Person Engagement Signal

The person_engagement signal monitors LinkedIn for posts and/or mentions from specific people, extracts the users who liked or commented on that content, filters them against your Ideal Customer Profile (ICP), and scores each lead 1–3 based on fit and intent. Use this signal to capture your competitors’ audiences, track who engages with your champions, or monitor influencers in your market.

You can create multiple person_engagement signals — each targeting a different set of people or ICP. Each signal is identified by a signal_id returned on creation.

Create a person engagement signal

Request

string

required

Must be "person_engagement".

array

required

A list of LinkedIn profile URLs for the people to monitor. The system fetches each profile and extracts the LinkedIn member_id automatically. URLs that cannot be resolved are returned in unresolved_profile_urls and skipped.

[
  "https://www.linkedin.com/in/satyanadella/",
  "https://www.linkedin.com/in/williamhgates/"
]

Each URL must point to a valid public LinkedIn profile. The resolved full name and member_id are included in the response. Unresolvable URLs are reported but do not fail the request — as long as at least one URL resolves.

string

What type of content to monitor for each person.

Value	Monitors
`"posts"`	Posts published by the person
`"mentions"`	Posts where the person is mentioned
`"both"`	Both posts and mentions (default)

object

Ideal Customer Profile filter. If omitted, every engaging lead passes through unfiltered. See the ICP Filter Reference section below.

string

Only surface leads who engaged with content published within this window.Valid values: "past-24h" · "past-week" · "past-month"

array

Extra email addresses to receive the lead digest. Your registered account email is always included.

string

URL to receive qualified leads via POST after each run. See Webhooks.

string

HMAC secret for signing webhook payloads.

Response

{
  "message": {
    "signal_id": "b2d4f6a8-1c3e-4g7h-9i0j-k1l2m3n4o5p6",
    "signal_type": "person_engagement",
    "status": "active",
    "person_groups": [
      { "member_id": "ACoAABcd1234", "label": "Satya Nadella" },
      { "member_id": "ACoAAEfgh5678", "label": "Bill Gates" }
    ],
    "unresolved_profile_urls": ["https://www.linkedin.com/in/private-profile/"],
    "tracking_mode": "both",
    "icp": {
      "job_titles": ["VP Sales", "Head of Revenue"],
      "seniority_levels": ["vp", "c_level", "director"],
      "locations": ["United States", "United Kingdom"]
    },
    "email_recipients": ["user@example.com"],
    "webhook_url": "https://yourapp.com/webhooks/signals"
  }
}

string

Unique identifier for this signal. Save this — required for update and delete operations.

string

Always "person_engagement".

string

"active" after creation.

array

The resolved people — one entry per successfully fetched profile, each with the LinkedIn member_id and the person’s full name as the label.

array

Only present if one or more profile_urls could not be resolved. These profiles are not being monitored. The profile may be private, deleted, or the URL may be incorrect.

string

The tracking mode in effect: "posts", "mentions", or "both".

object

The ICP configuration, if provided.

ICP filter reference

All fields are optional. If no ICP is provided, every lead passes with a score of 1.0.

Hard filters — reject leads that don’t match

array

Accepted location strings (country names, cities, or regions). A lead passes if any value appears in their LinkedIn location.

["United States", "Canada", "London"]

array

Job titles to exclude. Seniority-aware — "Intern" excludes "Marketing Intern" but not "VP Sales".

["Intern", "Student", "Freelancer"]

array

At least one keyword must appear in the lead’s profile text.

["sales", "revenue", "B2B"]

array

Target job titles. Matching is seniority- and function-aware. Leads with confidence below 0.6 are hard-rejected.

["VP Sales", "Chief Revenue Officer", "Head of Revenue"]

array

Restrict to specific seniority bands. Leads with unclassified seniority ("unknown") always pass.Valid values: "intern" "entry" "ic" "manager" "director" "vp" "c_level" "founder" "unknown"

["vp", "c_level", "director", "founder"]

Soft filters — affect score but don’t reject

array

Target company industries. Uses semantic matching. Non-matches lower the ICP score rather than hard-rejecting.

["SaaS", "B2B Software", "Fintech"]

array

Target LinkedIn company size bands. Non-matches lower the ICP score. Must match LinkedIn’s exact size band strings:"" · "2 - 10" · "11 - 50" · "51 - 200" · "201 - 500" · "501 - 1000" · "1001 - 5000" · "5001 - 10000" · "10001+"

["51 - 200", "201 - 500", "501 - 1000"]

array

Keywords that reduce or eliminate a lead’s score if found in their profile text.

["recruiting", "hiring manager", "talent acquisition"]

Lead scoring

Each lead that passes the hard filters is scored on two dimensions: ICP Score (0.0–1.0) — average of all soft-filter scores (industries, company_size, negative_keywords). Leads with no ICP configured receive 1.0. Signal Score — based on:

Engagement type: comment = 1.0, like = 0.7
Recency: decays linearly over 14 days

Lead Score (1–3) — composite = 0.5 × icp_score + 0.5 × signal_score

Score	Threshold	Meaning
3	≥ 0.75	High-fit, high-intent
2	≥ 0.50	Good fit
1	< 0.50	Weak signal

Leads are delivered via email digest and/or webhook after each daily run.

Getting Started

Concepts

Person Engagement Signal

Person Engagement Signal

Create a person engagement signal

Request

Response

ICP filter reference

Hard filters — reject leads that don’t match

Soft filters — affect score but don’t reject

Lead scoring

​Person Engagement Signal

​Create a person engagement signal

​Request

​Response

​ICP filter reference

​Hard filters — reject leads that don’t match

​Soft filters — affect score but don’t reject

​Lead scoring

Person Engagement Signal

Create a person engagement signal

Request

Response

ICP filter reference

Hard filters — reject leads that don’t match

Soft filters — affect score but don’t reject

Lead scoring