1
Read and validate the CSV rows
The importer detects supported name and domain headers, keeps the original row data, and rejects unsupported file types before a long-running job is created.
Email Find Tools
Bulk Email Finder for Names and Company Domains
Upload a CSV, find one verified work email for each matched person, and download an enriched file. Rows without a reliable match are returned without a Finder charge.
Enrich a list with work emails
Upload a CSV with a person’s name and company domain on each row. BillionVerify groups the work by domain, searches progressively, and preserves the original rows in the result file.
Up to 64 MiB and 200,000 data rows. Headers are detected automatically.
Download sample CSV- 10 credits for each person with a match. Rows without a match are free.
- Every returned email is already verified. Verification is included at no extra cost.
A bulk email finder fills missing work emails across a CSV
Bulk Email Finder is the list-scale version of a person-level email finder. Each input row identifies a person and company domain; each successful output row receives one best work email, confidence, verification status, and evidence. The result remains aligned with the original file so it can return to a CRM, recruiting system, lead database, or review queue.
This workflow is designed for lists where identity is already known but the email field is empty. It does not replace email extraction from unstructured text, domain-wide company discovery, or verification of addresses already present in the file. Those are separate tools because their inputs, outputs, and billing units are different.
Bulk discovery also should not mean bulk guessing. BillionVerify searches by company domain, reuses domain-level evidence across people at the same organization, verifies each returned best match, and leaves unmatched rows uncharged instead of filling the file with low-confidence patterns.
How Bulk Email Finder processes an email discovery list
The job keeps row identity stable while sharing company-level discovery work wherever possible.
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Group contacts by company domain
People at the same company share domain-level evidence and public-site discovery. Grouping avoids treating every row as an unrelated website search while each person still receives an individual candidate evaluation.
3
Find and verify one best match per person
The search expands automatically for unresolved rows, tests likely work-email candidates, and includes mailbox verification in the Finder result rather than charging a second verification fee.
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Download an enriched result CSV
The output preserves every source row and appends match, confidence, status, and evidence fields. Unmatched rows remain visible for correction or later review and do not incur a Finder charge.
What the enriched CSV contains
A result file must remain auditable after it leaves the finder, so the match and the evidence travel with the source row.
One work email per matched person
Each successful row receives one best-match professional address. The output does not multiply one source record into a confusing list of unranked email guesses.
Confidence and verification fields
The CSV distinguishes the selected address, confidence score, verification conclusion, status, and evidence summary so downstream teams can define their own acceptance rules.
Original columns and row order
Source fields remain available beside the enrichment output. That makes it possible to join results back to an account, campaign, owner, territory, or external record identifier.
Job-level progress and billing totals
The product reports total rows, processed rows, matches found, unique domains, domains searched, reserved credits, and final credits charged before the result file is downloaded.
Prepare a CSV that produces usable email finder results
Most bulk errors begin before upload. A stable schema and clean identity inputs reduce ambiguous searches and make the output easier to review.
1
Use one person and one company domain per row
Keep the person’s name and current company domain in distinct columns. Do not put several people in one cell, mix company names with domains, or use a LinkedIn profile as the company website.
Include a stable source ID when the file will return to another system. The result can then be joined back without relying on names, which may be duplicated or formatted differently.
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Preserve unmatched rows instead of deleting them
A no-match result can reveal a wrong domain, a recent employer change, an unsupported name, a company without mail routing, or evidence that never reached the confidence threshold. Keeping the row makes those cases reviewable.
Because unmatched rows do not incur the 10-credit Finder charge, there is no need to replace them with weak guesses merely to make the output look complete.
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Separate discovery thresholds from campaign rules
The Finder result explains whether it found and verified a best match. Your sending workflow still decides which confidence bands, caveats, job titles, regions, and contact purposes are acceptable.
Store the verification and caveat columns instead of importing only the email. If a catch-all warning is discarded, downstream users may interpret an uncertain candidate as a confirmed mailbox.
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Download once, then validate the downstream import
Inspect row counts, matched counts, unmatched counts, and a sample of joined IDs before updating a production CRM. A successful finder job does not guarantee that a separate importer mapped every output column correctly.
If the source file already contains emails and your goal is deliverability, use bulk email verification or email list cleaning instead. Discovery should not overwrite a known address without an explicit reconciliation rule.
