Social Intelligence

LinkedIn Company Post Signals

AI-analyzed company LinkedIn posts with initiative extraction, pain point detection, technology mentions, and engagement metrics. Know what companies publicly prioritize across 4M+ LinkedIn pages.

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4M+

Companies Tracked

Signal Subtypes

Bi-weekly

Refresh Cadence

~300 taxonomy

AI Tags per Post

Social Intelligence1 subtypes · Bi-weekly refresh

What Are LinkedIn Company Post Signals?

LinkedIn company post signals are AI-analyzed posts from official company LinkedIn pages, capturing what organizations publicly say about their priorities, challenges, and initiatives. Each post is analyzed to extract structured pain points, initiatives with urgency scoring, technologies mentioned, competitors referenced, and engagement metrics (likes, comments).

Unlike contact-level LinkedIn signals that reveal individual intent, company posts represent official messaging and strategic direction: a company posting about supply chain challenges or cybersecurity investments is signaling priorities that multiple stakeholders share. That makes these signals well suited to timing outreach around announcements. A post about a new partnership, product launch, or strategic initiative is the moment to reach out with a message that references the company's own public communications.

Example Signal Subtypes

linkedinPost

Data Schema

Company LinkedIn Post Signal Schema

Company LinkedIn signals include full post content, AI-extracted initiatives and pain points with urgency scoring, engagement metrics, and topic tags.

linkedin_company_posts.schema.json

{
  "signal_id": "7f09831f-e135-49da-8db9-c3f48fd2deff",
  "signal_type": "linkedin-post-company",
  "signal_subtype": "linkedinPost",
  "signal_name": "Company posted on LinkedIn",
  "association": "company",
  "detected_at": "2026-06-06T19: 12: 42.111Z",
  "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": 5000
  },
  "data": {
    "post_url": "https://www.linkedin.com/feed/update/urn:li:activity: 7292841003974254593/",
    "post_text": "Introducing Figma AI, now in beta. Generate UI from a text prompt, iterate with your team in real time, and ship production-ready components directly from design to code.",
    "posted_date": "2026-06-06T18: 40: 42.000Z",
    "num_likes": 4821,
    "num_comments": 312,
    "tags": ["Product Launch", "Artificial Intelligence", "User Interface"],
    "summary": "Figma launches AI beta enabling prompt-to-UI generation and design-to-code handoff.",
    "pain_points": [],
    "initiatives": [
      { "topic": "launching AI-powered design tooling", "urgency": 0.9 }
    ],
    "technologies_mentioned": [
      { "name": "Figma AI", "status": "implemented" }
    ],
    "competitors_mentioned": []
  }
}

GCS Bucket: gs://autobound-linkedin-post-company-v2/
Formats: JSONL · Parquet
Refresh: Bi-weekly

Full schema docs →Measured coverage →

Applications

What teams build with LinkedIn Company Post Signals

04 documented applications

01
Trigger-Based Outreach
When a company posts about a new initiative, product launch, or strategic direction, reach out within days with messaging that references their own announcement.
02
Initiative-Aligned Selling
AI-extracted initiatives with urgency scoring let you prioritize accounts where the company is actively promoting programs relevant to your product category.
03
Competitive Intelligence
Track when target accounts mention competitors in their LinkedIn posts. Competitor references in company posts signal active vendor evaluation or partnership activity.
04
Account Research at Scale
Instead of manually scrolling through LinkedIn feeds, get structured summaries of each company's recent posts with AI-generated topic tags and initiative extraction.

Measured, Not Estimated

What's actually inside LinkedIn Company Post Signals

Volumes, subtypes, geography, and join-key fill rates audited directly from our production database, so you can verify coverage before you buy.

