Quick answer: Use deterministic matching for obvious duplicates and AI only to suggest review candidates. Never let a model silently merge customer records.
Why matching is harder than it looks
A regional home-services business might receive “Chris A Smith” in one form and “C. Smith” in another. Two records could represent the same person or two household members. A model might invent confidence based on name similarity while missing shared phone numbers, address changes and consent status.
A low-risk matching ladder
Normalize email case and whitespace. Standardize phone formats with a library that understands country codes, rather than deleting arbitrary characters. Flag identical verified email addresses for review, but do not assume a shared family inbox means the records belong to one individual.
Create a candidate pair record with the fields that match, the fields that differ and the proposed survivor record. Explicitly preserve the original IDs, source timestamps, opt-in status and audit history.
Approval before merge
The CRM owner compares the records. If history conflicts, keep both. When a merge is approved, export a backup or use the platform’s reversible merge feature, and record the operation ID. Reject any rule that overwrites a newer contact preference with an older one.
Test cases
- Two people with a shared office number.
- One person changing email addresses.
- Names with apostrophes or different spelling conventions.
- An imported list with all phone numbers blank.
- A customer who opted out in one system but not another.
A workflow must not convert uncertain identity matching into a privacy problem.
Measure success
Count reviewed candidates, confirmed duplicates, false matches and recovery time. “Records removed” alone is a bad KPI; deleting legitimate contacts is not progress.
FAQ
What if the CRM already provides duplicate detection?
Use its native feature first. AI might assist with confusing exceptions, but each added integration increases maintenance and data-processing scope.
References and further reading
These references provide context and official guidance. The sample workflows above are illustrative designs, not vendor performance tests.
Published by: FlowHarbor Editorial Desk. Read our sourcing and review policy.