Find LinkedIn Profiles from Names and Companies at Scale
Turn names and companies into verified LinkedIn URLs — often the missing first step in enrichment. Covers the technique, accuracy, and disambiguation.
Most enrichment providers need a LinkedIn URL as their lookup key. The problem: most lead lists don’t come with LinkedIn URLs. They come with names and company names.
This creates a gap that many teams paper over with manual LinkedIn searching — which is painfully slow at any meaningful scale.
Why LinkedIn URLs Matter as an Enrichment Input
LinkedIn profile URLs are the most reliable lookup key in B2B enrichment because:
They’re unique: There’s only one profile at /in/jane-smith-1a2b3c. A profile URL unambiguously identifies a specific person.
They’re stable: People don’t change their LinkedIn URL when they change jobs. The URL points to the person, not their employment.
They’re widely supported: Datagma, LeadMagic, Hunter.io, Apollo, and most enrichment providers accept LinkedIn URLs as a primary input key.
Without a LinkedIn URL, enrichment providers fall back to name + company matching — which is less precise, especially for common names.
The Name + Company Resolution Process
How does a name + company get resolved to a LinkedIn URL?
1. Search and filter: LinkedIn is searched for the name. Results are filtered by current employer matching the company name.
2. Company disambiguation: For large companies (Google, Salesforce, Microsoft), filtering by company name returns hundreds of candidates. Additional signals — title keywords, geography, profile completeness — are applied to narrow down.
3. Confidence scoring: The closest match is returned with a confidence score reflecting how strongly the result matches the input. Common names at large companies score lower than uncommon names at unique companies.
4. Fallback matching: If no direct match is found, the system may try domain-based matching (company website domain → LinkedIn company page → employee search) or email pattern guessing.
Accuracy Expectations by Input Quality
| Input | Expected Accuracy |
|---|---|
| Full name + unique company name | 85–92% |
| Full name + large/common company | 65–75% |
| Full name + company + title hint | 88–94% |
| Full name + company + location | 87–93% |
| Common name + any company | 55–70% |
How to improve accuracy: Add more context. Middle initial, title, department, or location significantly reduce ambiguity. Most lead lists have at least title available — always include it.
Handling Disambiguation
Common names are the hardest case. “John Smith at Salesforce” could be dozens of LinkedIn profiles. The disambiguation approach:
Add title: If you know the person is a VP of Sales, filter for LinkedIn profiles with “VP” or “Sales” in the title field.
Add location: If you know the company’s HQ or the person’s likely metro area, geographic filtering eliminates most duplicates.
Add email pattern: If you have an unverified email guess ([email protected]), you can use the email pattern as a secondary verification signal — look for LinkedIn profiles where the email pattern matches known contacts at the company.
Flag for manual review: Low-confidence matches (below 60%) should be flagged for spot-check rather than auto-accepted. One human review per 20 flagged records usually takes 10–15 minutes and catches most mismatches.
The Full Pipeline
Name + company resolution typically sits in the middle of a larger enrichment pipeline:
Input: Conference attendee list
(Name + Company + Title)
↓
Step 1: Name → LinkedIn URL resolution
↓
Step 2: LinkedIn URL → Full profile scrape
(current role, company, location, skills)
↓
Step 3: LinkedIn URL → Email + phone enrichment
(via Datagma, LeadMagic, etc.)
↓
Output: Fully enriched contact listEach step has its own coverage rate. If Step 1 resolves 80% of names to URLs, and Step 3 finds emails for 70% of resolved profiles, the combined pipeline produces verified contact details for approximately 56% of the original list. The remaining 44% require manual research or remain as partial records.
When to Skip LinkedIn URL Resolution
If your enrichment provider accepts name + company directly (without needing the LinkedIn URL), you can skip the resolution step. Most providers do support name + company matching, but accuracy is typically lower than URL-based lookups.
The resolution step adds value when:
- You need profile data (experience, title, skills) in addition to contact details
- Your provider’s name + company lookup accuracy is notably lower than URL lookup
- You want to use the LinkedIn URL for Sales Navigator imports or CRM linking
Output Format
The output of a name → LinkedIn URL resolution should include:
| Column | Content |
|---|---|
| Input Name | Original name from your list |
| Input Company | Original company from your list |
| LinkedIn URL | Resolved profile URL |
| Confidence Score | Match confidence (0–100) |
| Matched Title | Title found on the matched profile |
| Matched Company | Company found on the matched profile (should match input) |
| Review Flag | TRUE if confidence < threshold |
The matched title and company columns serve as a sanity check — if the matched title is completely unrelated to the expected role, the match may be wrong even if the company matches.
Resolve your contact list to LinkedIn URLs → LinkedIn Profile Finder from Names & Companies →