Bulk Data Dictionary

An intuitive, high-performance data dictionary viewer designed to organize, search, and manage complex schema documentation with ease.

Bulk Delivery Data Dictionary

Complete reference for every field included in LeadGenius bulk data deliveries — across business entity records and consumer-level data.

3 Product Datasets
10 Files
404+ Unique Fields
640M+ B2B Contacts
500M+ Consumer Records

B2B Dataset (Global)

B2B Attributes

All available B2B attributes across 11 categories — Standard Account Info, Standard Contact Info, Advertising Spend, Ecommerce, Firmographic, Funding, Growth, Hiring, Social, Technographic, Champion Monitoring, and Contact Insights. 640M+ contacts, 310M+ accounts.

Field	Type	Description	Example
Advertising Spend
	Boolean	Does the company have active ads on Facebook and Instagram? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	Boolean	Does the company actively advertise on LinkedIn? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	Boolean	Does the company have active ads on TikTok? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	String (range)	Estimated monthly spend on advertising within range B2B Attributes	`$10 - $1,000, $1,000 - $5,000, $5,000 - $10,000...`
Full Format String (range) Example `$10 - $1,000, $1,000 - $5,000, $5,000 - $10,000...`
	Float	Estimated monthly ad spend on Facebook and Instagram B2B Attributes	`10000.00`
Full Format Float Example `10000.00`
	Float	Monthly budget allocated for Google AdWords B2B Attributes	`10000.00`
Full Format Float Example `10000.00`
	Boolean	Does the company have active video ads on Google and YouTube? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	Integer	Total number of LinkedIn Ads B2B Attributes	`25`
Full Format Integer Example `25`
	Integer	Number of active ads on Facebook and Instagram B2B Attributes	`1000`
Full Format Integer Example `1000`
Champion Monitoring
	String	New Hire, New Role, Tenured, Influencer B2B Attributes	`Tenured`
Full Format String Example `Tenured`
	Date	Date of Hire (month/year) B2B Attributes	`2023-05`
Full Format Date Example `2023-05`
	Date	Date of Leaving (month/year) B2B Attributes	`2022-11`
Full Format Date Example `2022-11`
	Date	Date when contact received new title (month/year) B2B Attributes	`2023-05`
Full Format Date Example `2023-05`
	String	Name of the previous company the contact worked at B2B Attributes	`Vervoe`
Full Format String Example `Vervoe`
	Integer (months)	Duration at previous company in months B2B Attributes	`69`
Full Format Integer (months) Example `69`
	String	Job title held at the previous company B2B Attributes	`Advisor`
Full Format String Example `Advisor`
Contact Insights
	String	Company city of the contact's location B2B Attributes	`Berkeley`
Full Format String Example `Berkeley`
	String	Company country of the contact's location B2B Attributes	`United States`
Full Format String Example `United States`
	String	Contact and personal information from LinkedIn profile B2B Attributes	`C-Suite Start-Up Junkie...`
Full Format String – text Example `C-Suite Start-Up Junkie...`
	Date	Month and year when the contact started at the company B2B Attributes	`2019-03`
Full Format Date Example `2019-03`
	Date	Month and year when contact started in the current role B2B Attributes	`2019-03`
Full Format Date Example `2019-03`
	String	Company state of the contact's location B2B Attributes	`California`
Full Format String Example `California`
	String	Present or Left the Company B2B Attributes	`Present`
Full Format String Example `Present`
	String	Languages spoken on contact's social profiles B2B Attributes	`English, Spanish`
Full Format String Example `English, Spanish`
	String	Personal skills from contact's LinkedIn profile B2B Attributes	`Start-ups, Cloud Computing, Virtualization...`
Full Format String Example `Start-ups, Cloud Computing, Virtualization...`
	String	Tech or Knowledge Certifications on contact's social profiles B2B Attributes	`Series 65, Microsoft Azure, Microsoft 365`
Full Format String Example `Series 65, Microsoft Azure, Microsoft 365`
	Integer (months)	Tenure in months at the current company B2B Attributes	`79`
Full Format Integer (months) Example `79`
	Integer (months)	Tenure in months at the current position B2B Attributes	`79`
Full Format Integer (months) Example `79`
Ecommerce Insights
	String	Amazon seller name representing a specific brand on the marketplace B2B Attributes	`Utopia Deals`
Full Format String Example `Utopia Deals`
	Float	Measurement of seller quality on Amazon B2B Attributes	`4.9`
Full Format Float Example `4.9`
	String	Link to the Amazon seller storefront B2B Attributes	`https://www.amazon.com/sp?seller=A3AQP8TDYVYCGL`
Full Format String – URL Example `https://www.amazon.com/sp?seller=A3AQP8TDYVYCGL`
	Integer	Amazon Top Seller Rank Number B2B Attributes	`1`
Full Format Integer Example `1`
	String	Currencies accepted on a store page B2B Attributes	`US Dollar, Euro...`
Full Format String Example `US Dollar, Euro...`
	String	E-commerce platform currently used by a company B2B Attributes	`Shopify, Magento, Wix, WooCommerce...`
Full Format String Example `Shopify, Magento, Wix, WooCommerce...`
	String	Shipping options available B2B Attributes	`Local Pickup`
Full Format String Example `Local Pickup`
	Integer	Traffic rank of site compared to all other sites globally B2B Attributes	`1250500`
Full Format Integer Example `1250500`
	Integer	Number of unique individuals who visited a website in one month B2B Attributes	`15000`
Full Format Integer Example `15000`
	Float	Revenue generated online by a store B2B Attributes	`100000`
Full Format Float Example `100000`
	Float	Month-over-month growth of unique website visitors B2B Attributes	`0.25`
Full Format Float Example `0.25`
Firmographic Insights
	String	Type of business such as Sole proprietorship, Private, Public, Partnership, Non-Profit, etc. B2B Attributes	`Private`
Full Format String Example `Private`
	Float	Approval rating of the company CEO collected from Glassdoor B2B Attributes	`4.2`
Full Format Float Example `4.2`
	String	General overview of the company B2B Attributes	`Over 80% of B2B data remains undiscovered...`
Full Format String – text Example `Over 80% of B2B data remains undiscovered...`
	Integer (year)	Year when the company was founded B2B Attributes	`2011`
Full Format Integer (year) Example `2011`
	String	Name of top group of investors with investments in this company B2B Attributes	`Sierra Ventures, SJF Ventures, Initialized Capital`
Full Format String Example `Sierra Ventures, SJF Ventures, Initialized Capital`
	String	Specific business-related specialties from company LinkedIn page B2B Attributes	`Sales, Data Enrichment, Lead Generation, B2B`
Full Format String Example `Sales, Data Enrichment, Lead Generation, B2B`
	String	Main competitor companies B2B Attributes	`eBay, Walmart, BestBuy`
Full Format String Example `eBay, Walmart, BestBuy`
	Integer	Number of years company has been operating as active B2B Attributes	`13`
Full Format Integer Example `13`
Funding Insights
	Float	Amount of money raised in the last funding round B2B Attributes	`100000`
Full Format Float Example `100000`
	String	Type of last funding round (e.g. Pre-Seed, Seed, Series A, B, C, Private Equity) B2B Attributes	`Series A`
