The Fastest Way to Get LinkedIn Profiles at Scale From Names, Emails, or Any Raw Data

‍

‍

If you work in outbound or data operations, you already know the real bottleneck: you rarely get all the data you actually need.

Sometimes you only have a name and a company. Sometimes it’s a work email from a legacy CRM export. Sometimes it’s a Twitter profile or a job title scraped from a careers page.

‍

No LinkedIn URL → no segmentation → no personalization → no scalable outreach.

‍

Crona solves this with a single enricher that adapts to whatever data you already have: whether it’s clean, incomplete, or inconsistent, and reconstructs the missing details needed to return the correct LinkedIn profile.

‍

In practice, this means you can upload almost anything: names, companies, domains, work emails, Twitter profiles, job titles, locations, or any combination of them. Crona evaluates available signals, identifies the most probable company and identity, and produces a validated LinkedIn URL at scale.

Here’s how to get to the right LinkedIn profiles in a couple of minutes, depending on the data you already have.

‍

Supported Input Types

‍

Think of this as a spectrum: from the cleanest inputs (name + company) to the messiest (single email field).

Crona handles all of them.

‍

‍

More input signals = higher accuracy.

‍

Workflow

‍

1. Sign up to Crona https://app.crona.ai/sign-up (you get 1000 free credits)

2. Upload your CSV (any structure is fine: names, emails, titles, or a mix).

3. Map whatever fields you have.

4. Run the workflow.

5. Download a fully enriched dataset with verified LinkedIn URLs.

That’s all.

‍

‍

Use Cases

‍

1. Cleaning a messy CRM export

You have thousands of contacts with only emails or inconsistent names.

Crona reconstructs identities and returns verified LinkedIn URLs so you can segment and run outreach without manual cleanup.

‍

2. Preparing ICP lists for outbound

You upload names + companies. Crona fills in LinkedIn profiles, titles, domains, and validates whether the person still works there.

‍

3. Researching stakeholders inside target accounts

You only know the role (e.g., Head of Procurement at a specific company). Crona finds the person, their LinkedIn, and full metadata.

‍

4. Converting Twitter audiences into B2B leads

Useful for founders, engineers, crypto/web3 players.

Upload Twitter URLs → get matched LinkedIn profiles and work emails.

‍

5. Enriching lists from job boards or directories

You have title + company + location.

Crona identifies the correct employees and returns verified LinkedIn URLs for each.

‍

6. Validating old datasets before outreach

The person left the company? Title outdated?

Crona corrects these fields automatically and prevents mis-targeted outreach.

‍

FAQ

‍

How accurate is the LinkedIn matching?

Accuracy depends on the number and quality of input signals.

More data (name + company + email) = higher precision.

Even with minimal inputs like email-only, Crona reconstructs a correct profile in most cases.

‍

What if LinkedIn is not found?

You’ll see NOT_FOUND. You can manually check those cases if needed.

‍

Can I run this on 10k+ rows?

Yes. But we recommend testing 50–100 rows first, then run the entire dataset.

‍

Is this the same as Clay’s person lookup?

No. Crona uses multi-signal matching, domain reconstruction, and validation logic that adapts to incomplete datasets, not only clean inputs.

‍

Can Crona find a profile if I only have a work email?

Yes. The algorithm extracts the domain → determines the company → reconstructs the name → matches LinkedIn.

‍