SAMPLE LinkedIn Data | 70M+ Company Profiles Matched with Job Postings | Enriched LinkedIn Data ...

LinkedIn is the world's largest professional network, and its company data is some of the best business intelligence available. But pulling 70M+ company profiles into a clean, analysis-ready format at scale, matched with actual hiring activity, is the hard part.

Our LinkedIn Data pipeline delivers structured company profiles from LinkedIn combined with US job posting activity, all matched at the company level. The team includes engineers from leading tech companies, with every model output validated by our internal annotation team.

What This LinkedIn Data Covers

This LinkedIn Data product combines two datasets matched at the company level.

LinkedIn Data Company Profiles:

• Company name, industry, size, and employee count
• Headquarters and branch locations
• LinkedIn company URL, specialties, and business description
• Follower count, company type, and founded date
• Geographic coordinates and location data
LinkedIn Data Job Postings (US):

• Job title (raw and normalized from 50,000+ standardized categories)
• Location (city, state, ZIP)
• Seniority, work type (remote/hybrid/onsite), employment type
• Skills: hard skills, soft skills, certifications
• Posting date, source URL, and linked company profile
Both sides of this LinkedIn Data feed are matched at the company level, so you can connect a company's firmographic profile directly to its current hiring activity in one dataset.

What You Can Do With This LinkedIn Data

CRM Data Enrichment

Sales and RevOps teams use LinkedIn Data company profiles to keep CRM records current. Employee counts change, companies move, industries shift. LinkedIn Data gives you weekly-updated firmographics you can push directly into your CRM or data warehouse. Hiring spikes surface as strong signals of active budget and buying intent.

• Append industry, size, headquarters, and employee count to CRM records using LinkedIn Data
• Flag accounts showing hiring spikes as high-intent prospects via LinkedIn Data signals
• Refresh stale company records with weekly-updated LinkedIn Data firmographics
• Segment accounts by company size, industry, and hiring velocity from LinkedIn Data
• Match LinkedIn Data company profiles to existing accounts to find coverage gaps in your pipeline
B2B Lead Generation

LinkedIn Data hiring signals tell you which companies are actively expanding, which departments are growing, and what skills they're chasing. A company posting 30 sales roles in a new geography is a better lead than one that hasn't posted in six months. LinkedIn Data gives you that signal at the posting level.

• Build prospect lists of companies expanding specific departments using LinkedIn Data
• Prioritize outreach by identifying high-growth companies from LinkedIn Data hiring patterns
• Filter companies by size, industry, and location through LinkedIn Data firmographics
• Identify new market opportunities by analyzing growth signals in LinkedIn Data
• Time outreach to companies at the exact moment LinkedIn Data signals active expansion or new department investment
Talent Acquisition and HR Intelligence

HR teams use LinkedIn Data to track which companies are hiring for specific roles, benchmark compensation, and identify talent hotspots. Combined with LinkedIn Data company profiles, every hiring signal comes with full firmographic context, including company size, industry, and follower count.

• Identify companies actively hiring for specific roles using LinkedIn Data job postings
• Analyze competitor hiring patterns across functions and geographies with LinkedIn Data
• Benchmark hiring velocity against industry peers using LinkedIn Data signals
• Map talent hotspots by tracking LinkedIn Data posting concentrations by location
• Track in-demand skills by role and region using LinkedIn Data job postings to guide sourcing strategy
Company Analysis and Due Diligence

Investors and analysts use LinkedIn Data hiring trends as a leading indicator of company health. A company tripling headcount in engineering is sending a signal. LinkedIn Data gives you that signal at the posting level, not an aggregated summary from a quarterly report.

• Track hiring velocity of competitors and portfolio companies using LinkedIn Data
• Conduct due diligence on private companies through LinkedIn Data hiring history
• Benchmark a company's LinkedIn Data activity against its industry peers
• Build quantitative models correlating LinkedIn Data hiring trends with performance
• Size addressable markets by counting companies in LinkedIn Data hiring for specific roles or skills
How We Build This LinkedIn Data

Our deduplication model identifies when the same job appears on LinkedIn and elsewhere using semantic matching on title, company, location, and description. It goes beyond exact matching to catch near-duplicates with slightly different wording. Roughly 60% of raw records collapse into unique entries, so LinkedIn Data job postings reflect true hiring intent instead of inflated counts.

The title taxonomy model normalizes raw LinkedIn Data job titles by stripping location noise, qualifiers, and formatting variations, then maps them into a hierarchical taxonomy of 50,000+ standardized categories from 20M+ raw titles. This makes LinkedIn Data usable for cross-company and cross-region analysis without manual cleanup.

Job category models classify LinkedIn Data postings by seniority level (Entry, Mid, Senior, Lead, Executive) and work modality (Remote, Hybrid, Onsite) using LLM-based analysis of the full job description, not just title keywords.

Company profiles in our LinkedIn Data are normalized for consistent industry classification, location matching, and employee count standardization across 70M+ global records.

Our annotation team validates every LinkedIn Data model output before delivery.

What Makes This LinkedIn Data Different

• Company-to-job match: every LinkedIn Data job posting connects to a verified company profile with firmographics and location data
• 70M+ global company profiles in one LinkedIn Data feed, matched with US job posting activity
• Weekly updates: LinkedIn Data company profiles and job postings refresh every week
• Deduplication: roughly 60% of raw LinkedIn Data job postings collapse into unique records showing true hiring intent
• Hiring signals: LinkedIn Data shows velocity, department growth, and skill demand at the company level
• Follower count and company type in LinkedIn Data profiles add context beyond basic firmographics for segmentation and targeting
Who Uses This LinkedIn Data

• CRM and RevOps Teams use LinkedIn Data to keep account records current and flag high-intent prospects by hiring activity
• Business Development and Sales Teams use LinkedIn Data hiring signals to prioritize outreach and build targeted prospect lists
• HR and Talent Acquisition Teams use LinkedIn Data to track competitor hiring and identify talent market trends by region and role
• Investors, PE Firms, and VC Funds use LinkedIn Data hiring velocity as alternative data for due diligence and portfolio monitoring
• Site Selection Consultants and EDOs use LinkedIn Data to assess company growth signals and regional hiring concentration
• Market Research and BI Teams use LinkedIn Data to analyze corporate expansion patterns and industry hiring trends
• Staffing and Recruiting Agencies use LinkedIn Data to identify market expansion opportunities and build data-driven client advisory reports
• HR Tech Companies and B2B Platforms use LinkedIn Data to power firmographic enrichment, lead scoring, and talent intelligence tools
Delivery and Format

LinkedIn Data is delivered in CSV, JSON, or Parquet via AWS S3 or Google Cloud Storage. Custom filters by geography, industry, company size, date range, skill, and seniority. Compatible with Snowflake, Databricks, Power BI, Tableau, Salesforce, and most BI platforms.

搜集汇总

背景与挑战

背景概述

该数据集整合了LinkedIn的7000万+公司档案与美国职位发布信息，在公司层面进行匹配，提供每周更新的公司详情和招聘活动数据。它支持CRM丰富、B2B潜在客户开发、人才招聘分析等多种商业应用，并经过去重和标准化处理，确保数据质量。