LinkedIn Posts

A person's posts and engagement activity on LinkedIn.

Overview

Contact LinkedIn Posts capture what individual prospects are publicly saying about their priorities, challenges, and initiatives.

We track millions of professional LinkedIn profiles, optimizing coverage by seniority, title, and account importance. Each post is analyzed to extract structured pain points, initiatives, technologies mentioned, and competitors referenced—turning unstructured social content into actionable signal.

The result: you can reference a prospect's own words in outreach, understand what they care about before the first call, and time your message to what's top of mind for them right now.

How we build and maintain coverage: Our monitoring pool is designed to maximize buyer coverage across your highest-value accounts while maintaining a well-distributed sample across geographies, industries, and company sizes.

We continuously ingest new LinkedIn profile URLs and evaluate whether we can successfully gather posts from them. We plan to roughly double the total number of contacts in our monitoring pool in the near term - expanding coverage for mid-market, SMB, and international segments.

See how coverage works →

Subtype

SignalSubtype EnumDescription
LinkedIn postlinkedinPostContact's recent posts on LinkedIn

Schema

{
  "signal_id": "5349e887-baee-4974-aa3e-02294badfa94",
  "signal_type": "linkedin-post-contact",
  "signal_subtype": "linkedinPost",
  "signal_name": "Contact posted on LinkedIn",
  "association": "contact",
  "detected_at": "2026-01-22T15:36:11.235Z",
  "contact": {
    "email": "[email protected]",
    "name": "Aditya Shankar",
    "first_name": "Aditya",
    "last_name": "Shankar",
    "job_title": "Senior Director of Marketing",
    "linkedin_url": "linkedin.com/in/aditya-shankar"
  },
  "company": {
    "name": "hosted.ai",
    "domain": "hosted.ai",
    "linkedin_url": "linkedin.com/company/hostedai",
    "description": "AI infrastructure company",
    "industries": [
      "Software Development"
    ],
    "employee_count_low": 11,
    "employee_count_high": 50
  },
  "data": {
    "post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7416003205425303552/",
    "post_text": "The inaugural AI Leadership Forum exceeded my expectation. We brought together 80 leaders across tech, infrastructure, and VC. The 'Agentic Workforce' is here. We must treat AI agents with the same rigor as FTEs.",
    "posted_date": "2026-01-11T06:29:06.850Z",
    "num_likes": 116,
    "num_comments": 4,
    "tags": [
      "Artificial Intelligence",
      "Events",
      "Digital Transformation",
      "Workforce Management"
    ],
    "summary": "Senior Director of Marketing reflects on successful AI Leadership Forum hosting 80 leaders.",
    "pain_points": [],
    "initiatives": [
      {
        "topic": "hosting AI Leadership Forum",
        "urgency": 0.9
      },
      {
        "topic": "establishing new office in HSR",
        "urgency": 0.8
      }
    ],
    "technologies_mentioned": [
      {
        "name": "AI Agents",
        "status": "using"
      },
      {
        "name": "DeepSeek",
        "status": "considering"
      }
    ],
    "competitors_mentioned": [
      {
        "name": "packet.ai"
      },
      {
        "name": "GPUaaS.com"
      }
    ]
  }
}

Field Reference

Core Fields

FieldTypeDescription
signal_idstring (UUID)Unique identifier for this signal
signal_typestringAlways "linkedin-post-contact"
signal_subtypestringAlways "linkedinPost"
signal_namestringAlways "Contact posted on LinkedIn"
associationstringAlways "contact"
detected_atstring (ISO 8601)When we detected this signal

Contact Object

FieldTypeDescription
contact.emailstringContact's email address
contact.namestringContact's full name
contact.first_namestringContact's first name
contact.last_namestringContact's last name
contact.job_titlestringContact's job title
contact.seniority_levelstringSeniority level (e.g., "senior", "head", "director")
contact.departmentstringDepartment (e.g., "Marketing", "Engineering")
contact.linkedin_urlstringContact's LinkedIn URL
contact.citystringContact's city
contact.statestringContact's state
contact.countrystringContact's country

