Data Quality Overview

Data Legion ensures accuracy through confidence levels, validation processes, and rigorous data standards across both person and company datasets.

​

Key Quality Features

​

Full Coverage

Person profiles span career history, contact information, and social profiles across 100+ data points. Company profiles span firmographics, office locations, workforce analytics, and growth signals across 75+ data points. See Person Dataset Statistics and Company Dataset Statistics for field-level coverage.

​

Confidence Levels

Data points receive confidence levels (high, moderate, or low) that help you filter and prioritize data. See Confidence Levels for details.

​

Data Freshness Tracking

Records include freshness indicators such as last_seen dates and current flags on person contact data, helping you prioritize the most up-to-date information.

​

Email Validation

We’re working on validating deliverability for current professional (work) emails. emails[].validated indicates whether validation was performed, and emails[].validation_status (nullable) may be valid, invalid, risky, or catch_all.

​

Production-Ready Quality

Higher confidence in data accuracy means fewer wasted outreach attempts, better match rates, and reliable data for mission-critical operations across sales, marketing, recruiting, investment research, and data science use cases.

​

Learn More

For detailed information on each quality feature:

• Data Verification - How we verify data quality
• Confidence Levels - Understanding confidence levels and how to use them
• Data Freshness - How freshness tracking works and how to use current flags
• Data Standardization - How data is normalized and standardized