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What It Does

  • Finds email addresses for people using first/last name + company info.
  • Preserves all input columns while adding contact_email_address and contact_email_address_provider.
  • Supports template variables for flexible per-row enrichment (e.g., @first_name, @company_domain).
  • Processes data asynchronously with webhook callbacks for large datasets.
  • Handles column name conflicts automatically with numeric suffixes to avoid overwriting existing data.

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🏁 Getting Started

Waterfall Email Enrichment config screenshot
1

Connect Input Data

Attach previous node output containing columns for person and company references.
2

Map Person Reference

Select first name and last name columns using template variables (e.g., @first_name, @last_name).
3

Map Company Reference

Select either company name, domain, or both using template variables (e.g., @company_name, @domain).
4

Run Node

Execute in batch. Use Test Mode if desired to preview a small subset of results.
5

Review Outputs

Access enriched email addresses and provider information in S3 (Parquet + CSV).

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Inputs

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🛠️ Required Fields

  • Person Reference (✅)
    Contains first and last name identifiers for email lookup.
    Why it matters: Provides the primary identifiers for finding the correct email address.
  • Company Reference (✅)
    Company name and/or domain to improve email accuracy. At least one field is required.
    Why it matters: Helps disambiguate common names and improve enrichment precision.

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Output

  • Adds columns:
    contact_email_address, contact_email_address_provider, contact_email_address_status
  • Preserves all original input columns.
  • Column conflicts resolved automatically with numeric suffixes (e.g., contact_email_address_1).

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How It Works

  1. Validate settings: person and company references, template variable syntax.
  2. Connect previous node output.
  3. Resolve template variables for each row (@first_name, @last_name, @company_domain).
  4. Receive results map back to original rows.
  5. Merge enriched data with input columns and handle column name conflicts.

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🚀 Example Use Cases & Prompts

Use CaseSetup or Prompt Example
Enrich lead listUse @first_name, @last_name, and @company_domain to find emails for cold outreach.
CRM cleanupAdd missing emails to contacts for improved campaign targeting.
Multi-source contact enrichmentCombine company name + domain for better accuracy across datasets.

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✨ Pro Tips

  • Use both company name and domain when available for higher match confidence.
  • Test with a small subset in Test Mode before running large datasets.
  • Rename output columns (EmailAddress, Provider, EmailStatus) for cleaner downstream reporting.

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⚠️ Important Considerations

  • Credits are consumed per successful enrichment only. Failed lookups do not consume credits.
  • Large datasets will take considerable amount of time.

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🛠 Troubleshooting & Gotchas

SymptomLikely CauseQuick Fix
Blank contact_email_addressNo match for person/company inputVerify column mapping and template variable syntax
Unexpected _1 suffixesColumn name conflicts with inputRename outputs for clarity

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📝 FAQ

Yes — using both increases accuracy and reduces false positives.
The row remains in output with contact_email_address empty. No credits are consumed.
Test Mode processes a small subset for fast validation without consuming full credits.

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💰 Pricing

ActionCredit Cost
Successful email enrichment3 credits per row
Failed enrichment0 credits
Credits are only charged when an email address is successfully returned. Batch processing optimizes usage.

Drop this node into your Play to automatically enrich your contacts with verified email addresses—fast and at scale. 🚀