Data mapping is the foundation of CRM migration. Learn how to create a comprehensive mapping document with this template and methodology.
Dirty data is responsible for 65% of CRM migration failures — more than technical issues.
Need help applying this? Our CRM consultants are available.
Get Mapping TemplateKey Takeaways
Migration — Quick Summary
- 1Object Mapping
- 2Field Mapping Template
Who This Article Is For
Migration — role-specific value map
Dirty source data causing silent failures and post-migration corrections
Structured audit, cleanup, and validation that ensures data integrity on day one
Business disruption during cutover and no tested rollback plan
Phased migration approach with tested rollback procedures and minimal downtime
Migration budget overruns due to underestimated data complexity
Realistic budget built on data audit findings, not vendor estimates
of migrations impacted by poor data quality
Source: Gartner
less post-migration fixing with pre-migration cleanup
Source: Industry Research
faster recovery when rollback plan is tested pre-launch
Source: IT Risk Research
typical CRM data migration timeline
Source: AavishkarIT Data
CRM Migration Flow
Data mapping is the process of defining how data from your source CRM will be structured in your target CRM. It includes mapping objects, fields, relationships, picklist values, and data transformation rules. A comprehensive mapping document is essential for accurate migration.
Map source objects to target objects:
| Source Object | Target Object | Notes |
|---|---|---|
| Accounts | Accounts | Direct mapping |
| Contacts | Contacts | Direct mapping |
| Opportunities | Opportunities | Direct mapping |
| Cases | Cases | Direct mapping |
| Custom Object X | Custom Section X | Needs custom creation |
For each mapped object, document field-level mapping:
| Source Field | Source Type | Target Field | Target Type | Transformation | Default Value |
|---|---|---|---|---|---|
| AccountName | Text(100) | Name | Text(100) | None | - |
| Phone | Phone | Phone | Phone | Standardize format | - |
| Industry | Picklist | Industry | Picklist | Map values | Other |
Document how relationships between objects will be maintained:
- Contact → Account (lookup relationship)
- Opportunity → Contact (lookup relationship)
- Opportunity → Account (lookup relationship)
- Activity → Related Record (polymorphic relationship)
Map source picklist values to target picklist values:
| Source Value | Target Value | Action |
|---|---|---|
| Technology | Technology | Direct map |
| IT Services | Technology | Consolidate |
| Software | Technology | Consolidate |
Document rules for data transformation:
- Phone numbers: Remove non-numeric characters, add country code
- Addresses: Split full address into street, city, state, zip
- Dates: Convert from MM/DD/YYYY to YYYY-MM-DD
- Currency: Convert values to base currency
- Text fields: Trim whitespace, fix capitalization
Document validation requirements:
- Required fields must not be null
- Email fields must match email format
- Phone fields must be valid format
- Picklist values must match allowed values
- Date fields must be valid dates
We create comprehensive data mapping documents as part of every migration project. Our mapping process includes object mapping, field mapping, relationship mapping, picklist mapping, transformation rules, and validation criteria.
We've completed over 80 CRM migrations. The projects that fail have one thing in common: they started migrating data before they finished cleaning it. Never rush the audit phase.
Key Terms & Definitions
Quick reference glossary for this topic
Downloadable Resources
Free templates and guides
References & Resources
- 1AavishkarIT CRM Implementation Services
aavishkarit.com
- 2