How Account Matching Works
Understand how RevenueProven matches LinkedIn-engaged companies to your CRM records without cookies.
Account matching is the step that links a company engaging with your LinkedIn Ads to the corresponding account in your CRM. It is what turns a list of engaged organizations into an attribution view tied to real pipeline. Revenue Proven matches in two phases, domain-first with a name-based fallback, and this page explains how each works and how to improve your match rate.
Domain-first matching
The primary and highest-confidence method is matching on company domain. Revenue Proven normalizes the website on each engaged LinkedIn organization and the website on each CRM account — stripping the protocol, any leading www, and trailing paths — and compares the normalized values. Because the normalized domain is precomputed and indexed, this comparison is fast even across large account sets, and a clean domain on both sides produces an unambiguous match.
Name-based fallback
When an engaged company has no usable domain or its domain does not match any CRM account, Revenue Proven falls back to comparing company names. This fuzzy step scores name similarity to catch accounts that are clearly the same organization despite small formatting differences. Name matching is inherently less certain than domain matching, so it is used only to recover accounts the domain pass could not resolve.
Handling unmatched companies
Some engaged companies will not match anything in your CRM, either because there is genuinely no account for them or because the data needed to match is missing. By default, unmatched companies are hidden from attribution views so the numbers reflect known accounts, but you can choose to show them when you want to see the full engaged universe.
- Keep the website or domain field populated and correct on your CRM accounts — this is the single biggest driver of match rate.
- Use the primary corporate domain rather than a regional or campaign-specific one where possible.
- Review the unmatched list periodically to spot accounts that should exist in the CRM but do not yet.
A high match rate is mostly a function of clean CRM data, so a little domain hygiene pays off directly in attribution accuracy.