Full Format String Example `Series A`
	Date	Date when the company raised its last round of funding B2B Attributes	`2023`
Full Format Date Example `2023`
	Float	Total amount of money raised across all funding rounds B2B Attributes	`1000000`
Full Format Float Example `1000000`
Growth Insights
	String	Name of the company which acquired this company B2B Attributes	`LeadGenius`
Full Format String Example `LeadGenius`
	Float	Percentage of department employee headcount change in the last year B2B Attributes	`0.2`
Full Format Float Example `0.2`
	Float	Percentage of department employee headcount change in the last 6 months B2B Attributes	`0.1`
Full Format Float Example `0.1`
	Integer	Number of employees in the specific department B2B Attributes	`100`
Full Format Integer Example `100`
	Float	Percentage of employee headcount change in the last year B2B Attributes	`0.2`
Full Format Float Example `0.2`
	Float	Percentage of employee headcount change in the last 2 years B2B Attributes	`0.3`
Full Format Float Example `0.3`
	Float	Percentage of employee headcount change in the last 6 months B2B Attributes	`0.1`
Full Format Float Example `0.1`
	Boolean	Merger or Acquisition Announced in Last 12 Months B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	String	URL with evidence of merger or acquisition announcement B2B Attributes	`Evidence URL`
Full Format String – URL Example `Evidence URL`
	String	Indicates a new location opening event B2B Attributes	`Evidence URL`
Full Format String Example `Evidence URL`
	Boolean	New Product or Offering Announced in the last 12 months B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	String	URL to new product or offering announcement B2B Attributes	`Evidence URL`
Full Format String – URL Example `Evidence URL`
	String	Link to most recent article mentioning company news B2B Attributes	`Evidence URL`
Full Format String – URL Example `Evidence URL`
Hiring Insights
	Integer	Specific active job postings (Sales, Digital Marketing, Engineering, etc.) B2B Attributes	`50`
Full Format Integer Example `50`
	Boolean	Did the company have executive role changes in the last 6 months? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	Boolean	Did the company have executive role changes in the last 12 months? B2B Attributes	`Yes/No`
Full Format Boolean Example `Yes/No`
	Integer	Sum of all open job positions the company is offering B2B Attributes	`150`
Full Format Integer Example `150`
Social Insights
	String	Link to the company Crunchbase page B2B Attributes	`https://www.crunchbase.com/organization/mobileworks`
Full Format String – URL Example `https://www.crunchbase.com/organization/mobileworks`
	String	Link to the company Facebook page B2B Attributes	`https://www.facebook.com/Amazon/`
Full Format String – URL Example `https://www.facebook.com/Amazon/`
	String	Instagram handle of the company B2B Attributes	`@amazon`
Full Format String Example `@amazon`
	String	Twitter handle of the company B2B Attributes	`@amazon`
Full Format String Example `@amazon`
	String	Link to the company YouTube channel B2B Attributes	`https://www.youtube.com/user/amazon`
Full Format String – URL Example `https://www.youtube.com/user/amazon`
	Float	Company ratings on Glassdoor determined by recent employee feedback B2B Attributes	`4.2`
Full Format Float Example `4.2`
	Float	Rating based on Google Maps reviews B2B Attributes	`4.5`
Full Format Float Example `4.5`
	String	Google Maps URL for the company location B2B Attributes	`https://www.google.com/maps/place/LeadGenius`
Full Format String – URL Example `https://www.google.com/maps/place/LeadGenius`
	Integer	Total number of followers on company Instagram page B2B Attributes	`5000000`
Full Format Integer Example `5000000`
	Integer	Total number of likes on company Facebook page B2B Attributes	`30000000`
Full Format Integer Example `30000000`
	Integer	Total number of followers on company LinkedIn page B2B Attributes	`15000`
Full Format Integer Example `15000`
	Integer	Number of Twitter followers on the company Twitter page B2B Attributes	`6000000`
Full Format Integer Example `6000000`
Standard Account Information
	String	HQ City B2B Attributes	`Berkeley`
Full Format String Example `Berkeley`
	String	Company Name B2B Attributes	`LeadGenius`
Full Format String Example `LeadGenius`
	String	Company Phone Number B2B Attributes	`(888) 866-3775`
Full Format String Example `(888) 866-3775`
	String	HQ Country B2B Attributes	`United States`
Full Format String Example `United States`
	String (range)	LinkedIn Employee Range B2B Attributes	`1-10, 11-50, 51-200, 201-500 ...`
Full Format String (range) Example `1-10, 11-50, 51-200, 201-500 ...`
	String	Industry B2B Attributes	`Software Development`
Full Format String Example `Software Development`
	String	Company LinkedIn URL B2B Attributes	`https://www.linkedin.com/company/leadgenius`
Full Format String – URL Example `https://www.linkedin.com/company/leadgenius`
	Integer	LinkedIn Number of Employees B2B Attributes	`489`
Full Format Integer Example `489`
	String (range)	Revenue Range B2B Attributes	`$1M - $10M, $10M - $50M, $50M - $100M...`
Full Format String (range) Example `$1M - $10M, $10M - $50M, $50M - $100M...`
	String	HQ State B2B Attributes	`California`
Full Format String Example `California`
	String	HQ Street B2B Attributes	`2054 University Ave. Suite 200`
Full Format String Example `2054 University Ave. Suite 200`
	String	Company Domain B2B Attributes	`leadgenius.com`
Full Format String Example `leadgenius.com`
	String	HQ Zip B2B Attributes	`94704`
Full Format String Example `94704`
Standard Contact Information
	String	Present or Left the Company B2B Attributes	`Present`
Full Format String Example `Present`
	String	Department B2B Attributes	`Leadership`
Full Format String Example `Leadership`
	String	Contact Direct Dials (up to 3 numbers) B2B Attributes	`(123) 456-7890`
Full Format String Example `(123) 456-7890`
	String	Email B2B Attributes	`mark@leadgenius.com`
Full Format String Example `mark@leadgenius.com`
	String	First Name B2B Attributes	`Mark`
Full Format String Example `Mark`
	String	Last Name B2B Attributes	`Godley`
Full Format String Example `Godley`
	String	LinkedIn Profile URL B2B Attributes	`https://www.linkedin.com/in/markgodley/`
Full Format String – URL Example `https://www.linkedin.com/in/markgodley/`
	String	Seniority B2B Attributes	`C-level`
Full Format String Example `C-level`
	String	Title from LinkedIn B2B Attributes	`CEO`
Full Format String Example `CEO`
Technographic Insights
	Float	Estimated Technology Spend Range over a year period B2B Attributes	`10000`
Full Format Float Example `10000`
	Date	Date when technology was first verified B2B Attributes	`2024-01-15`
Full Format Date Example `2024-01-15`
	Date	Date when technology was last verified B2B Attributes	`2024-11-01`
Full Format Date Example `2024-11-01`
	String	Full stack of technologies the company is using B2B Attributes	`Hubspot, Pardot, Google Optimize 360, Slack...`
Full Format String Example `Hubspot, Pardot, Google Optimize 360, Slack...`
	String	Technology Category B2B Attributes	`Enterprise Resource Planning (ERP)`
Full Format String Example `Enterprise Resource Planning (ERP)`

