> ## Documentation Index
> Fetch the complete documentation index at: https://www.datalegion.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Person Data Overview

> Overview of Data Legion's person data: up to 100+ data points per profile covering contact info, employment history, education, skills, certifications, and social profiles.

Data Legion's person data product provides professional profiles with up to 100+ data points per person, available through APIs and monthly bulk data feeds.

## What's Included

Each person profile contains information across multiple categories:

### Core Identity

* Stable contact identifier (`legion_id`)
* Full name components (first, middle, last, suffix, prefix)
* Sex classification

### Birth & Age

* Birth date with precision preserved (year, month, day)
* Derived age calculation

### Current Employment

* Current job title, company name, and domain
* Seniority level and job function classifications
* P\&L expense category
* Decision maker flag
* Years of experience and average tenure
* Company data: Industry, company size, LinkedIn URL

### Contact Information

* Work email (validated, with quality scores)
* Mobile phone (with quality scores)
* All phone numbers (mobile, landline) with type, current status, and quality scores
* All email addresses (professional, personal) with type, validation status, current status, and quality scores

### Location

* Current city, state, state code, country, country code
* All locations (current and historical) with:
  * Street address, city, state, postal code
  * ISO 3166 codes (state and country)
  * Continent information
  * Quality scores

### LinkedIn Profile

* Primary LinkedIn profile URL (with current status)

### Skills & Languages

* Skills array (with cleaned normalized text and raw source snippets)
* Languages array (with proficiency levels, cleaned and raw variants)

### Professional Summary

* Headline (with cleaned normalized text and raw source snippets)
* Summary/about section (with cleaned and raw variants)

### Work Experience

* **Rich job history**: Career progression, not just current role
* Employment history with:
  * Job titles (cleaned and raw variants)
  * Company information (name, website, LinkedIn URL, industry, size)
  * Start and end dates
  * Current status flag
  * Tenure tracking (job tenure in months)
  * Seniority level, job function, expense category classifications
  * Decision maker flag
  * Job descriptions (cleaned and raw variants)
* Job transitions and career progression context

### Education

* Highest degree level classification
* Educational history with:
  * School/organization information (name, website, LinkedIn URL)
  * Degree information (cleaned and raw variants)
  * Degree level classification
  * Field of study (cleaned and raw variants)
  * Start and end dates
  * Current enrollment status

### Certifications

* Professional certifications, licenses, and credentials with:
  * Certification name (cleaned and raw variants)
  * Issuing institution (cleaned and raw variants)
  * Credential ID
  * Issue and expiration dates

### Social & Web Presence

* Social profiles (LinkedIn, GitHub, X, Facebook) with:
  * Network type
  * Social URL and username
  * Current status
  * Quality scores

### Metadata

* Schema version identifier

## Coverage Statistics

* **70% LinkedIn coverage** - Strong social profile coverage
* **76% location coverage** - Geographic data across profiles
* **28% work email coverage** - Professional contact data
* **24% mobile phone coverage** - Direct dial coverage

Strong LinkedIn coverage (70%) helps sales teams reach prospects, marketers personalize campaigns, recruiters find candidates, and data scientists build reliable models.

## Use Cases

### Sales & Marketing

* Sales prospecting and lead generation with reliable contact data
* Account-based marketing (ABM) with strong LinkedIn coverage (70%)
* CRM data enrichment with career history
* Territory planning and market segmentation
* Personalize campaigns with rich job history and company context

### HR Tech & Recruiting

* Candidate sourcing with career progression
* Talent pipeline building with full profiles
* Skills-based recruiting with detailed data
* Passive candidate identification
* Applicant data enrichment

### Investment & Research

* Conduct due diligence with executive data
* Map executive teams for M\&A transactions
* Analyze workforce composition for portfolio companies

## Access Methods

### APIs

* **[Enrichment API](/docs/api-reference/person-enrichment)**: Match and enrich your records
* **[Search API](/docs/api-reference/person-search)**: Query our database with flexible filters
* **[Discovery API](/docs/api-reference/person-discovery)**: Find people using natural language queries

### Bulk Data Feeds

* **Delivery Method**: Monthly via secure transfer (cloud storage, SFTP)
* **File Formats**: CSV, JSON, Parquet, Delta
* **Update Frequency**: Monthly full-file refreshes

## Next Steps

* **[View Schema Example](/docs/person-data/schema)** - See a complete example record
* **[Field Reference](/docs/person-data/fields)** - Detailed field descriptions
* **[Data Tiers](/docs/person-data/tiers)** - Base vs premium field availability
* **[Dataset Statistics](/docs/person-data/stats)** - Coverage statistics and field fill rates
* **[Enum Values](/docs/enums)** - All possible enum values
* **[Data Quality](/docs/data-quality/overview)** - Understanding quality scores and verification
* **[Field Formats](/docs/data-standardization/field-formats)** - Format specifications for all field types
* **[Array Ordering](/docs/data-standardization/array-ordering)** - How arrays are sorted
* **[Get Sample Data](https://www.datalegion.ai/get-started)** - Get a free sample dataset