Identity Resolution
Identity Resolution is the process of deciding whether two records — across systems, across sources, across time — refer to the same real-world person or company, so the data stack maintains one canonical view per entity.
What is Identity Resolution?
Identity Resolution is the foundation of every clean data system. Without it, the same person appears five times (once per data source) and downstream automation can't tell which record is current. Modern Identity Resolution uses both deterministic matching (exact email, exact domain, shared external IDs) and probabilistic matching (fuzzy name + employer, similar domains, location overlap). Every match has a confidence score, and low-confidence matches queue for human review.
Why it matters
- Resolves the duplication problem that breaks every downstream system if left unaddressed.
- Enables accurate counts, accurate reporting, and accurate agent behavior.
- Confidence-scored matching means edge cases get reviewed, not silently wrong.
Use cases
- CRM cleanup. Merge the duplicate accounts and contacts that accumulated over years.
- Cross-system reconciliation. Match records across CRM, marketing automation, and product analytics.
- Job-change detection. Recognize when a person at company A appears later at company B.
How turgo helps
turgo's Golden Records use a two-tier identity resolution (deterministic-first, probabilistic-second) with confidence scoring — every match is auditable, and edge cases queue for review.
See turgo in action →
