ACTION_ID: get_employees_by_company_using_sales_navigator NAME: Sales Nav: Find Employees at Company CATEGORY: enrich CREDITS: 25 credits per page of 25 employees Find employees at a target company using LinkedIn Sales Navigator as the data source. Returns a structured array of employee records with the person's name, current title, headline, summary, location, LinkedIn URL (both Sales Nav and flagship forms), profile picture, connections, skills, employer + employment history, education background, twitter handle, languages, and pronoun. Capped at the configured number of pages (25 employees per page). Same broad shape as get_employees_by_company_using_apollo and get_employees_by_company_using_floqer_native, with similar filtering knobs. The difference is the data source — Sales Navigator — and the cost: this action is significantly more expensive per employee. Reach for it only when Sales Nav coverage, freshness, or seniority/function classification is what you specifically 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 ================================================================================ number_of_pages (type: number, required) — Number of Pages Number of pages to fetch. Each page returns up to 25 employees. Default 1. ⚠ Cost is per page, not per employee — see KEY NOTES. company_linkedin_url (type: string, optional) — Company Linkedin URL Current company LinkedIn URL. current_title (type: string, optional) — Current Title Filter on the person's current job title. past_title (type: string, optional) — Past Title Filter on titles the person has held in the past. company_headquarters (type: string, optional) — Company Headquarters Filter on the headquarters location of the person's company. region (type: string, optional) — Region Filter on the geographical region of the person. seniority_level (type: string, optional) — Seniority Level Multi-select filter for seniority. The value sent is a JSON array of one or more level names from the allowed list (names used verbatim — Sales Nav has no separate IDs): "Owner / Partner", "CXO", "Vice President", "Director", "Experienced Manager", "Entry Level Manager", "Strategic", "Senior", "Entry Level", "In Training". Example value: ["CXO", "Vice President", "Director"]. years_of_experience (type: string, optional) — Years of Experience Multi-select filter for total career experience. JSON array of one or more values from: "Less than 1 year", "1 to 2 years", "3 to 5 years", "6 to 10 years", "More than 10 years". function (type: string, optional) — Function Comma-separated function or role of the person (e.g. "accounting, administrative, business development, consulting"). past_company (type: string, optional) — Past Company Filter on past companies the person has worked for. company_type (type: string, optional) — Company Type Multi-select filter for company type. JSON array of one or more values from: "Public Company", "Privately Held", "Non Profit", "Educational Institution", "Partnership", "Self Employed", "Self Owned", "Government Agency". exclude_current_company (type: string, optional) — Exclude Current Company Exclude people whose current company matches this filter. exclude_current_title (type: string, optional) — Exclude Current Title Exclude people whose current title matches this filter. exclude_past_title (type: string, optional) — Exclude Past Title Exclude people whose past titles match this filter. exclude_company_headquarters (type: string, optional) — Exclude Company Headquarters Exclude people whose company HQ matches this filter. exclude_region (type: string, optional) — Exclude Region Exclude people in the matching region. exclude_seniority_level (type: string, optional) — Exclude Seniority Level Multi-select EXCLUDE filter for seniority. Same allowed-values list as Seniority Level above. JSON array of one or more level names. exclude_function (type: string, optional) — Exclude Function Exclude people in the matching function / role. exclude_past_companies (type: string, optional) — Exclude Past Companies Exclude people who worked at the matching past companies. keywords (type: string, optional) — Keywords Free-text keyword filter. Sales Nav matches profiles containing the supplied keywords. years_at_current_company (type: string, optional) — Years At Current Company Multi-select filter for tenure at current company. JSON array from: "Less than 1 year", "1 to 2 years", "3 to 5 years", "6 to 10 years", "More than 10 years". years_in_current_position (type: string, optional) — Years In Current Position Multi-select filter for tenure in current position. Same allowed values as Years At Current Company. ================================================================================ 2. OUTPUTS ================================================================================ no_of_employees (type: number) — No. of Employees Number of employees actually returned. list_of_employees (type: structured_array) — List of Employees