✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
Pipedrive is a sales CRM built around the pipeline view, where deals move through stages with associated contacts. Contact email addresses come from manual entry by sales reps, imports from other systems, and integrations with lead generation tools. As deals accumulate across pipeline stages, the contact database grows with entries of varying quality. dataclean.to validates your Pipedrive contact export to ensure your sales outreach, follow-up sequences, and re-engagement campaigns target deliverable addresses.
The Problem
Pipedrive's contact model allows multiple email addresses per person (work, home, other), and exports include all of them. Sales reps often enter the first email they find for a prospect, which may be an outdated address from a previous company. Contacts imported from LinkedIn Sales Navigator or other prospecting tools carry addresses that were already stale at import time. Pipedrive does not validate email addresses at entry, so addresses with typos persist through the entire sales cycle. Lost deals retain their contact information, and since Pipedrive is designed for long sales cycles, the database may contain contacts from deals that were lost years ago. Duplicate contacts appear when different sales reps add the same person independently, each with slightly different email formatting. The 'organization' field may have its own email that defaults to a generic address (info@, sales@) rather than an individual contact. Pipedrive data export guide
How to Fix It
1
Export contacts from Pipedrive
In Pipedrive, go to Contacts > People, apply filters if needed, and export as CSV. Include all email fields (work, home, other), person name, organization, deal value, and deal stage.
2
Upload to dataclean.to
Import the Pipedrive CSV. The platform validates all email columns independently, checking each address type (work, home, other) for syntax, domain health, and deliverability.
3
Identify stale deal contacts
Cross-reference email validation with deal age and status. Contacts from deals lost more than a year ago are strong candidates for outdated email addresses, especially work email addresses from companies they may have left.
4
Consolidate duplicate contacts
Find people entered by different sales reps with slight email variations. Match by name and organization to identify duplicates that should be merged in Pipedrive to avoid conflicting outreach.
5
Export validated sales contacts
Download the cleaned contact data. Update Pipedrive records with corrected emails, suppress invalid addresses, or feed the validated list into your outreach automation tool.
Frequently Asked Questions
How do multiple email fields per contact affect cleaning?
Pipedrive stores up to three email addresses per contact (work, home, other). dataclean.to validates each field independently. If a work email is invalid but the personal email is valid, both results are reported so you can decide which to use for outreach.
Should I clean lost deal contacts?
Yes, if you ever plan to re-engage them. Many sales teams revisit lost deals when circumstances change. Cleaning these contacts before re-engagement ensures your follow-up emails actually reach the person rather than bouncing.
Can I preserve Pipedrive deal stages in the cleaned data?
Yes. dataclean.to preserves all non-email columns during cleaning. Deal stage, value, organization, and custom fields remain intact, allowing you to segment your cleaned contacts by pipeline position.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.