Product Introduction
The Crustdata People Dataset is a comprehensive collection of structured data containing billions of datapoints on hundreds of millions of individuals globally, designed to power AI-driven products and business intelligence tools. It provides detailed profiles with attributes such as employment history, career movements, social media activity, and professional certifications, delivered in Parquet file format for seamless integration into data pipelines. The dataset is refreshed monthly to ensure up-to-date information for applications requiring real-time or near-real-time insights.
The core value of the People Dataset lies in its ability to serve as a foundational layer for AI agents, sales automation tools, recruiting platforms, and investment analysis systems by providing actionable, high-quality data at scale. It eliminates reliance on fragmented or outdated sources by aggregating and standardizing data from multiple public and proprietary channels, enabling users to build dynamic workflows, enrich internal databases, or train machine learning models with minimal preprocessing.
Main Features
The dataset includes over 200 million individual profiles enriched with real-time signals such as job changes, promotions, certifications, and social media posts, sourced from eight distinct channels including LinkedIn, company filings, and news alerts. Each profile is linked to metadata like company affiliations, funding rounds, and web traffic trends, enabling cross-referencing with organizational data for holistic analysis.
Data is delivered in Parquet files optimized for bulk processing, supporting efficient storage, querying, and integration with modern data stacks like Apache Spark, Snowflake, or AWS Athena. The schema includes nested fields for career timelines, investment histories, and social media activity, allowing granular filtering and aggregation without requiring external joins.
Users can combine the static dataset with Crustdata’s live APIs to maintain freshness for specific records, reducing costs associated with full real-time API calls while ensuring critical profiles (e.g., high-priority sales targets or investment prospects) remain updated. This hybrid approach supports use cases requiring both historical analysis and immediate alerts on key events.
Problems Solved
The dataset addresses the challenge of relying on stale or incomplete public data for decision-making, which often leads to missed opportunities in sales, recruiting, or investment scenarios. By providing monthly-refreshed, standardized profiles, it eliminates manual data scraping and reconciliation efforts that consume engineering resources.
It targets AI developers building sales automation tools (e.g., AI SDRs), recruiting platforms sourcing passive candidates, and investment firms tracking founder movements. Enterprises managing large-scale CRMs or ATS systems also benefit from automated enrichment of internal records with external signals.
Typical use cases include generating targeted prospect lists for outbound sales campaigns, monitoring competitor talent movements, identifying founders open to funding, and triggering alerts when key individuals change roles or share relevant social media content. For example, a recruiting platform could use the data to identify engineers who recently earned certifications or left high-growth startups.
Unique Advantages
Unlike static B2B contact databases, Crustdata’s dataset integrates real-time signals (e.g., job changes updated within hours) with historical context, enabling predictive analytics and trend analysis. Competitors often lack this hybrid model, forcing users to choose between bulk datasets without freshness guarantees or expensive API-only solutions.
The inclusion of non-traditional data points—such as employee reviews, Form D filings, and social media sentiment—provides multidimensional insights unavailable in standard people databases. For instance, investment teams can correlate executive promotions with recent funding rounds or SEC filings to assess company health.
Competitive differentiation stems from Crustdata’s proprietary data fusion engine, which cross-references 60 million company profiles with individual records to validate employment histories and detect undisclosed career transitions. This reduces false positives in lead generation and ensures compliance with data accuracy standards required for GDPR and CCPA.
Frequently Asked Questions (FAQ)
How frequently is the People Dataset updated? The dataset is refreshed monthly with new profiles and revised attributes, while real-time APIs provide sub-hourly updates for specific high-priority records identified by users. Historical versions are archived for reproducibility in training AI models.
What data sources are used to build the profiles? Data is aggregated from eight verified sources, including LinkedIn profiles, corporate websites, SEC filings, news publications, social media platforms, patent databases, conference attendee lists, and government registries. Machine learning models deduplicate and reconcile conflicting information.
Can the dataset be integrated with existing CRM or ATS systems? Yes, the Parquet format is compatible with all major cloud data warehouses and ETL tools, and prebuilt connectors are available for Salesforce, HubSpot, Greenhouse, and LinkedIn Sales Navigator. Custom JSON/CSV exports are supported for on-premises systems.
What compliance measures are in place for GDPR and CCPA? All data is sourced from publicly available or licensed sources, with opt-out mechanisms and automated suppression of profiles requesting removal. Crustdata provides audit logs and data lineage reports to demonstrate compliance during regulatory reviews.
How does the dataset handle data gaps or inaccuracies? A multi-layered validation system flags inconsistencies (e.g., mismatched job titles and company sizes) for human review, achieving a 98.6% accuracy rate in employment history fields. Users can submit correction requests via API or dashboard, with updates reflected in the next monthly refresh.