Secretary of State (SoS) & Contact Dataset (US)

Corporate Registry & Contact

Corporate registry data sourced from official government registers — companies, officers, addresses, filings, and corporate relationships. 110M+ companies, 244M+ officers. Delivered as 7 separate files.

Field	Type	Description	Example
Address
	String	Country portion of contact address Officers	`"United Kingdom"`
Full Format String Example `"United Kingdom"`
	String	Contact address of the director Officers	`"10 Downing Street, London, SW1A 2AA"`
Full Format String Example `"10 Downing Street, London, SW1A 2AA"`
	String	Locality (e.g. City) portion of contact address Officers	`"London"`
Full Format String Example `"London"`
	String	Postcode portion of contact address Officers	`"SW1A 2AA"`
Full Format String Example `"SW1A 2AA"`
	String	Region (e.g. County) portion of contact address Officers	`"Greater London"`
Full Format String Example `"Greater London"`
	String	Street address portion of contact address Officers	`"10 Downing Street"`
Full Format String Example `"10 Downing Street"`
	String	Country part of non-registered address Non-Registered Addresses	`"United States"`
Full Format String Example `"United States"`
	String	Country code part of non-registered address Non-Registered Addresses	`"US", "GB", "AU"`
Full Format String Example `"US", "GB", "AU"`
	String	Address in full – for when it has not been normalized into street address, locality, etc. Non-Registered Addresses	`"Suite 400, 100 Market Street, San Francisco, CA 94105, US"`
Full Format String Example `"Suite 400, 100 Market Street, San Francisco, CA 94105, US"`
	String	Locality (e.g. city) part of non-registered address Non-Registered Addresses	`"San Francisco"`
Full Format String Example `"San Francisco"`
	String	Postal code part of non-registered address Non-Registered Addresses	`"94105"`
Full Format String Example `"94105"`
	String	Region part of non-registered address Non-Registered Addresses	`"California"`
Full Format String Example `"California"`
	String	Country part of registered address Companies	`"United Kingdom", "United States"`
Full Format String – varchar(255) Example `"United Kingdom", "United States"`
	String	Registered address as a single concatenated string. Companies	`"1 Victoria Street, London, SW1H 0ET, United Kingdom"`
Full Format String – text Example `"1 Victoria Street, London, SW1H 0ET, United Kingdom"`
	String	Locality (e.g. city) part of registered address Companies	`"London", "San Francisco"`
Full Format String – varchar(255) Example `"London", "San Francisco"`
	String	Postal code (e.g. ZIP) part of registered address Companies	`"SW1H 0ET", "94105"`
Full Format String – varchar(255) Example `"SW1H 0ET", "94105"`
	String	Region (e.g. state) part of registered address Companies	`"California", "Greater London"`
Full Format String – varchar(255) Example `"California", "Greater London"`
	String	Street address part of registered address Companies	`"1 Victoria Street"`
Full Format String – text Example `"1 Victoria Street"`
	String	Street address part of non-registered address Non-Registered Addresses	`"Suite 400, 100 Market Street"`
Full Format String Example `"Suite 400, 100 Market Street"`
Classification
	String	Address type – e.g. mailing, company Non-Registered Addresses	`"mailing", "trading", "company", null`
Full Format String Example `"mailing", "trading", "company", null` If blank, the address type is unspecified
	Enum	If this is a local registration of a foreign company this will be 'F'. Local branches of entities have an 'L' flag. Companies	`"F", "L", null`
Full Format Enum – 'F', 'L' or null Example `"F", "L", null`
	String	Type of entity (as described by the company register) Companies	`"Private Limited Company", "LLC", "Public Company"`
Full Format String – varchar(1000) Example `"Private Limited Company", "LLC", "Public Company"`
	String	LeadGenius code for the external identifier system. Additional Identifiers	`"gb_vat", "lei", "us_ein", "au_abn"`
Full Format String Example `"gb_vat", "lei", "us_ein", "au_abn"`
	String	Standard Industrial Classifications. Concatenated codes including code scheme and code number. Companies	`"us_sic-7372\|us_sic-7371"`
Full Format String – text: List of SIC codes separated by '\|' Example `"us_sic-7372\|us_sic-7371"`
	Boolean	Whether the company_type indicates it is a nonprofit Companies	`true, false`
Full Format Boolean Example `true, false` Mapping based on company_type
	String	One of the four types of relationship data object LeadGenius maintains: control statement, subsidiary, branch, share_parcel. Relationships	`"control_statement", "subsidiary", "branch", "share_parcel"`
Full Format String Example `"control_statement", "subsidiary", "branch", "share_parcel"`
	Enum	Person or "Company" or null Officers	`"Person", "Company", null`
Full Format Enum Example `"Person", "Company", null`
	String	Alternative name type Alternative Names	`"trading", "previous", "doing-business-as", "translation"`
Full Format String Example `"trading", "previous", "doing-business-as", "translation"`
Contact
	Emails as MD5 and SHA-256 hashes	Generic email tied to the business, not an officer or agent. Companies	`"5f4dcc3b5aa765d61d8327deb882cf99" (MD5)`
Full Format Emails as MD5 and SHA-256 hashes Example `"5f4dcc3b5aa765d61d8327deb882cf99" (MD5)` In cases where the business uses a personal freemail or personal business email, this email will be provided.
	NANP 10 digit	Company phone number, not tied to an officer or agent. Companies	`"4155551234"`
Full Format NANP 10 digit Example `"4155551234"`
	Emails as MD5 and SHA-256 hashes	Direct business email and/or personal freemail email tied to officer or agent Officers	`"5f4dcc3b5aa765d61d8327deb882cf99" (MD5)`
Full Format Emails as MD5 and SHA-256 hashes Example `"5f4dcc3b5aa765d61d8327deb882cf99" (MD5)`
	NANP 10 digit	Mobile phone number tied to officer or agent Officers	`"4155559876"`
Full Format NANP 10 digit Example `"4155559876"`
Content
	String	The given description of the filing Filings	`"Annual accounts and reports filed for the year ending 31 Dec 2023"`
Full Format String – varchar(2000) Example `"Annual accounts and reports filed for the year ending 31 Dec 2023"`
	String	Title of the filing, or the filing_type, or a human-friendly version of the date. Every filing can be relied upon to have a title. Filings	`"Annual Return (AR01)"`
Full Format String – varchar(2000) Example `"Annual Return (AR01)"`
Dates
	Date	Date accounts were last made up Companies	`"2023-12-31"`
Full Format Date – ISO 8601 Example `"2023-12-31"`
	Date	Date accounts are next due Companies	`"2025-01-31"`
Full Format Date – ISO 8601 Example `"2025-01-31"`
	dd/mm	Accounting reference date Companies	`"31/12"`
Full Format dd/mm Example `"31/12"`
	Date	Date returns were last made up Companies	`"2024-06-01"`
Full Format Date – ISO 8601 Example `"2024-06-01"`
	Date	Date annual return next due Companies	`"2025-06-01"`
Full Format Date – ISO 8601 Example `"2025-06-01"`
	Date	Date of the filing as provided by source Filings	`"2024-01-15"`
Full Format Date – ISO 8601 YYYY-MM-DD Example `"2024-01-15"`
	Date	Date of dissolution of entity Companies	`"2021-11-30"`
Full Format Date – YYYY-MM-DD Example `"2021-11-30"`
	Date	End date of officership Officers	`"2022-09-30"`
Full Format Date – YYYY-MM-DD Example `"2022-09-30"`
	Date	End date of an address Non-Registered Addresses	`"2023-12-31"`
Full Format Date – ISO 8601 YYYY-MM-DD Example `"2023-12-31"`
	String	Alternative name known end date Alternative Names	`"2018-06-30"`
Full Format String Example `"2018-06-30"`
	Date	Our best estimate of when the relationship ended. Relationships	`"2023-06-30"`
Full Format Date – YYYY-MM-DD Example `"2023-06-30"`
	String	One of 'at', 'before', or 'after'. Used to refine the end_date field. Relationships	`"at", "before", "after"`
Full Format String Example `"at", "before", "after"`
	Date	Date of incorporation Companies	`"2003-04-15"`
Full Format Date – YYYY-MM-DD Example `"2003-04-15"`
	Date	Date of latest filed accounts Companies	`"2023-12-31"`
Full Format Date – ISO 8601 Example `"2023-12-31"`
	Date	Start date of officership Officers	`"2015-06-01"`
Full Format Date – YYYY-MM-DD Example `"2015-06-01"`
	Date	Start date of an address Non-Registered Addresses	`"2018-03-01"`
Full Format Date – ISO 8601 YYYY-MM-DD Example `"2018-03-01"`
	String	Alternative name known start date Alternative Names	`"2010-01-01"`
Full Format String Example `"2010-01-01"`
	Date	LeadGenius' best estimate of when the relationship began. Relationships	`"2015-01-01"`
Full Format Date – YYYY-MM-DD Example `"2015-01-01"`
	String	One of 'at', 'before', or 'after'. Used to refine the start_date field. Relationships	`"at", "before", "after"`
Full Format String Example `"at", "before", "after"`
Demographics
	String	Country of Residence of the officer Officers	`"United Kingdom", "United States"`
Full Format String Example `"United Kingdom", "United States"`
	String	Nationality of director Officers	`"British", "American", "French"`
Full Format String Example `"British", "American", "French"`
	String	Occupation of director if given Officers	`"Chief Executive Officer", "Chartered Accountant"`
Full Format String Example `"Chief Executive Officer", "Chartered Accountant"`
	Partial Date	Partial date of birth (month and year only) Officers	`"1974-04"`
Full Format Partial Date – YYYY-MM Example `"1974-04"`
Firmographic
	Integer	Current assets in latest accounts, in local currency Companies	`8200000`
Full Format Integer Example `8200000`
	Integer	Cash at bank in latest accounts, in local currency Companies	`1500000`
Full Format Integer Example `1500000`
	Integer	Current liabilities in latest accounts, in local currency Companies	`3400000`
Full Format Integer Example `3400000`