Company Object

FieldTypeDescription
company.namestringCompany name
company.domainstringCompany website domain
company.linkedin_urlstringLinkedIn company URL
company.industriesarray[string]Industry classifications
company.employee_count_lowintegerLower bound of employee count
company.employee_count_highintegerUpper bound of employee count
company.descriptionstringCompany description

Data Object

FieldTypeDescription
data.post_urlstring (URL)Link to the LinkedIn post
data.post_textstringFull post content
data.posted_datestring (ISO 8601)When the post was published
data.num_likesintegerNumber of likes on the post
data.num_commentsintegerNumber of comments on the post
data.tagsarray[string]Gemini-generated topic tags (~300 possible values)
data.summarystringLLM-generated 10-15 word summary of the post
data.pain_pointsarray[object]Challenges or problems the contact is experiencing
data.initiativesarray[object]Projects or activities the contact is pursuing
data.technologies_mentionedarray[object]Tech products or platforms referenced
data.competitors_mentionedarray[object]Other companies referenced in the post

Pain Points Object

FieldTypeDescription
topicstringDescription of the pain point
intensityfloat (0-1)How acute the pain is expressed (higher = more acute)

Initiatives Object

FieldTypeDescription
topicstringDescription of the initiative
urgencyfloat (0-1)How immediate/active the initiative is (higher = more urgent)

Technologies Mentioned Object

FieldTypeDescription
namestringName of the technology, product, or platform
statusenumRelationship: evaluating, using, implemented, migrating_from, migrating_to, churned, considering, integrated, building_on, hiring_for

Competitors Mentioned Object

FieldTypeDescription
namestringName of the company mentioned

Example Output

"Karie - saw your post about growth marketing needing to be structured and data-informed. Totally agree that without a roadmap, you're just doing more. We've helped marketing leaders like you build that strategic framework. Would love to share what's worked."

Identity Resolution

Every contact LinkedIn post signal is pre-resolved to a business contact record with a work email. Here's how:

  1. LinkedIn profile URL captured from the post activity — this is a deterministic, unique identifier
  2. Profile URL matched against our contact database (250M+ contacts, 75M+ companies), ingested monthly with continuous updates from our pipeline exhaust
  3. Business email, job title, and company resolved from the matched record
  4. Company firmographic data (domain, LinkedIn URL, industries, headcount) attached

Key Points

  • Business emails only. The contact.email field is a professional/work email. Our domain validation excludes generic providers (gmail.com, yahoo.com, etc.). We do not deliver personal emails.
  • Match accuracy: 99.8%. We prefer no match over a false match — if we can't resolve a profile to a business contact with high confidence, the signal is not delivered.
  • Coverage: contact.linkedin_url is populated on 90-98% of signals. contact.email is populated on 85-95%.
  • No false positives from common names. LinkedIn profile URLs are deterministic unique identifiers — there is no ambiguity in the match.

Full matching guide with SQL examples: Resolution

Coverage

  • Refresh: Every 2 weeks
  • Coverage: 25-50% of contacts
  • Best for: Social selling, account-based marketing, timing outreach

How Coverage Works

Our monitoring pool balances two objectives: deep buyer coverage on your most important accounts, and broad distribution across the market.

Prioritizing hot accounts. Contacts at high-value accounts—based on account importance, seniority, and title relevance—are prioritized for monitoring. This ensures the prospects most likely to appear in your pipeline have the highest likelihood of coverage.

Sampling across segments. Beyond priority accounts, we maintain a well-distributed sample across geographies, industries, and company sizes. This prevents blind spots in underrepresented segments and ensures signal coverage scales with your market, not just your ABM list.

Continuous URL ingestion. We are constantly adding new LinkedIn profile URLs to the monitoring pool and evaluating whether we can successfully gather posts from them. Profiles that are publicly accessible and active are retained; inactive or restricted profiles are cycled out.

Pool expansion. We plan to roughly double the total number of contacts in our monitoring pool in the near term. This expansion specifically targets improved coverage for mid-market and SMB companies, international markets (EMEA, APAC), and emerging industries and verticals.