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Company LinkedIn Posts

Surface and analyze a prospect company's LinkedIn posts to identify initiatives, pain points, and engagement patterns.

Company LinkedIn Posts capture what organizations are publicly communicating about their strategy, priorities, and direction on LinkedIn.

We monitor LinkedIn company pages across 4M+ organizations, with concentration on high-value accounts in tech, enterprise, and high-growth segments. Multiple billion-dollar enterprise CRM and sales tech companies have built their entire social monitoring products on our refresh pools, validating the pool size and quality. Each post is analyzed to extract structured initiatives, pain points, technologies mentioned, and competitors referenced — turning corporate social activity into actionable signal.

The result: you know what a company is publicly prioritizing before your first call, can align messaging to their announced direction, and spot strategic shifts as they happen.

📎

See real delivered data → Sample Files

Filter by topic — This signal uses Tags Taxonomy (300+ values) rather than subtypes for topic-based filtering. Use tags alongside pain_points, initiatives, and technologies_mentioned for targeting and routing.

Example Signal

What a single entry looks like in a delivered signal file:

{
  "signal_id": "d3a82c19-5f7b-4e91-bc04-9217ad63ef80",
  "batch_id": "2026-03-15-00-00-00",
  "signal_type": "company-linkedin-posts",
  "signal_subtype": "companyLinkedinPost",
  "detected_at": "2026-03-14T09:44:12.881Z",
  "association": "company",
  "company": {
    "name": "Figma",
    "domain": "figma.com",                        // match on domain
    "linkedin_url": "linkedin.com/company/figma",  // or match on LinkedIn URL
    "industries": ["Software Development"],
    "employee_count_low": 1001,
    "employee_count_high": 2000,
    "description": "Collaborative design and prototyping platform..."
  },
  "contact": [],
  "data": {
    "summary": "Figma announces enterprise-grade admin controls and SOC 2 Type II certification, signaling push into regulated verticals...",
    "post_text": "Security isn't a feature — it's a foundation. Today we're announcing enterprise admin controls, SOC 2 Type II certification, and SCIM provisioning for teams...",
    "post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7171234567890123456",
    "posted_date": "2026-03-12",
    "num_likes": 2341,
    "num_comments": 187,
    "tags": ["enterprise security", "SOC 2", "compliance", "admin controls"],
    "pain_points": [
      { "topic": "enterprise security requirements", "intensity": 0.65 },
      { "topic": "compliance gaps in design tools", "intensity": 0.58 }
    ],
    "initiatives": [
      { "topic": "SOC 2 Type II certification", "urgency": 0.95 },
      { "topic": "SCIM provisioning rollout", "urgency": 0.82 },
      { "topic": "enterprise admin console launch", "urgency": 0.88 }
    ],
    "technologies_mentioned": [
      { "name": "SCIM", "status": "in_use" },
      { "name": "Okta", "status": "in_use" }
    ],
    "competitors_mentioned": [
      { "name": "Adobe XD" }
    ]
  }
}

Field Reference

Standard envelope and entity fields are shared across all signals — see Schema and Resolution. The fields below are specific to this signal:

Signal-Specific Fields

The data object contains everything unique to this signal type — the intelligence extracted from the company's LinkedIn post.

FieldTypeDescription
summarystringOne-line headline describing the post's strategic significance (e.g., "Figma announces SOC 2 Type II certification, signaling push into regulated verticals"). Designed to be shown directly to end users. Typically 10–20 words, always includes the company name and core announcement. Generated by analyzing the full post text
post_textstringThe original text of the LinkedIn post. May be truncated for very long posts. Useful for understanding the company's messaging tone and extracting specific claims for outreach
post_urlstring (URL)Direct link to the LinkedIn post. Useful for displaying to users who want to read the full post or verify context
posted_datestring (date)Date the post was published. Useful for recency filtering and aligning with quarterly planning cycles
num_likesintegerNumber of likes on the post at time of processing. High engagement on a company post indicates it's a priority they're actively promoting
num_commentsintegerNumber of comments on the post. High comment counts signal active market interest in the announcement
tagsarray[string]Topic tags extracted from the post content. Useful for filtering signals by theme or building topic-based account lists
pain_pointsarray[object]Challenges or gaps the company acknowledges in their post. Each entry has topic (the pain point) and intensity (0.0–1.0). Useful for identifying companies experiencing problems your product solves
pain_points[].topicstringDescription of the pain point or challenge expressed
pain_points[].intensityfloat (0.0–1.0)How strongly the pain point was communicated. Higher = more critical
initiativesarray[object]Strategic projects or priorities announced in the post. Each entry has topic (the initiative) and urgency (0.0–1.0). Useful for identifying companies actively investing in areas where you can help
initiatives[].topicstringDescription of the initiative or project
initiatives[].urgencyfloat (0.0–1.0)How time-sensitive or actively promoted the initiative appears. Higher = more immediate
technologies_mentionedarray[object]Technologies referenced in the post. Each entry has name and status (in_use, evaluating, replacing, mentioned). Useful for tech-stack enrichment and competitive intelligence
technologies_mentioned[].namestringName of the technology or platform
technologies_mentioned[].statusstringRelationship to the technology: in_use, evaluating, replacing, or mentioned
competitors_mentionedarray[object]Competitors referenced in the post. Each entry has name. Useful for competitive displacement plays
competitors_mentioned[].namestringName of the competitor mentioned

Timing & Delivery

  • detected_at is when we processed the post. Use posted_date for the original publication date.
  • One signal per company per post. A company posting multiple times in a delivery window will generate one signal per post.
  • Each delivery arrives in a timestamped folder. Treat all signals in a new folder as recent — no need to diff against prior deliveries.

Coverage

  • Refresh: Monthly
  • Coverage: 4M+ company LinkedIn pages (mid-market and enterprise accounts)
  • Best for: Aligning outreach to announced company strategy, identifying product launches and platform shifts, spotting compliance or security investments

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Updated 10 days ago