails and timestamps during migration.
4. Test historical data accessibility to ensure users can find what they need.

Bonus Tip: We help clients create “data bridges” that maintain access to historical information even when it doesn’t fully migrate to the new system.

Challenge 8: Migration Validation and Rollback Planning

The Problem: You won’t know if your migration succeeded until users start working with the data. By then, rolling back might be impossible, and fixing problems becomes exponentially more difficult.

Common Symptoms:

• Data discrepancies discovered weeks after migration
• No way to verify migration accuracy
• Users unable to find critical information
• Inability to return to the old system if needed

Best Practices:

1. Create comprehensive validation procedures that check data accuracy, completeness, and relationships.
2. Develop detailed rollback plans in case migration needs to be reversed.
3. Implement parallel running periods where both systems operate simultaneously.
4. Train power users to validate data in their areas of expertise.

Bonus Tip: Our validation process includes automated data comparison tools plus user acceptance testing to catch issues before they impact business operations.

Real-World Success: AMP’s CRM Migration

American Marketing & Publishing (AMP) faced many of these challenges when migrating from their legacy print-focused CRM to a modern SugarCRM solution. Their old system couldn’t export data easily, used proprietary formats, and lacked the flexibility needed for their digital transformation.

Working with Faye, AMP took a methodical approach to migration:

• Data assessment first: We identified data quality issues and inconsistencies before attempting any technical migration
• Phased approach: Critical customer and sales data moved first, followed by historical information
• Custom extraction tools: We built specialized tools to extract data from their legacy system without performance impact
• Integration planning: Marketing automation and ERP connections were redesigned for the new system architecture

The result? AMP achieved a 97% increase in digital contract processing and a 45% improvement in Field Optima sales. More importantly, their sales team gained real-time access to accurate customer data for the first time in years.

Read the complete AMP success story to see how proper migration planning delivers measurable business results.

Your Migration Success Strategy

CRM data migration doesn’t have to be a nightmare. The key is treating it as a strategic business project, not just a technical task. Start with clear business objectives, invest time in data preparation, and plan for the organizational changes that come with new systems.

Remember: The goal isn’t moving every piece of data perfectly. It’s ensuring your team has the accurate, accessible information they need to serve customers and grow your business.