The hard part of deduplication: matching records that do not look identical

Exact-match duplicates are the easy ones to catch, same email, same everything, a basic rule finds them instantly. The duplicates that actually damage a database are the ones that do not look identical at all: a nickname instead of a formal first name, a personal email on one record and a work email on another, a job title updated on one entry but not the other. Those are the records that slip past simple deduplication and keep causing problems.

A contact who shows up under a shortened first name at one email and a full formal name at another, both technically valid, both technically different strings, is still one person receiving two separate outreach sequences that were never meant to overlap. Basic exact-match dedup logic sees two different records and leaves both in place, which is how a database can look clean by a naive count while still sending a prospect contradictory messages.

Matching these records correctly requires looking at a combination of signals together, name similarity, shared company domain, overlapping phone numbers, job history continuity, rather than any single field being an exact match. Getting this wrong in the other direction is just as costly: merge two records that are actually different people at the same company, and you lose a legitimate second contact entirely, which is its own kind of data damage.

We treat this as a matching problem, not a filtering problem. Records get evaluated on weighted similarity across several fields at once, so a near-match with strong signal across multiple data points gets merged, while a record that only shares one coincidental detail, a common last name, stays separate. That distinction is what keeps a merge from accidentally deleting a real contact.

This level of matching is slower and more deliberate than a simple duplicate scan, but it is what keeps our database of 46M+ records genuinely clean rather than clean by a surface-level count, which is the standard that protects deliverability and campaign accuracy across every channel built on top of it.