	String	Number of employees at the company Companies	`"250", "1-10", "501-1000"`
Full Format String – varchar(255) Example `"250", "1-10", "501-1000"`
Identifier
	String	Cross-government business numbers for those jurisdictions (e.g. Australia, New Zealand, Canada) that have them Companies	`"ABN 12 345 678 901"`
Full Format String Example `"ABN 12 345 678 901"`
	String	Identifier given by the Company register to the entity. Together with the jurisdiction_code this forms a composite primary key for the companies dataset. Companies	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Company number Officers	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Identifier given by the Company register to the entity. Non-Registered Addresses	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Identifier given by the Company register to the entity. Alternative Names	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Identifier given by the Company register to the entity. Filings	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Identifier given by the Company register to the entity. Additional Identifiers	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Jurisdiction code of the home company, for branch entities. Companies	`"us_de"`
Full Format String – varchar(8) Example `"us_de"`
	String	Company number of the home company if the entity is a branch. Reconciled by LeadGenius. Companies	`"3141592"`
Full Format String – varchar(128) Example `"3141592"`
	String	Jurisdiction of the home company, in cases where the entity is a branch registered in a different jurisdiction Companies	`"Delaware, USA"`
Full Format String Example `"Delaware, USA"`
	Integer	Internal LeadGenius ID for officership Officers	`84726193`
Full Format Integer Example `84726193`
	Integer	LeadGenius ID Filings	`937261048`
Full Format Integer Example `937261048`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code) Companies	`"gb_en", "us_ca", "au_qld"`
Full Format String – varchar(8) Example `"gb_en", "us_ca", "au_qld"`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code). Officers	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code). Non-Registered Addresses	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code). Alternative Names	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code) Filings	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Code for the jurisdiction (lowercase, underscore version of ISO 3166-2 code). Additional Identifiers	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	Integer	LeadGenius' internal identifier for the data object representing the relationship Relationships	`52904817`
Full Format Integer Example `52904817`
	String	On occasion a company number is re-used or renumbered by a registry. This field stores the former number. Companies	`"OLD-445790"`
Full Format String Example `"OLD-445790"`
	String	Companies House uid for the person including address change counter. Officers	`"204942900001"`
Full Format String Example `"204942900001"` Applies to UK data only
	String	Derived person uid from the person_number. Individuals with the same person_uid are asserted by Companies House to be the same person. Officers	`"20494290"`
Full Format String Example `"20494290"` Applies to UK data only
	Integer	The id given to the filing by the company registry Filings	`MzY5NzI4MzM0OGFkaXF6a2N4`
Full Format Integer Example `MzY5NzI4MzM0OGFkaXF6a2N4`
	String	Identifier value Additional Identifiers	`"GB123456789", "LEI-XKZZ2JZF41MRHTR8Y1"`
Full Format String Example `"GB123456789", "LEI-XKZZ2JZF41MRHTR8Y1"`
Metadata
	Datetime	When LeadGenius first became aware of this relationship. Relationships	`"2020-05-12T14:33:00Z"`
Full Format Datetime – ISO 8601 Example `"2020-05-12T14:33:00Z"`
	String	URL of the page for the company on the official corporate register. Companies	`"https://find-and-update.company-information.service.gov.uk/company/00445790"`
Full Format String – text Example `"https://find-and-update.company-information.service.gov.uk/company/00445790"`
	Datetime	Datetime the record was retrieved from the official source Companies	`"2024-03-15T08:22:11Z"`
Full Format Datetime – ISO 8601 Example `"2024-03-15T08:22:11Z"`
	Datetime	Datetime the record was retrieved from the official source Officers	`"2024-03-15T08:22:11Z"`
Full Format Datetime – ISO 8601 Example `"2024-03-15T08:22:11Z"`
	String	URL of the page for the officer on the official corporate register Officers	`"https://find-and-update.company-information.service.gov.uk/officers/xyz/appointments"`
Full Format String – text Example `"https://find-and-update.company-information.service.gov.uk/officers/xyz/appointments"`
	Datetime	When LeadGenius last updated any details on this relationship record. Relationships	`"2024-01-08T09:15:22Z"`
Full Format Datetime – ISO 8601 Example `"2024-01-08T09:15:22Z"`
	String	The URL of the filing. May be an HTML page, or of the document itself. Filings	`"https://find-and-update.company-information.service.gov.uk/company/00445790/filing-history"`
Full Format String – text URL Example `"https://find-and-update.company-information.service.gov.uk/company/00445790/filing-history"`
Name
	String	Alternative legal name (in another language) if provided by the register. Companies	`"АКМЕ КОРПОРЕЙШН"`
Full Format String Example `"АКМЕ КОРПОРЕЙШН"`
	String	Language of the alternative name, if known Companies	`"ru", "zh", "fr"`
Full Format String Example `"ru", "zh", "fr"`
	String	First name of officer Officers	`"John"`
Full Format String Example `"John"`
	String	Last name of the officer. For corporate officers, the company name appears here. Officers	`"Smith"`
Full Format String Example `"Smith"`
	String	Legal name of entity Companies	`"ACME CORPORATION LTD"`
Full Format String – varchar(2000) Example `"ACME CORPORATION LTD"`
	String	Full name of the officer Officers	`"SMITH, John David"`
Full Format String – varchar(2000) Example `"SMITH, John David"`
	String	Alternative name for an entity Alternative Names	`"Acme Trading Co"`
Full Format String Example `"Acme Trading Co"`
	String	Legal name of entity Filings	`"ACME CORPORATION LTD"`
Full Format String – varchar(2000) Example `"ACME CORPORATION LTD"`
	String	Normalized legal name of entity, using LeadGenius normalization. Companies	`"acme corporation"`
Full Format String – varchar(2000) Example `"acme corporation"`
	String	Normalized legal name of entity, using LeadGenius normalization. Filings	`"acme corporation"`
Full Format String – varchar(2000) Example `"acme corporation"`
	String: List separated by '\|'	Previous names the company has traded under Companies	`"Old Name Ltd\|Another Name Inc"`
Full Format String: List separated by '\|' Example `"Old Name Ltd\|Another Name Inc"`
	String	Title of the officer, e.g. "Mr" Officers	`"Mr", "Ms", "Dr", "Sir"`
Full Format String Example `"Mr", "Ms", "Dr", "Sir"`
Object Entity
	String	Company number of the object entity Relationships	`"00112233"`
Full Format String – varchar(128) Example `"00112233"`
	String	Jurisdiction code of the object entity Relationships	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Name of the object entity (the company that controls or owns shares in the subject entity) Relationships	`"ACME HOLDINGS PLC"`
Full Format String – varchar(2000) Example `"ACME HOLDINGS PLC"`
Ownership
	Float	Maximum possible ownership percentage. Only relevant for control relationships. Relationships	`75.0`
Full Format Float Example `75.0`
	Float	Maximum possible voting percentage. Only relevant for control relationships. Relationships	`75.0`
Full Format Float Example `75.0`
	Float	Minimum possible ownership percentage. Only relevant for control relationships. Relationships	`51.0`
Full Format Float Example `51.0`
	Float	Minimum possible voting percentage. Only relevant for control relationships. Relationships	`51.0`
Full Format Float Example `51.0`
Role
	String	Position held by the officer Officers	`"director", "secretary", "chief executive officer"`
Full Format String – varchar(1000) Example `"director", "secretary", "chief executive officer"`
Share Parcel
	Integer	The number of shares in the object entity held by the subject entity. Only relevant for share_parcel relationships. Relationships	`1000000`
Full Format Integer Example `1000000`
Status
	String	Status of entity at retrieved_at date as reported by company registry Companies	`"Active", "Dissolved", "In Administration"`
Full Format String – varchar(1000) Example `"Active", "Dissolved", "In Administration"`
	String	Status of the officership as reported by the company register Officers	`"Active", "Resigned"`
Full Format String Example `"Active", "Resigned"`
	Boolean	Whether company has been liquidated Companies	`true, false`
Full Format Boolean Example `true, false`
	Boolean	Whether company has charges Companies	`true, false`
Full Format Boolean Example `true, false`
	Boolean	Whether company has insolvency history Companies	`true, false`
Full Format Boolean Example `true, false`
	Boolean	A flag that indicates whether a company is in an inactive state. True reflects high confidence of inactivity; false or null means insufficient evidence. Companies	`true, false, null`
Full Format Boolean Example `true, false, null` Mapping based on current_status values
	String	Indicates whether marketing is allowed to this customer Companies	`"true", "false"`
Full Format String – text Example `"true", "false"`
Subject Entity
	String	Company number of the subject entity Relationships	`"00445790"`
Full Format String – varchar(128) Example `"00445790"`
	String	Jurisdiction code of the subject entity Relationships	`"gb_en"`
Full Format String – varchar(8) Example `"gb_en"`
	String	Name of the subject entity Relationships	`"ACME CORPORATION LTD"`
Full Format String – varchar(2000) Example `"ACME CORPORATION LTD"`

