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Social Intelligence

LinkedIn Post Signals

Published Updated

See what your buyers post on LinkedIn.

Every LinkedIn post from 4M+ monitored contacts, analyzed into pain points with intensity scores, initiatives with urgency scores, technology mentions with adoption status, and topic tags from a 300+ value taxonomy. Resolved to work emails and refreshed every 2 weeks.

Read the API docs
Contacts Monitored
4M+
Tag Types
300+
Refresh Cadence
Bi-weekly
Avg Tags per Post
5-12
Delivery
REST API, GCS Push, Generate Insights API, Flat File
Format
JSONL or Parquet
Bucket
gs://autobound-linkedin-post-contact-v3/

What Are LinkedIn Contact Signals?

300+ tags

LinkedIn contact signals capture what individual prospects publicly post on LinkedIn, delivered as structured data. Autobound monitors 4M+ contacts and analyzes every post with AI to extract pain points scored 0-1 for intensity, initiatives scored for urgency, technologies mentioned with one of 10 adoption statuses (evaluating, using, migrating_from, and more), competitors referenced, topic tags from a 300+ value taxonomy, and a 10-15 word factual summary.

Every signal arrives resolved to a business contact: LinkedIn URL on 90-98% of records, work email on 85-95%, matched at 99.8% accuracy against a 270M+ contact database. Posts refresh every 2 weeks, so you can reference a prospect's own words in outreach while the post is still earning engagement.

Example record

LinkedIn postlinkedinPost

Illustrative example

Datadogdatadoghq.com

VP of Engineering plans data tooling consolidation to reduce on-call overhead.

Source: datadoghq.com

From a LinkedIn post to your next move

What we detect, what you get, and what you do with it. Pick the path that fits your team.

Sales, marketing and RevOps: Slack, CRM fields and plays.

  1. 0103

    Prospects post their priorities

    When a monitored contact posts on LinkedIn, we read the post for pain points, initiatives and the tools they name.

    1. LinkedIn
    LinkedInJun 18, 2026

    We've been running five different data pipeline tools for three years. The cognitive overhead is crushing our on-call team, so this quarter we're consolidating onto a single platform...

    Extracted
    Datadogdatadoghq.comcompanySarah ChencontactLinkedIn postsignal_subtype

  2. 0203

    You get one clean record

    Each record names the person, their title and company, labels the event, and links back to the source.

    2. Signal record

    Datadog

    datadoghq.comSoftware Development

    Sarah ChenVP of Engineering

    LinkedIn postlinkedinPost

    VP of Engineering plans data tooling consolidation to reduce on-call overhead.

    “We've been running five different data pipeline tools for three years. The cognitive overhead is crushing our on-call team, so this quarter we're consolidating onto a single platform...”
    Likes
    234
    Comments
    47
    Detected
    Jun 18, 2026

    signal_id 5349e887…

  3. 0303

    Act on it where you work

    Send it to Slack, write it to your CRM, or give it to an AI agent.

    When
    pain_points names a problem you solve
    Do
    Social touch, then an email that quotes the post
    3. Your team acts
    or your own code
    #account-signals

    Signal alert from your workflow

    Sarah Chen, Datadog· LinkedIn post

    VP of Engineering plans data tooling consolidation to reduce on-call overhead.

    Play: Social touch, then an email that quotes the post

    Start the playOpen the source

    Illustration. The record fields are real.

Try it on your own accounts

1,000 free credits. Query linkedin-post-contact in the Signal API or from Claude.

Get a free API keyUse it in Claude via MCP

How we build this signal

How we build each LinkedIn post signal

Each run reads the newest posts from every monitored person and turns each one into a structured signal.

Max posts per person per run
20
  1. 01

    Collection

    For each monitored person, plus people customers ask us to monitor, we read their newest posts inside the run window, up to 20 per person.

  2. 02

    Context first

    Before any model reads a post, the author is matched to our contact records and their company to our company records, so the model knows who is speaking and where they work.

  3. 03

    Extraction

    A model summarizes each post and lists the pain points, initiatives, technologies and competitors it states. A request for tool recommendations or a new-role announcement counts as a signal. Without clear evidence, it returns empty lists.

  4. 04

    Tags and delivery

    Topic tags must come from our approved taxonomy, and code removes any other tag. Each record carries the post URL, text, engagement counts, contact and company.