Array of employees found, with one entry per person. Per-row fields: - person_name (type: string) — Person Name Full name of the employee. - person_location (type: string) — Person Location Person's location (city / region / metro). - person_linkedin_url (type: url) — Person Linkedin URL Sales Nav-style LinkedIn profile URL for the person. - default_position_title (type: string) — Default Position Title Current job title at the default position. - default_position_company_linkedin_id (type: string) — Default Position Company LinkedIn Id LinkedIn company ID for the default position's company. - default_position_is_decision_maker (type: string) — Default Position Is Decision Maker Sales Nav's "decision maker" flag — "true" / "false". - person_flagship_linkedin_url (type: url) — Person Flagship LinkedIn URL Flagship LinkedIn URL (linkedin.com/in/) — preferred for downstream actions that require flagship URLs. - person_linkedin_picture (type: url) — Person LinkedIn Picture Profile picture URL. - person_headline (type: string) — Person Headline LinkedIn-style headline. - person_linkedin_summary (type: string) — Person LinkedIn Summary Profile summary / about section. - person_linkedin_connections (type: number) — Person LinkedIn Connections Number of LinkedIn connections. - related_colleague_company_id (type: string) — Related Colleague Company Id LinkedIn company ID for related-colleague matching. - person_skills (type: string) — Person Skills Skills associated with the person (string blob). - employer (type: raw_array) — Employer Employer record. Nested fields: title, company_name, company_linkedin_id, start_date, end_date. - education_background (type: raw_array) — Education Background Education history. Nested per-entry fields: degree_name, institute_name, field_of_study, start_date, end_date. - person_websites (type: raw_array) — Person Websites Personal websites listed on the profile. - person_twitter_handle (type: string) — Person Twitter Handle Twitter handle (e.g. "@johndoe"). - person_languages (type: string) — Person Languages Languages listed on the profile. - person_pronoun (type: string) — Person Pronoun Pronoun listed on the profile. - person_title (type: string) — Person Title Current title (separate from Default Position Title — same value in most cases). ================================================================================ 3. HOW TO CONFIGURE ================================================================================ Configure Action body: { "inputs": { "number_of_pages": 1, "company_linkedin_url": "{{input.company_linkedin_url}}", "current_title": "VP of Engineering", "seniority_level": ["Vice President", "Director"], "function": "engineering" } } Field-by-field: - number_of_pages Pages to fetch (25 employees per page). Required. - company_linkedin_url Target company LinkedIn URL — usually `{{input.company_linkedin_url}}`. - current_title / past_title / function / keywords / region etc. Free-text filters (single string). - seniority_level / years_of_experience / company_type / years_at_current_company / years_in_current_position Multi-select filters — pass a JSON array of allowed values verbatim (see INPUTS for allowed names). - exclude_* Same shape as the corresponding include fields, but the value list is excluded. ================================================================================ 4. KEY NOTES ================================================================================ - Cost: 25 credits per page of 25 employees. Cost is charged per PAGE, not per employee: - 3 employees returned (less than one full page) → 25 credits. - 8 employees returned → 25 credits. - 25 employees returned (one full page) → 25 credits. - 26 employees returned (two pages, second one partial) → 50 credits. - Once you cross any 25-employee boundary, the next full page is charged. Set Number of Pages thoughtfully — there is no per-employee proration. - Filter strategy: filters compound and tighten the result set — more filters means fewer matches, which can pull more pages needed to fill the page count. Start narrow, verify, then widen. - Pair with push_data_to_sheet to fan out the structured_array into individual rows on a new sheet for per-employee enrichment (email, phone, LinkedIn) before outreach. If you're using more than one employee finder in parallel (e.g. running this action alongside get_employees_by_company_using_floqer_native or get_employees_by_company_using_apollo on the same company to maximise coverage), merge the per-finder structured arrays into one with merge_employee_finder_structured_array first, then push the combined array to a sheet — that way you get a single deduped / unified row set on the new sheet rather than pushing each finder's output separately and ending up with duplicate rows. - For email enrichment downstream, pair with the dedicated email-finder waterfall (person_work_email_waterfall) — don't rely on this action for