ACTION_ID: person_enrich_using_apollo NAME: Apollo: Person Enrich CATEGORY: scrape CREDITS: 1.4-8.4 Enrich a person's profile with data sourced from Apollo. Given any combination of identifying signals (name + company, email, or LinkedIn URL), the action returns a broad set of person and employer attributes, including: - LinkedIn URL - Phone number (optional — only returned if unlock_phone_numbers is set to "Yes"; phone enrichment may take several minutes) - Location (city, state, country) - Job title, headline, seniority, departments - Current and historical employment history - Current company name + domain + firmographics (industry, headcount, revenue, funding, technologies, etc.) - Other social profiles (Twitter, GitHub, Facebook) Use it as a richer alternative when the leaner Floqer-native person_enrich_by_floqer (emails + phones only) doesn't have the breadth of attributes you need. INDEX: 1. Inputs 2. Outputs 3. How to configure 4. Key notes 5. Where it fits in a workflow 6. When to use 7. When not to use ================================================================================ 1. INPUTS ================================================================================ first_name (type: string, optional) — First Name First name of the person. last_name (type: string, optional) — Last Name Last name of the person. full_name (type: string, optional) — Full Name Full name. Use this if you're not using First Name and Last Name separately. email (type: email, optional) — Email The person's email address. company_name (type: string, optional) — Company Name The person's employer (current or previous). company_domain (type: url, optional) — Company Domain The domain for the person's employer (current or previous). Do not include the @ symbol. linkedin_url (type: url, optional) — LinkedIn URL LinkedIn URL of the person. unlock_phone_numbers (type: string, optional) — Unlock Phone Numbers Phone-number enrichment may take several minutes. Allowed values: - "Yes" (consumes 7 additional credits, if found) - "No" (default) Use the dedicated phone waterfall (personal_phone_number_by_linkedin_url_waterfall) for phone enrichment in new workflows — see KEY NOTES. ================================================================================ 2. OUTPUTS ================================================================================ first_name (type: string) — First Name First name of the person. last_name (type: string) — Last Name Last name of the person. person_name (type: string) — Person Name Full name as Apollo records it. person_linkedin_url (type: url) — Person LinkedIn URL LinkedIn URL of the person. person_title (type: string) — Person Title Current job title. person_city (type: string) — Person City City. person_state (type: string) — Person State State / region. person_country (type: string) — Person Country Country. person_twitter_url (type: url) — Person Twitter URL Twitter profile URL. person_github_url (type: url) — Person Github URL GitHub profile URL. person_facebook_url (type: url) — Person Facebook URL Facebook profile URL. person_headline (type: string) — Person Headline LinkedIn-style headline. company_id (type: string) — Company ID Apollo's internal ID for the person's current company. person_contact_info (type: raw_array) — Person Contact Info Apollo's full contact-info blob for this person. Includes contact metadata (roles, stage, owner, source), CRM linkage IDs (Salesforce, HubSpot), email status / sources / unsubscribe state, an array of contact_emails (each with email, status, source, confidence), and an array of phone_numbers (each with raw_number, sanitized_number, type, status, dnc flags). Use raw_to_structured_array or format_data_using_js_expression to extract specific nested fields for downstream steps. company (type: raw_array) — Company Apollo's full firmographic blob for the person's current company. Includes identifiers (id, linkedin uid, website, logo, crunchbase), classification (industry, industries, keywords, technologies), location (raw / street address, city, state, postal_code, country), size and finances (employee count, annual revenue, total funding, funding rounds), and org-chart metadata. Treat as nested JSON — pass as-is or extract specific fields with format_data_using_js_expression. employment_history (type: raw_array) — Employment History Work history. Each entry exposes: id, kind, title, organization_name, organization_id, start_date, end_date, current, description, raw_address, degree, major, grade_level, updated_at. departments (type: raw_array) — Departments High-level functional departments the person belongs to (e.g. "engineering", "sales"). sub_departments (type: raw_array) — Sub-Departments Sub-department breakdown. functions (type: raw_array) — Functions Functional roles attached to the person. seniority (type: string) — Seniority Seniority level (e.g. "manager", "director", "vp", "c_suite"). revealed_for_current_team (type: string) — Revealed For Current Team "true" / "false" indicating whether the contact has already been revealed for your team's Apollo account (affects credit usage on subsequent pulls). phone_numbers (type: raw_array) — Phone Numbers Array of phone numbers for the person. Each entry exposes raw_number, sanitized_number, type, position, status, dnc_status, dnc_other_info, and dialer_flags. ⚠ Only populated if the unlock_phone_numbers input is set to "Yes". With unlock_phone_numbers = "No" (the default), this field will be empty — Apollo's standard response does not include phone data without the unlock. ================================================================================ 3. HOW TO CONFIGURE ================================================================================ Configure Action body: { "inputs": { "first_name": "{{input.first_name}}", "last_name": "{{input.last_name}}", "company_name": "{{input.company_name}}", "linkedin_url": "{{input.linkedin_url}}", "unlock_phone_numbers": "No" } } Pass at least one identifying signal: an email, a LinkedIn URL, or the name + company combination (first_name + last_name + company_name or company_domain). All identifying inputs are individually optional but the action needs at least one to identify the person. Leave `unlock_phone_numbers` at `"No"` by default — for phone enrichment, use the dedicated phone waterfall instead (see KEY NOTES). ================================================================================ 4. KEY NOTES ================================================================================ - Phone enrichment: prefer the dedicated phone waterfall (personal_phone_number_by_linkedin_url_waterfall) — broader provider coverage and better hit rates than this action's unlock_phone_numbers flag. Use unlock_phone_numbers only as a fallback, e.g. when the phone waterfall returns "no data found". ================================================================================ 5. WHERE IT FITS IN A WORKFLOW ================================================================================ Pattern (name + company -> LinkedIn URL -> profile -> email): you have first_name, last_name, and company_name as sheet inputs and need to enrich up to a real outreach contact. Apollo resolves the LinkedIn URL and core person fields, the LinkedIn scrape fills in profile depth (employment history, location, headline), and the work-email waterfall produces a verified email. input (first_name + last_name + company_name) -> person_enrich_using_apollo (resolves person_linkedin_url) -> enrich_person_linkedin_profile (richer profile / employment history / location) -> person_work_email_waterfall (work email) -> outreach. ================================================================================ 6. WHEN TO USE ================================================================================ Use person_enrich_using_apollo for Apollo's person + company contact data including unlocked phones. Use it when you only have a person's first and last name and company name, and you'd like to find their LinkedIn URL. ================================================================================ 7. WHEN NOT TO USE ================================================================================ Need PDL person data -> person_enrich_using_people_data_labs (https://floqer.com/docs/action-detail/person_enrich_using_people_data_labs.txt) You already have a LinkedIn URL and only need employment history or location data -> enrich_person_linkedin_profile (https://floqer.com/docs/action-detail/enrich_person_linkedin_profile.txt) Apollo is the heavier, multi-source enrichment path; if your goal is just work history / city / state / country and you've already got a LinkedIn URL, the LinkedIn profile scrape is the leaner and cheaper way to get those fields. ================================================================================ This file is maintained manually. Last updated: 2026-05-01. Full interactive reference: https://floqer.com/docs/reference Action catalog: https://floqer.com/docs/action-catalog.txt