LinkedIn Post Signal Schema

LinkedIn contact signals include the full post content, 300+ AI-generated tags with intensity scoring, engagement metrics, and contact resolution data.

Full schema docs →
{
  "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": "2026-06-18T15:36:11.235Z",
  "contact": {
    "email": "s***@datadoghq.com",  // match on email
    "name": "Sarah Chen",
    "first_name": "Sarah",
    "last_name": "Chen",
    "job_title": "VP of Engineering",
    "linkedin_url": "linkedin.com/in/sarahchen-eng"  // or match on LinkedIn URL
  },
  "company": {
    "name": "Datadog",
    "domain": "datadoghq.com",  // match on domain
    "linkedin_url": "linkedin.com/company/datadog",
    "description": "Cloud monitoring and observability platform",
    "industries": ["Software Development"],
    "employee_count_low": 5001,
    "employee_count_high": 10000
  },
  "data": {
    "post_url": "https://www.linkedin.com/feed/update/urn:li:activity:7416003205425303552/",
    "post_text": "We've been running five different data pipeline tools for three years. The cognitive overhead is crushing our on-call team, so this quarter we're consolidating onto a single platform...",
    "posted_date": "2026-06-11T06:29:06.850Z",
    "num_likes": 234,
    "num_comments": 47,
    "tags": ["Infrastructure", "Consolidation", "DevOps"],
    "summary": "VP of Engineering plans data tooling consolidation to reduce on-call overhead.",
    "pain_points": [
      { "topic": "tool sprawl overwhelming on-call team", "intensity": 0.8 }
    ],
    "initiatives": [
      { "topic": "consolidating pipeline tooling this quarter", "urgency": 0.9 }
    ],
    "technologies_mentioned": [
      { "name": "Airflow", "status": "migrating_from" }
    ],
    "competitors_mentioned": []
  }
}

Bulk data

Need this signal for 10,000+ companies?

Get a free sample file or a bulk feed (API, GCS push, flat file). The sample is real LinkedIn Contact Posts records, as a CSV.

Talk to sales

Measured coverage

What's inside LinkedIn Post Signals (Contact-Level)

A dated snapshot counted in our production database, not a live count. Minimums, not ceilings.

Coverage for all 35 signal types →
269,241
Contacts with fresh data per month
6-month average, records through Jul 16, 2026
772,916
Records created per month
Published baseline, records through Jul 16, 2026

Top subtypes

1 total
Linkedin Post5.4M · 100%

Seniority

full breakdown →
C-Suite154K · 15%
Director140K · 14%
VP140K · 14%
Staff75K · 7.5%
Manager43K · 4.4%
Consultant2.3K · 0.2%

Departments

full breakdown →
Business Management232K · 23%
Sales39K · 3.9%
Marketing33K · 3.3%
Human Resources26K · 2.6%
Technology, Software, Information Technology24K · 2.4%
Executive23K · 2.3%
Operations21K · 2.1%

Join keys

fill rate
Contact LinkedIn100%
Contact name100%
Email76%
Records measured 5,410,415+Contacts reached 995,315+

See for yourself

Check out sample data: real LinkedIn Post records with the same fields the API returns.

Read the API docs
“Autobound's API streamlined our data management, accelerated product development, and improved outreach quality.”
AiSDR Team, Engineering Team, AiSDR

Frequently asked questions

How are LinkedIn contact signals different from company-level LinkedIn signals?
Contact-level signals track individual posts from decision-makers, including their pain points, technology evaluations, and career moves. Company-level signals track the company page's announcements and social presence. Contact signals are more actionable for personalized outreach.
How many contacts are covered by LinkedIn post signals?
Our LinkedIn contact signal database covers 4M+ monitored contacts, with bi-weekly refresh cycles. Coverage is concentrated on B2B decision-makers including VPs, directors, C-suite executives, and technical leads.
What does the 300+ tags classification include?
Our AI models classify LinkedIn posts into 300+ semantic tags covering pain points (with intensity scoring), technology evaluations, initiatives (with urgency levels), hiring announcements, thought leadership, vendor comparisons, and more. Each tag includes a confidence score.
Can I use LinkedIn signals for ABM campaigns?
Yes. LinkedIn contact signals are ideal for account-based marketing. You can target specific accounts and monitor when decision-makers post about relevant pain points, technology evaluations, or initiatives that align with your solution.