How it works
Why normalize
CSV imports quickly create duplicates when LinkedIn URLs are not standardized.
n8n recipe
Import a CSV prospect list without creating LinkedIn duplicates.
This recipe starts from a CSV file, cleans required fields, and creates leads in Yadulink with an idempotency key.
What the workflow covers
Nodes and logic
This page describes the recipe publicly; importable JSON files remain protected by API access.
Input
Validate name, company, role, email, and LinkedIn URL.
Reject rows without a usable identifier.
Normalize
Clean LinkedIn URLs and text fields.
Remove tracking parameters and spaces.
Create
Create leads with an idempotency key.
Source: `csv-import` + profile/email hash.
Verified facts
What the tool should clarify before being used.
Use caseUseful for migrating an event list, CRM export, enriched file, or manual sourcing.
Expected outputRead CSV from n8n.
Method proofReject rows without a usable identifier.
Verification method
How to turn the template into an actionable step.
- 01 Input Reject rows without a usable identifier.
- 02 Normalize Remove tracking parameters and spaces.
- 03 Create Source: `csv-import` + profile/email hash.
How it works
Quality before volume
Import fewer leads if needed, but keep the fields that enable contextual follow-up.