Consumer Dataset (US)

Consumer Address & Attributes

Individual- and household-level data covering 500M+ records with address-level fidelity and 470+ unique attributes across 16 enrichment categories.

Field	Type	Description	Example
Automotive
	Boolean (1/0)	Owns a vehicle with a body type classified as Minivan Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a vehicle with a body type classified as Sedan Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a vehicle with a body type classified as SUV Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a vehicle with a body type classified as Truck Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a Compact vehicle Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a Luxury vehicle Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a Mainstream vehicle Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Drive type of an owned vehicle is 4WD Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Drive type of an owned vehicle is AWD Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Drive type of an owned vehicle is FWD Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Drive type of an owned vehicle is RWD Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Fuel type of an owned vehicle is Diesel Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Fuel type of an owned vehicle is Flex Fuel Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Fuel type of an owned vehicle is Gasoline Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Fuel type of an owned vehicle is Hybrid Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	The manufacturer of an owned vehicle is Asia-based Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	The manufacturer of an owned vehicle is European-based Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	The manufacturer of an owned vehicle is USA-based Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Float	The maximum MSRP of an owned vehicle Consumer Attributes	`45000`
Full Format Float Example `45000`
	Float	The minimum MSRP of an owned vehicle Consumer Attributes	`25000`
Full Format Float Example `25000`
	Boolean (1/0)	Purchased a new vehicle Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Indicates ownership of a car Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Indicates ownership of an SUV Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Indicates ownership of a truck Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Indicates ownership of a van Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Integer (year)	Earliest model year of an owned vehicle Consumer Attributes	`2015`
Full Format Integer (year) Example `2015`
	Integer (year)	Latest model year of an owned vehicle Consumer Attributes	`2022`
Full Format Integer (year) Example `2022`
	Integer	Number of vehicles in household Consumer Attributes	`1, 2, 3`
Full Format Integer Example `1, 2, 3`
Behavioral
	Boolean (1/0)	Owns a Cat Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a Dog Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Healthy Living lifestyle indicator Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Comprised of three or more luxury interests: Gourmet Cooking, Health Foods, Natural Foods, Wines, Fashion Clothing, and Home Décor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Purchased a magazine Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a pet Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Operates a business out of the home Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Likes Cruise Travel Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Lifestyle Foreign Travel Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Vacation Travel Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a truck or pick-up truck Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
Consumer Interest Index
	Integer (0-9)	Affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`7`
Full Format Integer (0-9) Example `7`
	Integer (0-9)	Apparel affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`6`
Full Format Integer (0-9) Example `6`
	Integer (0-9)	Auto interest affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`4`
Full Format Integer (0-9) Example `4`
	Integer (0-9)	Bargain hunter affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`8`
Full Format Integer (0-9) Example `8`
	Integer (0-9)	Beauty affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`7`
Full Format Integer (0-9) Example `7`
	Integer (0-9)	Catalog affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`5`
Full Format Integer (0-9) Example `5`
	Integer (0-9)	Cooking affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`8`
Full Format Integer (0-9) Example `8`
	Integer (0-9)	Donor affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`5`
Full Format Integer (0-9) Example `5`
	Integer (0-9)	Fitness affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`6`
Full Format Integer (0-9) Example `6`
	Integer (0-9)	Gardening affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`7`
Full Format Integer (0-9) Example `7`
	Integer (0-9)	Golf affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`5`
Full Format Integer (0-9) Example `5`
	Integer (0-9)	Health interest affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`8`
Full Format Integer (0-9) Example `8`
	Integer (0-9)	Home Decorating affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`6`
Full Format Integer (0-9) Example `6`
	Integer (0-9)	Outdoors affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`5`
Full Format Integer (0-9) Example `5`
	Integer (0-9)	Pets affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`7`
Full Format Integer (0-9) Example `7`
	Integer (0-9)	Travel affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`5`
Full Format Integer (0-9) Example `5`
	Integer (0-9)	Women's Apparel affinity score — 0=No Interest, 1=Weakest, 9=Strongest Consumer Attributes	`6`
Full Format Integer (0-9) Example `6`
Data Quality
	Boolean (1/0)	The record links back to the National Consumer Database Consumer Attributes	`1 (Yes), 0 (No)`
Full Format Boolean (1/0) Example `1 (Yes), 0 (No)`
Demographic
	Integer	Numerical Age Consumer Attributes	`35, 52, 68`
Full Format Integer Example `35, 52, 68`
	Integer	Birth Year Consumer Attributes	`1978, 1955, 1990`
Full Format Integer Example `1978, 1955, 1990`
	String	Highest level of education attained Consumer Attributes	`"Completed College", "Completed Graduate School", "Some High School"`
Full Format String Example `"Completed College", "Completed Graduate School", "Some High School"`
	Integer (1-7)	Education level as ordinal integer. 1=Some High School, 3=Completed HS, 5=Completed College, 7=Doctorate Consumer Attributes	`5 (Completed College)`
Full Format Integer (1-7) Example `5 (Completed College)`
	String	Ethnic grouping Consumer Attributes	`"White", "Hispanic", "African American", "Asian", "Jewish"`
Full Format String Example `"White", "Hispanic", "African American", "Asian", "Jewish"`
	Boolean (1/0)	African American Ethnicity Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Asian Ethnicity Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String	Detailed ethnicity classification Consumer Attributes	`"English", "German", "Irish", "Hispanic", "Italian"`
