📊 COMPLETE GUIDE

The Complete Salesforce Data Migration Playbook

Everything you need to migrate data into Salesforce successfully. Based on 100+ migrations, with free templates, tool comparisons, and step-by-step instructions.

100+
Successful Migrations
15M+
Records Migrated
99.8%
Data Accuracy Rate
Free
Templates Included

Data migration is the #1 reason Salesforce implementations fail or get delayed. Poor planning, inadequate tools, or missing validation steps can turn a 2-week migration into a 6-month nightmare.

This guide contains everything I've learned from migrating over 15 million records across 100+ Salesforce implementations. Follow this playbook, and you'll complete your migration on time, on budget, and with data integrity intact.

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The 7-Phase Data Migration Framework

1

Discovery & Analysis

Analyze source data, identify data quality issues, and document business requirements. This phase determines 80% of your migration success.

⏱️ 2-3 days
2

Data Mapping & Design

Map source fields to Salesforce objects, design transformation rules, and plan data relationships. Critical for maintaining data integrity.

⏱️ 3-5 days
3

Data Preparation

Clean, deduplicate, and standardize data. Fix formatting issues, validate required fields, and prepare import files.

⏱️ 3-7 days
4

Test Migration

Run pilot migration with subset of data. Validate relationships, test automation triggers, and verify data accuracy.

⏱️ 2-3 days
5

Full Migration

Execute production migration following tested procedures. Monitor progress, handle errors, and maintain audit trail.

⏱️ 1-3 days
6

Validation & Reconciliation

Verify record counts, validate data accuracy, test business processes, and reconcile with source system.

⏱️ 2-3 days
7

Post-Migration Optimization

Enable automation, activate validation rules, optimize performance, and train users on data maintenance.

⏱️ 1-2 days

Choosing the Right Migration Tool

Selecting the appropriate tool can save days of work and prevent data corruption. Here's when to use each option:

Tool Best For Record Limit Complexity Cost
Data Import Wizard Simple imports, standard objects 50,000 Low Free
Data Loader Large volumes, scheduled jobs 5 million Medium Free
Dataloader.io Complex mappings, transformations 10+ million Low-Medium $59-299/mo
Workbench Developers, bulk API operations 10+ million High Free
ETL Tools (Informatica, Talend) Enterprise migrations, ongoing sync Unlimited High $1000+/mo
⚠️ Critical Warning
Never use Excel's VLOOKUP for ID mapping on datasets over 50,000 records. Excel will truncate Salesforce's 18-character IDs to 15 characters, causing data corruption. Use proper database tools or Salesforce's native ID handling.

Data Mapping Template

Use this template structure for mapping your source data to Salesforce objects:

# Account Data Mapping Template
# Source: Legacy CRM System
# Target: Salesforce Account Object

Source_Field | SF_Object | SF_Field | Transformation | Required | Notes
company_name | Account | Name | TRIM() | Yes | Max 255 chars
company_id | Account | External_ID__c | None | Yes | Unique identifier
annual_rev | Account | AnnualRevenue | CURRENCY() | No | Convert to USD
emp_count | Account | NumberOfEmployees | INTEGER() | No | Round to whole
website_url | Account | Website | LOWER() | No | Standardize format
industry_code | Account | Industry | PICKLIST_MAP() | Yes | Map to SF values

Common Migration Pitfalls (And How to Avoid Them)

🚫 Fatal Error #1: Circular Dependencies

Loading Contacts before Accounts when Contacts have Account lookups will fail. Always load parent objects first: Accounts → Contacts → Opportunities → Custom Objects.

🚫 Fatal Error #2: Duplicate Rules Active

Salesforce duplicate rules will block your migration. Deactivate all duplicate rules during migration, then reactivate after cleaning duplicates.

🚫 Fatal Error #3: Validation Rules Enabled

Complex validation rules designed for UI entry will fail bulk imports. Create a "Data Migration" user profile that bypasses validation rules.

Pre-Migration Checklist

✅ Complete This Before Starting Migration

Data Analysis

Source data profiling completed
Data quality issues documented
Record counts verified
Duplicate records identified

Salesforce Preparation

Custom fields created
Page layouts updated
Record types configured
Picklist values added
External ID fields created

Technical Setup

Sandbox environment ready
Migration tools installed
API limits verified
Backup strategy defined

Data Migration Timeline

Week 1: Discovery & Planning
Analyze source data, gather requirements, create migration plan
Week 2: Data Preparation
Clean data, create mappings, prepare Salesforce environment
Week 3: Test Migration
Run pilot migration, validate results, refine process
Week 4: Production Migration
Execute full migration, validate data, optimize performance

Advanced Migration Strategies

1. Handling Large Data Volumes (10M+ Records)

  • Use Bulk API 2.0: Processes up to 100 million records per day
  • Implement Parallel Processing: Split data into chunks and process simultaneously
  • Disable Triggers During Load: Re-enable after migration for 10x speed improvement
  • Use PK Chunking: For objects with more than 10 million records

2. Complex Relationship Management

  • Self-Lookups: Load records twice - first without lookups, then update with relationships
  • Many-to-Many: Create junction objects after loading both parent objects
  • Master-Detail: Always load master records before detail records
  • Hierarchies: Use External IDs to maintain parent-child relationships

3. Data Transformation Best Practices

  • Date Formats: Convert to YYYY-MM-DD format for Salesforce compatibility
  • Phone Numbers: Standardize to E.164 format for global compatibility
  • Addresses: Use Google Maps API for standardization and validation
  • Currency: Convert to org's default currency with dated exchange rates
✅ Success Story

Using this framework, we migrated 12 million records for a Fortune 500 company in just 3 weeks, with 99.8% data accuracy and zero business disruption. The key? Thorough planning and systematic validation at every step.

Post-Migration Validation

Never declare victory until you've validated:

  1. Record Counts: Source count = Target count (accounting for intentional exclusions)
  2. Data Integrity: Spot-check 100 random records for accuracy
  3. Relationships: Verify all lookups and master-detail relationships
  4. Business Logic: Test key business processes end-to-end
  5. Reports: Run critical reports and compare with legacy system
  6. User Acceptance: Have power users validate their specific data

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Frequently Asked Questions

How long does a typical data migration take?

For most organizations (under 1 million records), expect 2-4 weeks from planning to completion. Larger migrations (10M+ records) typically take 4-8 weeks.

What's the biggest migration risk?

Data quality issues in the source system. Poor data quality accounts for 60% of migration delays. Always budget time for data cleanup.

Should we migrate historical data?

Migrate only what's necessary for business operations. As a rule: 2 years of transactional data, 5 years of customer data, all active records.

Can we run old and new systems in parallel?

Yes, but avoid dual data entry. Use integration tools to sync systems during transition, then cut over completely to prevent data divergence.

How do we handle ongoing changes during migration?

Implement a "freeze period" for the source system 48 hours before final migration, or use delta loads to capture changes.

Remember: A successful migration is 70% planning, 20% execution, and 10% validation. Never skip the planning phase.