Clean and Deduplicate a Lead List
Use ProfileSpider to review, clean, tag, and deduplicate extracted leads before export. Remove irrelevant rows, check missing fields, keep source URLs, and prepare a cleaner CSV, Excel, or JSON file.
Goal
What This Workflow Is For
Clean an extracted lead list before using it for outreach, recruiting, research, or export.
Use this workflow after extracting leads, profiles, companies, or contacts with ProfileSpider and before exporting the final list.
Lead lists often contain duplicates, empty fields, irrelevant rows, repeated page elements, outdated records, or rows that need tags and notes. Cleaning the list inside ProfileSpider helps you avoid exporting messy data.
This workflow is especially useful after scraping directories, team pages, social profile sources, search results, or paginated pages where the same person or company may appear more than once.
Prerequisites
Before You Start
Confirm the page and tooling match this workflow.
Before you start, make sure you have:
- A saved ProfileSpider list with extracted leads, profiles, companies, or contacts
- Source URLs included where possible
- A clear idea of which rows should stay in the final list
- A target export format such as Excel, CSV, or JSON
- A consistent column structure if you plan to import the list into another tool
Cleaning is easiest when the list includes stable identifiers such as email, LinkedIn URL, website, company domain, or source URL.
Fit
Best For / Not Ideal For
Set expectations before you install or run an extract.
Best for
- Removing duplicate leads before export
- Cleaning extracted directory or team page data
- Preparing prospect lists for outreach
- Preparing recruiting lists before shortlisting
- Reviewing rows after enrichment or email finding
- Standardizing tags, notes, and source URLs
- Creating cleaner CSV or Excel exports
Not ideal for
- Fixing data that was never present on the source page
- Replacing manual review for high-value outreach lists
- Guaranteeing that two similar names are the same person
- Cleaning private or unauthorized data
- Large CRM hygiene projects that need full database-level deduplication
Steps
Step-by-Step Workflow
- 1
Open the saved lead list
Go to the ProfileSpider list you want to clean. This could be a list created from a directory, team page, social media source, search result, or company website.
- 2
Scan for obviously irrelevant rows
Remove rows that are not useful for your workflow, such as navigation items, unrelated companies, repeated sidebar content, ads, generic page links, or non-lead records.
- 3
Check key identifiers
Review fields that help identify duplicates: email, LinkedIn URL, website, domain, company name, person name, and source URL.
The strongest deduplication keys are usually exact emails, exact LinkedIn URLs, exact company domains, or exact website URLs.
- 4
Review likely duplicates
Look for rows that appear to describe the same person or company. Check whether names, companies, profile URLs, websites, and source URLs match before deleting anything.
- 5
Standardize tags and notes
Use tags and notes to make the final list easier to filter later. Examples include client names, campaign names, region, source type, role, status, or priority.
- 6
Export the cleaned list
After reviewing the list, export it as CSV, Excel, or JSON. Keep source URLs in the export so each row can be traced back to the original page.
Schema
What ProfileSpider Extracts
Default fields for this workflow. Add or remove columns before you extract.
- NameUse person or company names to review likely duplicates, but do not rely on name alone.
- CompanyUseful for grouping people by account or checking whether similar profiles belong to the same organization.
- EmailA strong deduplication key when available because exact email matches usually identify the same contact.
- LinkedIn URLA strong person-level identifier when the exact profile URL is present.
- WebsiteUseful for company-level deduplication, especially when multiple listings refer to the same domain.
- DomainA normalized company domain can help group companies even when names are written differently.
- TagsUse tags to segment cleaned rows by campaign, source, client, region, role, or status.
- NotesUse notes for manual review comments, qualification status, or follow-up instructions.
- Source URLHelps verify where a row came from and identify repeated extraction sources.
Output
Example Output
What a downloaded file looks like. Real exports are saved as .csv, .xlsx, or .json.
| Name | Title | Company | Website | Tags | Notes | Source | ||
|---|---|---|---|---|---|---|---|---|
| Sofia Martin | Head of People | Northstar Talent | northstartalent.com | linkedin.com/in/sofiamartin | sofia@northstartalent.com | recruiting, reviewed | Keep - target account | example-directory.com/recruiting-agencies |
| Daniel Weber | VP Sales | Weber Growth | webergrowth.io | linkedin.com/in/danielweber | daniel@webergrowth.io | sales-lead, reviewed | Duplicate removed from second source | example-marketplace.com/b2b-consultants |
| Nina Verhoeven | Founder | ExampleTech | exampletech.com | linkedin.com/in/ninaverhoeven | founder, needs-email | Find email before outreach | conference-site.com/sponsors |
Troubleshooting
Common Problems
Two rows look similar but not identical
Check stronger identifiers before deleting anything: email, LinkedIn URL, company domain, website, and source URL. Similar names are not always the same person.
The list has many empty fields
Empty fields usually mean the source page did not expose that data. Keep useful rows, enrich missing details where available, or remove columns that are not needed for the final export.
The same company appears with different names
Use website or domain as the main company identifier. Company names can vary across directories, marketplaces, and social profiles.
The export still looks messy
Use a template with a consistent column structure. Keep only columns that matter for your next step, such as Name, Company, Title, Email, LinkedIn, Website, Tags, Notes, and Source URL.
I am not sure which rows to delete
When in doubt, tag rows for review instead of deleting them immediately. You can export only reviewed or qualified rows later.
Questions