Measured coverageaudited from production · minimums, not ceilings

449,749

companies with fresh data / month

basis: 3-mo avg

3,595,986

records created / month

basis: 30-day window

Top subtypes

1 total

Linkedin Post16M · 100%

Geography

all 206 countries →

🇺🇸United States149K · 16%

🇬🇧United Kingdom57K · 6.1%

🇮🇳India32K · 3.4%

🇨🇦Canada27K · 2.9%

🇫🇷France26K · 2.8%

🇩🇪Germany24K · 2.5%

🇦🇺Australia20K · 2.1%

CA 52KNY 32KTX 30KFL 24KIL 16KPA 14K

Top industries

all industries →

IT Services and IT Consulting20K · 2.1%

Financial Services19K · 2.0%

Non-Profit Organizations19K · 2.0%

Building Construction18K · 2.0%

Software Development18K · 1.9%

Advertising Services17K · 1.8%

Hospitals and Health Care16K · 1.7%

Join keys

fill rate

Domain100%

LinkedIn URL100%

Company name97%

Records measured 15,771,301+Companies reached 945,943+Full schema & examples →

See the real records for yourself.

See full coverage & segmentation across all 35 signal types →

Worked Example

One signal, traced to outcome

One LinkedIn Company Post Signals record followed from detection, through the action a rep took on it, to the measured result. Illustrative composite of observed customer workflows.

01 signal → 02 action → 03 outcome

Signal detected

HubSpot's company page posts about launching a new AI-powered content assistant for SMBs, generating 1,200 likes and 85 comments, with AI-extracted initiative: 'AI product expansion' (urgency 0.9).

Action taken

An LLM infrastructure vendor reaches out to HubSpot's VP of AI:

“Saw your announcement about the AI content assistant. Impressive engagement. We power the inference layer for similar AI features at scale. Would love to share benchmarks.”

Outcome

Technical call scheduled

Because the outreach referenced a specific, high-visibility company announcement and offered directly relevant expertise.

Run this against live data →

FAQ

Frequently Asked Questions

What are LinkedIn company post signals?

LinkedIn company post signals track what organizations are publicly saying on their LinkedIn company pages. Autobound monitors 4M+ company pages and uses AI to extract structured initiatives with urgency scores, pain points, technology mentions, competitor references, and engagement metrics from each post. This reveals organizational priorities at scale.

How does Autobound detect LinkedIn company post signals?

Autobound scans 4M+ company LinkedIn pages on a bi-weekly cadence. Each post is processed by AI models that extract topic tags from a ~300 tag taxonomy, identify mentioned initiatives with urgency scoring, detect pain points, flag competitor mentions, and capture engagement metrics. Posts are associated with the company's domain for CRM matching.

How should I use company LinkedIn post data in my outreach?

Company LinkedIn posts are ideal for trigger-based outreach. When a company announces a product launch or strategic initiative, reach out within days referencing their specific announcement. Frame your product as supporting their publicly stated priority. The key advantage over contact-level signals is that company posts represent official organizational direction, not individual opinions.

How It Works

From Raw Data to Your Stack

Autobound ingests from LinkedIn API, Glassdoor, GitHub, Reddit, G2, extracts structured signals with AI, and delivers them however your infrastructure needs.

Autobound Ingests

Raw data from LinkedIn API, Glassdoor, GitHub, Reddit, G2 is continuously collected and normalized across millions of sources.

AI Extracts & Scores

ML models extract 1 signal subtypes with relevance scoring, confidence levels, and entity resolution.

You Receive

Structured JSONL delivered via your preferred method, updated on a bi-weekly cadence.

REST API

Real-time access with subtype filtering

300 req/min

GCS Push

Automated delivery to your bucket

JSONL + Parquet

Enrich API

On-demand LLM-ranked insights

AI relevance scoring

Flat File

Bulk exports for data warehouses

CSV, JSON, Parquet

3 vendors consolidated

“By consolidating three data vendors into Autobound's Enrich API, we added 100+ new signal types and saved 4 months of engineering time.”

AiSDR Team

Engineering, AiSDR

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Custom pricing based on signal types, delivery frequency, and volume. Full schema documentation and integration guides included.

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