Definition
Company data matching is the process of resolving different representations of the same company (e.g., 'Google LLC', 'Alphabet Inc.', 'google.com') to a single canonical record, enabling accurate deduplication, enrichment, and CRM hygiene.
In Depth
The core challenge: companies have legal names, DBA names, domain names, stock tickers, and informal names that all refer to the same entity. Traditional approaches use string matching (Levenshtein distance, Jaro-Winkler) but these fail on abbreviations ('IBM' vs 'International Business Machines') and parent-subsidiary relationships ('Instagram' vs 'Meta Platforms'). Domain-based matching resolves this for companies with known domains but fails for companies sharing email providers (many startups use gmail.com). Search-based matching offers a hybrid approach: search Google for the company name and compare the top result's domain against your stored domain. If they match, high confidence. If the search returns a different canonical name, update your record. Implementation cost: one search per company at $0.005/query via Scavio or $0.0006 via DataForSEO ($50 min deposit). For a one-time cleanup of 5K company records: $25 via Scavio (no commitment) or $3 via DataForSEO (requires $50 deposit). Clearbit (now part of HubSpot) offers domain-to-company resolution but requires a HubSpot relationship. Apollo provides company matching as part of its enrichment from $49/mo.
Example Usage
A RevOps team has 8K company records with inconsistent naming. They search Google for each company name via Scavio, extract the top result's displayed company name and domain, then fuzzy-match against their CRM records. 12% of records had name variants that prevented proper account merging. Total cleanup cost: $40 (8K queries). Time: 2 hours of scripting, 30 minutes of API calls.
Platforms
Company Data Matching is relevant across the following platforms, all accessible through Scavio's unified API: