The playbook
CRM Data Migration: Worked Examples
The following CRM data migration examples illustrate how to move from an observed problem to a practical decision. They are hypothetical operating scenarios, not customer results or performance benchmarks. The central question is whether the work helps improve reconciled migrated records without losing the context needed to judge it.
Put the task in context
Keep the original source identifier during migration so records can be reconciled. Map relationships as well as fields. Test duplicate matching, blank values, stage translation, and dates on a small sample before moving the remaining records.
Example 1: establish a usable starting point
A team begins working on CRM data migration but cannot consistently describe source ID and target ID for the same item. The immediate task is inventory source objects fields and identifiers. The team records the current state, identifies the source of each value, and resolves conflicting information before making a broader change.
The useful output is a customer or opportunity record that another person can interpret. This example does not require assuming an uplift. Success at this stage means the next decision can be made using a shared set of facts, with missing information explicitly identified.
Example 2: correct a specific failure
In a second situation, the team observes importing duplicate people as separate unrelated contacts. It proposes the correction: define matching rules and test a small representative migration. Before applying that correction everywhere, the owner checks whether the same cause is present in other affected items. A common symptom alone does not prove that all items need the same repair.
| Decision | Illustrative reasoning |
|---|---|
| Observation | Importing duplicate people as separate unrelated contacts |
| Likely correction | Define matching rules and test a small representative migration |
| Verification task | Clean duplicates and map values before import |
| Result to inspect | Reconcile counts relationships and sample histories |
After the change, the owner repeats the relevant task and records what happened. If the condition remains, the team returns to the evidence rather than declaring the process complete. The example illustrates a repair cycle; it does not claim a particular commercial result.
Example 3: extend a process after it works
A third team already has reliable records for a small scope and wants to expand. It compares the next group with the first: are source ID, target ID, field mapping defined in the same way, and does the intended outcome remain reconciled migrated records? Differences are written down before the earlier process is reused.
Expansion is appropriate when the assumptions still hold and an owner can review exceptions. Where the new group has different needs, the team adapts the process and tests again. Reusing the structure is useful; reusing a conclusion without checking its conditions is much less reliable.
Apply the examples to your own work
- Write the current problem in observable terms using source ID.
- Choose which of the three examples matches the stage of the work.
- Complete this action first: inventory source objects fields and identifiers.
- Keep the resulting evidence and review reconciled migrated records on a consistent basis.
Preserve the context of the last meaningful conversation. The next owner should know what was promised, what remains unresolved, and who is expected to act. A stage label alone rarely supplies enough information.
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