Apollo Bulk Enrichment

Turn a list of emails or domains into full profiles in minutes. Enrich contacts and companies in bulk without manual lookups.

Data enrichmentList buildingCRM hygieneData operations

The Challenge

You have a list of contacts from an event, a CSV export, or a CRM dump — but half the records are missing job titles, phone numbers, or company data. Manually looking up each person in Apollo takes 2-3 minutes per contact. With a list of 50+ people, you are looking at hours of copy-paste work just to fill in the blanks.

What This Prompt Does

Person Enrichment

Get job title, email, phone, and LinkedIn for each contact

Company Enrichment

Get industry, revenue, funding, and tech stack for each company

Structured Output

Results compiled into clean tables ready for export or CRM import

Error Tracking

Clear reporting on which entries were found vs. not found

The Prompt

The Prompt

Task

Enrich a list of contacts or companies in bulk using Apollo. The user provides a list of emails, names with companies, or company domains. For each entry, enrich with full profile data and compile results into an export-ready format.

Input

The user provides one of:

  • A list of email addresses
  • A list of names with their company names
  • A list of company domains
  • A mix of the above

Example:

  • "sarah@stripeName it "stripe" and call it with @stripe.com, john@notionName it "notion" and call it with @notion.so, lisa@figmaName it "figma" and call it with @figma.com"
  • "Sarah Chen at Stripe, John Smith at Notion"
  • "stripe.com, notion.so, figma.com"

Context

Workflow

For people enrichment:

  1. For each person in the list, use @Apollo/Enrich PersonName it "Apollo/Enrich Person" and call it with @Apollo/Enrich Person with their email, name, or LinkedIn URL
  2. Extract: full name, job title, seniority, department, email, phone number, LinkedIn URL, and company name
  3. Compile all results into a structured table

For company enrichment:

  1. For each company in the list, use @Apollo/Enrich CompanyName it "Apollo/Enrich Company" and call it with @Apollo/Enrich Company with their domain
  2. Extract: company name, industry, employee count, revenue, funding, tech stack, and headquarters
  3. Compile all results into a structured table

For mixed lists:

  1. Identify whether each entry is a person or company
  2. Route to the appropriate enrichment tool
  3. Compile results into separate tables for people and companies

What to Extract

Person Profiles:

  • Full name
  • Job title and seniority level
  • Department
  • Email address (verified)
  • Phone number (if available)
  • LinkedIn URL
  • Current company and company domain

Company Profiles:

  • Company name and domain
  • Industry
  • Employee count
  • Revenue range
  • Total funding raised
  • Headquarters location
  • Tech stack highlights

Error Handling

  • If a person or company is not found, note it as "Not found" in the results
  • If partial data is returned, include what is available and flag missing fields
  • Track success rate (found vs. not found)

Output

Enrichment Results Total processed: [count] | Found: [count] | Not found: [count]

People:

| Name | Title | Company | Email | Phone | LinkedIn | |------|-------|---------|-------|-------|----------| | [name] | [title] | [company] | [email] | [phone] | [url] |

Companies:

| Company | Industry | Employees | Revenue | Funding | HQ | |---------|----------|-----------|---------|---------|-----| | [name] | [industry] | [count] | [range] | [total] | [location] |

Not Found: List of entries that could not be enriched, with possible reasons (e.g., email not in Apollo database, domain not recognized).

Example Usage

Try asking:

  • "Enrich these emails: sarah@stripe.com, john@notion.so, lisa@figma.com — get their titles and phone numbers"
  • "I have a list of 10 company domains from a conference. Enrich each with employee count, revenue, and funding data."
  • "Enrich Sarah Chen at Stripe, John Smith at Notion, and Lisa Park at Figma — give me full profiles"