Resolve customer identities with accountable match decisions

Preserve source identity from the start

Customer records arrive from CRM, billing, service, policy, onboarding and other systems. Each contributing record keeps its original source identifier so it can be traced, corrected and republished without losing provenance.

Compare consistent values

Names, addresses, phone numbers, emails and official identifiers are parsed and normalized before matching. Validation and reference data improve comparability while the original source values remain available for lineage.

Standardization reduces false differences; it does not hide missing or uncertain information.

Use rules appropriate to the business

Candidate rules narrow the search to plausible duplicates. Matching considers exact and fuzzy similarities across multiple attributes. Scores, contributing evidence and rule outcomes remain visible so users can understand why records were proposed.

The right thresholds depend on risk: a marketing use case and a regulated onboarding decision may require different controls.

Put people in control of uncertainty

High-confidence cases may follow configured automation. Ambiguous candidates enter a stewardship queue where an authorized person compares values, sources and evidence, then confirms or rejects the match.

The review decision, reviewer and timestamp become part of the governed history.

Build a traceable golden record

Survivorship rules choose the best values using trusted source, completeness, recency or other configured priorities. The merged record retains links to every contributing source and the history of how it was formed.

See how the result is modeled in the Golden customer record guide.

Keep exploring Customer 360

See where matching fits in the wider architecture, how the data model supports it and what survives into the golden record.