What is data matching?
Data matching is the algorithmic process of deciding whether two records describe the same person, account, or thing. Exact matching is easy (same email = same person); fuzzy and probabilistic matching get into the messy real-world cases where the same company shows up as "Acme Inc.," "Acme Incorporated," and "ACME."
Why it matters
- Underpins deduplication — you can't merge records you didn't match
- Required for identity resolution across systems with different keys
- Drives account-based reporting where a single account spans many touchpoints
Matching strategies
- Exact — fastest, highest precision, lowest recall
- Normalized exact — lowercase, strip punctuation, then exact — catches most easy variants
- Fuzzy — edit distance, phonetic encoding (Soundex/Metaphone) for names
- Probabilistic — combine many weak signals into a confidence score
- Embedding-based — vector similarity for semantic matching
How TexAu helps
Built-in matching rules let you stitch records inside a TexAu table — match contacts to accounts by domain, dedupe accounts by normalized name, link inbound leads to existing CRM records before they ever get duplicated.
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