Lists that benefit from bulk work-email discovery
Use bulk discovery when every row names a person and organization but manual email research would be too slow.
Conference and event attendee lists
Enrich a permissioned attendee, speaker, sponsor, or exhibitor list when names and employers are present but professional emails are missing.
CRM migration and data repair
Fill missing work-email fields while retaining source IDs and owners, then route uncertain or unmatched rows to a separate cleanup queue.
Account-based prospecting
Prepare named buying-committee contacts across a target-account list without running the same company-domain research manually for every person.
Recruiting and talent operations
Add professional contact fields to a candidate research list while keeping company identity, verification evidence, and unmatched outcomes explicit.
Bulk Email Finder compared with adjacent email tools
Choose based on the shape of the source data, not the number of rows alone.
| Tool | You provide | You receive | Use it when |
|---|---|---|---|
| Email Verifier | One complete email address | SMTP deliverability and risk signals | The address already exists and needs a sendability decision |
| Email Finder | One name and company domain | One verified best-match work email | You are researching one important person |
| Bulk Email Finder | CSV rows with names and company domains | Enriched CSV with one match per person | Many named records need missing work-email fields |
| Company Search | One domain and maximum result count | Verified public email addresses from that company | The company is known but the people are not |
Bulk discovery limits that protect data quality
A bulk tool should make large jobs easier without pretending that every row is equally searchable.
CSV is the supported upload format
The current product accepts CSV files up to 64 MiB and 200,000 data rows. Spreadsheet formulas, multiple worksheets, and PDF contact lists should be exported or transformed first.
Each row needs a usable person and domain
Names without a company domain are ambiguous, and domains without a named person belong in Company Search. Unsupported inputs remain visible rather than silently changing product behavior.
A match is one conclusion, not every possible permutation
Bulk Email Finder returns one selected work email per person. Candidate attempts are evidence used to reach that conclusion, not a collection for indiscriminate sending.
Found does not mean permission to send
The output still requires a relevant purpose, suppression checks, audience rules, and the sender’s own compliance process before it enters outreach.
Standards that make bulk email data portable
The finder adds product-specific fields, while established specifications define the CSV exchange format and the email and mail-routing concepts inside the result.
Describes the common comma-separated value format, including records, fields, headers, quoting, and embedded line breaks.
Defines SMTP and mail exchanger behavior used when evaluating whether a discovered company address can receive email.
Defines mailbox address syntax and the local-part plus domain structure carried in result fields.
Documents structured organization properties that public company pages may expose during domain-level discovery.
Choose the next list workflow
The right adjacent page depends on whether the list is missing addresses or already contains them.
Email Finder
Research one named person when a CSV job is unnecessary.
Company Search
Discover public company contacts when the source list contains domains but no people.
Bulk Email Verification
Validate a file that already contains email addresses instead of searching for missing ones.
Email List Cleaning
Classify and remove risky, invalid, disposable, role-based, and other unwanted addresses from an existing list.
Bulk Email Finder questions
1. What columns does a bulk email finder need?
Each row needs a person’s name and company domain. The importer can detect supported name and domain headers, and a stable source ID is recommended when results will be joined back to another system.
2. How many rows can I upload?
The current Bulk Email Finder accepts CSV files up to 64 MiB and 200,000 data rows. Use the downloadable sample to confirm the expected structure before preparing a large job.
3. How does bulk email finder pricing work?
Each person with a returned best match costs 10 credits. Rows without a reliable match cost zero. Verification of the returned work email is included and is not charged again.
4. Does the output keep unmatched rows?
Yes. The result preserves source rows so no-match cases can be corrected, reviewed, or imported with a clear status instead of disappearing from the file.
5. Is Bulk Email Finder the same as bulk email verification?
No. Bulk Email Finder starts with names and company domains to discover missing work emails. Bulk email verification starts with complete email addresses and evaluates their deliverability and risk.
6. Are the found emails verified?
Yes. Every returned best match includes verification in the Finder price. Confidence, verification status, evidence, and caveats remain available for downstream review.
7. Can I upload a list of company names without domains?
No. Company names can be ambiguous, so the current workflow requires domains. Resolve each organization to its official domain first, or use Company Search one domain at a time when no named contacts are available.
Bulk Email Finder
Turn a list of names into verified work emails
Upload a structured CSV, preserve every row, and pay only for people who receive a reliable best match.
10 credits per matched person · Verification included · Unmatched rows are free