emails. ================================================================================ 5. WHERE IT FITS IN A WORKFLOW ================================================================================ Pattern (account list -> per-employee outreach): start with a list of target accounts, find the right people at each, expand into rows on a new sheet, enrich each with a work email, then send to outreach. input (target company list — Company LinkedIn URL per row) -> get_employees_by_company_using_sales_navigator (returns List of Employees as a structured_array of matched employees) -> push_data_to_sheet (one row per employee on a new sheet, with Person Flagship LinkedIn URL, name, etc. as inputs) -> person_work_email_waterfall (resolve work email per row) -> outreach. Pattern (account-level signal — count people in a function): use the No. of Employees output as a signal on the account row itself, without expanding to per-employee rows. Useful for "how many engineers does this company have?" or "do they have a head of revenue?". input (target company) -> get_employees_by_company_using_sales_navigator (with Current Title / Seniority Level / Function set to the function in question, Number of Pages set high enough to count) -> read No. of Employees as a per-account signal (filter / score on it) -> outreach prioritization. Pattern (multi-finder coverage): run multiple employee finders in parallel for maximum coverage, then merge before fanning out. input (target company) -> get_employees_by_company_using_sales_navigator (in parallel) + get_employees_by_company_using_floqer_native (in parallel) + get_employees_by_company_using_apollo (in parallel) -> merge_employee_finder_structured_array (deduplicate and combine the per-finder structured_arrays into one) -> push_data_to_sheet (one row per unique employee) -> person_work_email_waterfall -> outreach. ================================================================================ 6. WHEN TO USE ================================================================================ Use get_employees_by_company_using_sales_navigator when: - You specifically need Sales Navigator-sourced employee data — e.g. you trust Sales Nav's coverage / freshness for your ICP, or you want Sales Nav's view of seniority / function as the source of truth. - You need filter dimensions that the other employee finders don't expose: tenure (`years_at_current_company` / `years_in_current_position`), `years_of_experience`, the full set of EXCLUDE filters (`exclude_current_company`, `exclude_past_title`, etc.), or Sales Nav's own seniority taxonomy. - You want a quick employee-count signal for a function or seniority at a target company — filter to the relevant titles / levels and read No. of Employees as the answer (skip the row fan-out). - You're running a multi-finder coverage strategy alongside get_employees_by_company_using_floqer_native and / or get_employees_by_company_using_apollo (see KEY NOTES on merging). ================================================================================ 7. WHEN NOT TO USE ================================================================================ Need a cheaper, Floqer-native employee finder (no Sales Nav dependency, much lower per-employee cost) -> get_employees_by_company_using_floqer_native (https://floqer.com/docs/action-detail/get_employees_by_company_using_floqer_native.txt) Same broad shape as this action and significantly cheaper — the right default unless Sales Nav as a data source is what you specifically need. Need Apollo's per-person depth (employment history, headline, multiple social URLs) and Apollo as the data provider -> get_employees_by_company_using_apollo (https://floqer.com/docs/action-detail/get_employees_by_company_using_apollo.txt) You only need ONE specific person's contact info, not a list of employees at a company -> person_enrich_using_apollo or person_enrich_using_people_data_labs (https://floqer.com/docs/action-detail/person_enrich_using_apollo.txt) Use a person-enrich action with name + company instead of pulling the full employee list and filtering. You need a conditional / fallback search — e.g. "look for C-suite titles at this company; if there's no one at C-suite, fall back to VPs; if no VPs, fall back to Directors". This action returns a single filtered list per call and can't branch on whether the first filter found anyone -> llm_web_agents (https://floqer.com/docs/action-detail/llm_web_agents.txt) A web agent can run the conditional logic in one step ("find me the most senior person at this company in [function] — try C-suite first, then VP, then Director") and return whoever it finds. Use that instead of chaining several calls of this action with different filters. ================================================================================ This file is maintained manually. Last updated: 2026-04-30. Full interactive reference: https://floqer.com/docs/reference Action catalog: https://floqer.com/docs/action-catalog.txt