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POST
Count database leads

Use Case:

Count matching cached leads before running a database lead search.

Pricing

This endpoint is free — it does not incur any charges.

Authorizations

Authorization
string
header
required

Use the required Token prefix. Example: Authorization: Token xxxxxxxxx

Body

application/json
job_titles
string[]

Job titles held by the people you want to find. A lead only needs to match one of the titles you provide — adding more expands your search. Results may also include similar titles (e.g. "marketing manager" can return "content marketing manager"). Combine with seniorities to target both function and level. Examples: "sales development representative", "marketing manager", "software engineer".

seniorities
string[]

Job seniority levels at the lead's current employer (current position only, not previous roles). A lead needs to match at least one; adding more values expands your search. Allowed values: owner, founder, c_suite, partner, vp, head, director, manager, senior, entry, intern. Combine with job_titles to narrow targeting.

locations
string[]

Geographic locations where leads currently live — matches across cities, states/regions and countries. A lead needs to match at least one. To filter by the employer's HQ location, use company_locations. Examples: "San Francisco, California, United States", "Germany", "London".

exclude_locations
string[]

Locations to exclude from results.

company_locations
string[]

Headquarters location of the lead's current employer; a lead is included if their company's HQ matches at least one. Filters by where the company is based — distinct from locations, which is where the lead personally lives.

exclude_company_locations
string[]

Company locations to exclude.

company_industries
string[]

Industries of the lead's current employer; a lead is included if their company matches at least one. Values follow LinkedIn's industry taxonomy. Examples: "Software Development", "Financial Services", "Information Technology".

exclude_company_industries
string[]

Company industries to exclude.

company_headcounts
string[]

Size of the lead's current employer, as employee-count ranges; a lead is included if their company falls into at least one. Allowed values: "1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10 000+".

exclude_company_headcounts
string[]

Company size ranges to exclude.

company_types
string[]

Company types: "Public Company", "Privately Held", "Non Profit", "Government Agency", "Educational", "Self Employed", "Partnership", "Self Owned".

company_name
string

Target company name (mutually exclusive with company_link and company_id).

LinkedIn company URL (mutually exclusive with company_name and company_id).

company_id
integer

LinkedIn company numeric ID (mutually exclusive with company_name and company_link).

exclude_names
string[]

Skip leads by full name.

exclude_ids
string[]

Skip leads by Sales Navigator ID.

filter_empty_vars
string[]

Skip leads where these fields are empty. Options: job_started_on, profile_photo, started_at_position, company_website.

limit_by
integer

Maximum number of leads to return. For filter-only searches (no company_id/company_link/company_name) the maximum is 2400.

offset_by
integer

Number of leads to skip (for pagination). For filter-only searches the maximum is 2399.

strict
string[]

Fields to apply strict matching on (e.g. "company_locations").

skip_truncated_names
boolean
default:false

Drop leads whose first or last name is a single character or empty. LinkedIn abbreviates surnames for members who restrict their profile, so these rows carry a name that cannot be personalised. Applies to both database and realtime search.

gender
enum<string>[]

Gender of the lead; a lead is included if it matches at least one value. Case-insensitive; any other value is rejected with 400. Gender is inferred from the lead's name, so it is an estimate, and a lead whose name does not point to one is unknown. To leave a gender out, list the others — e.g. ["female", "unknown"].

Database mode only. LinkedIn search has no gender facet, so realtime search rejects this field rather than accepting it and returning a wider result set than you asked for.

Coverage matters here: gender is known for roughly a third of leads, and the rest are unknown. Filtering by male or female therefore also drops leads whose gender simply is not known, not only those of the other gender.

Available options:
male,
female,
unknown
Example:

Response

Matching lead count

data
object
meta
object

Operation metadata returned in every data/meta response.