Full Format String Example `"English", "German", "Irish", "Hispanic", "Italian"`
	Boolean (1/0)	Hispanic Ethnicity Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	White Ethnicity Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String	Primary name given - may contain initial only Consumer Address	`"JOHN", "M"`
Full Format String Example `"JOHN", "M"`
	String	Gender, as provided by the participants and overlays Consumer Address	`"M" (Male), "F" (Female)`
Full Format String Example `"M" (Male), "F" (Female)`
	String	Gender Consumer Attributes	`"Female", "Male"`
Full Format String Example `"Female", "Male"`
	String	Generational cohort of the individual Consumer Attributes	`"2. Generation X (1961-1981)", "3. Baby Boomers (1943-1960)"`
Full Format String Example `"2. Generation X (1961-1981)", "3. Baby Boomers (1943-1960)"`
	Integer	Generational cohort as ordinal integer. 1=Millennials/Gen Z, 2=Gen X, 3=Boomers, 4=Post-WWII Consumer Attributes	`2`
Full Format Integer Example `2`
	Boolean (1/0)	Has email address Consumer Address	`1 (Yes), 0 (No)`
Full Format Boolean (1/0) Example `1 (Yes), 0 (No)`
	Boolean (1/0)	Has known email address Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Has phone number Consumer Address	`1 (Yes), 0 (No)`
Full Format Boolean (1/0) Example `1 (Yes), 0 (No)`
	Boolean (1/0)	Has known phone number Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Known Hispanic Ancestry Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String	Preferred language of the individual Consumer Attributes	`"English", "Spanish", "Chinese (Mandarin, Cantonese and other dialects)"`
Full Format String Example `"English", "Spanish", "Chinese (Mandarin, Cantonese and other dialects)"`
	String	Surname (Last Name) - compressed to eliminate spaces and special characters Consumer Address	`"SMITH", "ODONNELL"`
Full Format String Example `"SMITH", "ODONNELL"`
	String	Marital Status Consumer Attributes	`"Married", "Single"`
Full Format String Example `"Married", "Single"`
	Boolean (1/0)	Married flag Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Speaks multiple languages Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String	Religious affiliation Consumer Attributes	`"Protestant", "Catholic", "Jewish", "Buddhist", "Islamic / Muslim"`
Full Format String Example `"Protestant", "Catholic", "Jewish", "Buddhist", "Islamic / Muslim"`
	Boolean (1/0)	Speaks English Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
Donor Behavior
	Boolean (1/0)	Indicates An Individual's Propensity To Be A Charitable Donor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Donates to Animal Causes Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Donates to Art/Cultural causes Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Donates to Children's Cause Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Environmental Contributor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Health Contributor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Political Contributor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Donates to Conservative Political Party Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Donates to Liberal Party Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Contributor for a Social Cause Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Religious Contributor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Veterans Contributor Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String (range)	Average dollars donated per donation in the last 36 months Consumer Attributes	`"A. 1-100", "B. 101-500", "C. 501-1000"`
Full Format String (range) Example `"A. 1-100", "B. 101-500", "C. 501-1000"`
	String (range)	Total number of donations in the last 36 months Consumer Attributes	`"A. 1 to 10", "B. 11 to 25"`
Full Format String (range) Example `"A. 1 to 10", "B. 11 to 25"`
	Integer	Number of different charities donated to Consumer Attributes	`1, 2, 3+`
Full Format Integer Example `1, 2, 3+`
EAGLES
	String	EAGLES 120 Segment — see documentation Consumer Attributes	`See documentation`
Full Format String Example `See documentation`
	String	EAGLES 18 Segment — income + age + marital status segment Consumer Attributes	`"GT_90K__1959_1973_M" (High-Income Marrieds)`
Full Format String Example `"GT_90K__1959_1973_M" (High-Income Marrieds)`
	String	EAGLES 4800 Segment — most granular EAGLES segmentation Consumer Attributes	`See documentation`
Full Format String Example `See documentation`
	String	EAGLES 60 Segment — income + age + marital status + urbanicity Consumer Attributes	`"GT_90K__1957_1967_M_U"`
Full Format String Example `"GT_90K__1957_1967_M_U"`
Financial
	Boolean (1/0)	Owns a regular American Express credit card Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a bank credit card Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns a credit card Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Integer	Credit rating range midpoint in the household Consumer Attributes	`725, 775`
Full Format Integer Example `725, 775`
	String (range)	Credit rating range in the household Consumer Attributes	`"C. 700-749", "A. 800+"`
Full Format String (range) Example `"C. 700-749", "A. 800+"`
	String (range)	Total household income Consumer Attributes	`"H. $75,000-$99,999", "K. $100,000-$149,999"`
Full Format String (range) Example `"H. $75,000-$99,999", "K. $100,000-$149,999"`
	String (range)	Individual income range estimate Consumer Attributes	`"LT_30K", "30K_50K", "50K_74K"`
Full Format String (range) Example `"LT_30K", "30K_50K", "50K_74K"`
	Integer	Individual income range midpoint Consumer Attributes	`87500, 125000`
Full Format Integer Example `87500, 125000`
	Boolean (1/0)	Known investor flag Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Integer	Median income Consumer Attributes	`75000`
Full Format Integer Example `75000`
	String (range)	Predicted net worth range based on Home Value, Age, dwelling size, and census data. Consumer Attributes	`"H. $100,000 - $249,999", "J. Greater than $499,999"`
Full Format String (range) Example `"H. $100,000 - $249,999", "J. Greater than $499,999"`
	Integer	Net worth range midpoint Consumer Attributes	`175000, 750000`
Full Format Integer Example `175000, 750000`
	String (range)	Range of new credit granted for an individual within the household Consumer Attributes	`"E. $1,001 - $3,000", "H. Greater than $9,999"`
Full Format String (range) Example `"E. $1,001 - $3,000", "H. Greater than $9,999"`
	Integer	Number of credit lines in the household Consumer Attributes	`1, 2, 3`
Full Format Integer Example `1, 2, 3`
	Boolean (1/0)	Owns investments Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Owns stocks or bonds Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Indicates possession of one or more premium credit cards in a household Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	String (range)	Premium Household Income range Consumer Attributes	`"D. $50K-$60K", "K. $120K-$130K"`
Full Format String (range) Example `"D. $50K-$60K", "K. $120K-$130K"`
	Integer	Premium household income range midpoint Consumer Attributes	`55000, 125000`
Full Format Integer Example `55000, 125000`
Geographic
	String	Address post-direction, e.g., N, S, E, W, etc. Consumer Address	`"NE"`
Full Format String Example `"NE"`
	String	Address pre-direction, e.g., N, S, E, W, etc. Consumer Address	`"N", "SW"`
Full Format String Example `"N", "SW"`
	String	Primary address Consumer Address	`"123 MAIN"`
Full Format String Example `"123 MAIN"`
	String	Secondary address: apartment, building and/or lot number. Consumer Address	`"APT 4B", "SUITE 200"`
Full Format String Example `"APT 4B", "SUITE 200"`
	String	Street name Consumer Address	`"MARKET"`
Full Format String Example `"MARKET"`
	String	Address suffix (street type abbreviation) Consumer Address	`"ST", "AVE", "BLVD"`
Full Format String Example `"ST", "AVE", "BLVD"`
	String	Full address not parsed Consumer Address	`"123 MAIN ST"`
Full Format String Example `"123 MAIN ST"`
	String	Address Type (A=Other, G=General Delivery, H=Highway, P=PO Box, R=Rural Route, S=Street) Consumer Address	`"S" (Street), "P" (PO Box), "H" (Highway)`
Full Format String Example `"S" (Street), "P" (PO Box), "H" (Highway)`
	String	Carrier Route Code. Postal requirement when carrier route pre-sort is requested. Consumer Address	`"C042"`
Full Format String Example `"C042"`
	String	CBSA (Core Base Statistical Area) codes. Cover 93% of population including Metropolitan and Micropolitan areas. Consumer Address	`"41860" (San Francisco-Oakland-Hayward)`
Full Format String Example `"41860" (San Francisco-Oakland-Hayward)`
	String	Smallest geographic unit used by the US Census Bureau for tabulation. Range: 000-999 Consumer Address	`"012"`
Full Format String Example `"012"`
	String	Census Block Group — statistical divisions of census tracts between 600-3,000 people. Range: 0-9 Consumer Address	`"3"`
Full Format String Example `"3"`
	String	Census Tracts are small, relatively permanent statistical subdivisions of a county. Consumer Address	`"010100"`
Full Format String Example `"010100"`
	String	City Consumer Address	`"SAN FRANCISCO"`
Full Format String Example `"SAN FRANCISCO"`
	String	U.S. Congressional Districts — Range: 00-53 Consumer Address	`"12" (CA-12)`
Full Format String Example `"12" (CA-12)`
	String	County name Consumer Address	`"San Francisco"`
Full Format String Example `"San Francisco"`
	String	Designated Market Area Code — represents a geographic television viewing market. Range: 500-999 Consumer Address	`"807" (San Francisco)`
Full Format String Example `"807" (San Francisco)`
	String	Delivery Point Barcode (Internal field) — Range: 001-999 Consumer Address	`"023"`
Full Format String Example `"023"`
	String	DPV validated. A non-empty value = DPV validated Consumer Address	`"Y"`
Full Format String Example `"Y"`
	String	Federal Information Processing Standard County Codes — Range: 000-999 Consumer Address	`"075" (San Francisco)`
Full Format String Example `"075" (San Francisco)`
	String	Federal Information Processing Standard State Codes — Range: 00-56 Consumer Address	`"06" (California)`
Full Format String Example `"06" (California)`
	Float	Latitude — decimal is 6 places from the right. E.g. 80954671 = 80.954671 Consumer Address	`37774929 (= 37.774929)`
Full Format Float Example `37774929 (= 37.774929)`
	Float	Longitude — decimal is 6 places from the right. Longitudes are 2 or 3 digits before decimal. Consumer Address	`122419416 (= 122.419416)`
Full Format Float Example `122419416 (= 122.419416)`
	String	Metropolitan Statistical Area code — Range: 1-9999 Consumer Address	`"7360"`
Full Format String Example `"7360"`
	String	SCF code — first three digits of the ZIP code. Range: 006-999 Consumer Address	`"941"`
Full Format String Example `"941"`
	String	State abbreviation (2-character US state code) Consumer Address	`"CA", "NY", "TX"`
Full Format String Example `"CA", "NY", "TX"`
	String	Urban-Rural Classification (U=Urban, S=Suburban, R=Rural) Consumer Address	`"U" (Urban), "S" (Suburban), "R" (Rural)`
Full Format String Example `"U" (Urban), "S" (Suburban), "R" (Rural)`
	String	Standard zip code - full five position zip code Consumer Address	`"94105"`
Full Format String Example `"94105"`
	String	Standard zip code + 4 — Range: 0001-9999 Consumer Address	`"2301"`
Full Format String Example `"2301"`
Household Composition
	Boolean (1/0)	Presence of Children in Household Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Integer	The number of adults in the household Consumer Attributes	`1, 2, 3`
Full Format Integer Example `1, 2, 3`
	Integer	The number of children in the household Consumer Attributes	`1, 2, 3`
Full Format Integer Example `1, 2, 3`
	Integer	The number of people in the household Consumer Attributes	`1, 2, 4`
Full Format Integer Example `1, 2, 4`
	Boolean (1/0)	Veteran in household Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
Interests
	Boolean (1/0)	Interest in cooking Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Likes Fitness Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Gardening interest Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Likes Golfing Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
	Boolean (1/0)	Home Decorators Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`
Internal
	String	Persistent Address ID Consumer Address	`"ADDR-00456789012"`
Full Format String Example `"ADDR-00456789012"`
	String	Persistent Address ID Consumer Attributes	`"ADDR-00456789012"`
Full Format String Example `"ADDR-00456789012"`
	String	Persistent Household ID Consumer Address	`"HH-00987654321"`
Full Format String Example `"HH-00987654321"`
	String	Persistent Household ID Consumer Attributes	`"HH-00987654321"`
Full Format String Example `"HH-00987654321"`
	String	Persistent Individual ID Consumer Address	`"IND-00123456789"`
Full Format String Example `"IND-00123456789"`
	String	Persistent Individual ID Consumer Attributes	`"IND-00123456789"`
Full Format String Example `"IND-00123456789"`
	Boolean (1/0)	The record links back to the National Consumer Database Consumer Address	`1 (Yes), 0 (No)`
Full Format Boolean (1/0) Example `1 (Yes), 0 (No)`
	Integer	Number of contributing sources Consumer Attributes	`3`
Full Format Integer Example `3`
Occupations
	String	Occupation category of the individual Consumer Attributes	`"Professional", "Blue Collar", "Homemaker", "Retired", "Upper Management"`
Full Format String Example `"Professional", "Blue Collar", "Homemaker", "Retired", "Upper Management"`
	String	Detailed occupation of the individual Consumer Attributes	`"Manager", "Engineer", "Homemaker", "Nurse", "Teacher"`
Full Format String Example `"Manager", "Engineer", "Homemaker", "Nurse", "Teacher"`
Political
	String	Political party affiliation Consumer Attributes	`"Republican", "Democrat", "Independent"`
Full Format String Example `"Republican", "Democrat", "Independent"`
Real Estate
	Integer (1, 3, 4)	Home ownership status. 1=Renter, 3=Probable Home Owner, 4=Home Owner Consumer Attributes	`4 (Home Owner), 1 (Renter)`
Full Format Integer (1, 3, 4) Example `4 (Home Owner), 1 (Renter)`
	Boolean (1/0)	Single family residence Consumer Attributes	`1 (Yes)`
Full Format Boolean (1/0) Example `1 (Yes)`

Reference

File Format & Delivery

Specifications for how bulk data is packaged, transferred, and structured.

Naming: Folders named by "as-at" date — e.g. 2016-06-01
Compression: Gzip with .gz extension. Includes md5sum file with checksums.
Transfer: SFTP. Authentication via password or private-key certificate.
File Format: CSV per RFC 4180. Comma-separated. UTF-8. Unix line endings.
Field Enclosure: Optional double-quotes when a field contains a comma. Quotes escaped with double-quotes.
Cadence: Quarterly, monthly, or weekly depending on subscription.

Data Types

Type	Description
`varchar(255)`	String up to 255 characters
`text`	String up to 65,535 bytes
`mediumtext`	String up to 16MB
`longtext`	String up to 4GB
`pipe separated`	Variable length, may need ETL normalization
`boolean`	true, false, or blank for "unknown"

Delivery Latency

Data flows through 5 stages: Fetching (5 min to 2 weeks), Processing (immediate), Ingestion (every 5 min, <24h typical), Extraction (every 4 days, 1 min to 12h), and Delivery (10 min to 1 hour). Each jurisdiction has its own pace.

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Bulk Delivery Data Dictionary

B2B Attributes

Companies

Officers

Non-Registered Addresses

Alternative Names

Filings

Additional Identifiers

Relationships

Consumer Address

Consumer Attributes

B2B Attributes

Corporate Registry & Contact

Consumer Address & Attributes

File Format & Delivery

Data Types

Delivery Latency

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