Welcome to Enigma! Here you'll find comprehensive guides and documentation to help you start working with Enigma's Businesses product as quickly as possible, as well as support if you get stuck. Let's jump right in!
This page defines the list of attributes available in the Businesses API. For each attribute, we denote the output values and how to interpret them.
For certain premium attributes listed below, historical data going back to 2017 is available.
card_revenue
card_revenue_growth
card_transactions
card_transactions_stability
card_customers
refunds
The historical MTX attributes listed above can be accessed using the ID endpoint for both Business and Business Location entities. See our ID endpoint reference for guidance on how to call these premium attributes.
Our basic attributes help you identify the right businesses for easy integration into your workflows.
Attributes |
|---|
Indicates the extent to which the user’s query matched a business record in Enigma’s SMB data asset, where 1 represents an exact match. (Number from 0 to 1) `matched_fields`Shows the name, address, and person in Enigma’s data asset, that were found in relation to the user’s query Child Attributes`name` `person` `address``address`Child Attributes`street_address1` `street_address2` `city` `state` `postal_code`Whether the `match_confidence` for the returned business exceeds the match threshold. To return `non_matches`, set `show_non_matches: 1` in your Request parameters |
{
"match_confidence": 0.97,
"matched_fields": {
"name": "ENIGMA TECHNOLOGIES INC",
"address": {
"street_address1": "245 5 AVE",
"street_address2": "FL 17",
"city": "NEW YORK",
"state": "NY",
"postal_code": "10016"
},
"person": "HICHAM OUDGHIRI"
},
"is_matched": true
}
Attributes |
|---|
Enigma's unique identifier for the business `aliases`The various names for the business found in Enigma’s data sources, ordered by prevalence `addresses`List of addresses for the business containing street, city, state, and postal code `ein`The EIN numbers associated with the business `phone_numbers`The phone numbers associated with the business `year_incorporated`Year of the earliest incorporation date found in Enigma’s data sources `websites`List of website URLs associated with the business |
{
"aliases": [
"ENIGMA TECHNOLOGIES INC"
],
"ein": [
"12-3456789"
],
"year_incorporated": "2011",
"websites": [
"https://www.enigma.com/"
]
}
Attributes |
|---|
People associated with the business and their titles
A registered agent is a business or individual designated to receive service of process when a business is involved in a legal matter
The legal structure under which the business is incorporated |
{
"associated_people": [
{
"name": "HICHAM OUDGHIRI",
"titles": [
"OFFICER"
]
}
],
"registered_agents": [
"ENIGMA TECHNOLOGIES INC",
"CORPORATION SERVICE COMPANY"
],
"corporate_structure": "CORPORATION"
}
Attributes |
|---|
A list of states and corresponding registration dates for state-level corporate registrations found in Enigma’s data sources Child Attributes`state` `issue_date` `file_number` |
{
"registrations": [
{
"state": "NY",
"issue_date": "2011-11-09",
"file_number": "4163621"
}
]
}
We model our premium attributes from hundreds of private and public sources to provide unique signals about a business.
Premium attributes can be retrieved through the ID endpoint by selecting codes for desired premium attributes with the attrs query parameter. For example, to select premiums attributes with codes abc and def, append the query parameters ?attrs=abc,def to the end of the URL for the ID endpoint. See Quick Start for more details.
Attributes |
|---|
A list of objects describing the average monthly revenue a business receives from credit and debit card transactions across 1 month, 3 month and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`start_date`The date that the 1-month period begins, inclusive. `average_monthly_amount`The business's card revenue in the 1 month leading up to and including end_date, Child Attributes`start_date`The date that the 3-month period begins, inclusive. `average_monthly_amount`The business's average monthly card revenue in the 3 months leading up to and including end_date, Child Attributes`start_date`The date that the 12-month period begins, inclusive. `average_monthly_amount`The business's average monthly card revenue in the 12 months leading up to and including end_date, |
{
"card_revenue": [
{
"end_date": "2020-08-31",
"1m": {
"start_date": "2020-08-01",
"average_monthly_amount": 1200.11
},
"3m": {
"start_date": "2020-06-01",
"average_monthly_amount": 1400.77
},
"12m": {
"start_date": "2019-09-01",
"average_monthly_amount": 3200.80
}
}
]
}
Attributes |
|---|
A list of objects describing the revenue growth trends at a business, measured across 3 month, 3 month (seasonally adjusted) and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`start_date`The date that the 3-month period begins, inclusive. `rate`The change in revenue in the past 3 months from the 3 months prior, expressed as a ratio, The change in revenue in the past 3 months from the corresponding 3 months a year prior, expressed as a ratio, Child Attributes`start_date`The date that the 12-month period begins, inclusive. `rate`The change in revenue in the past 12 months from the 12 months prior, expressed as a ratio, |
{
"card_revenue_growth": [
{
"end_date": "2020-08-31",
"3m": {
"start_date": "2020-06-01",
"rate": 0.1320,
"rate_sa": 0.0218
},
"12m": {
"start_date": "2019-09-01",
"rate": 0.1338
}
}
]
}
Attributes |
|---|
A list of objects describing the average monthly number of credit and debit card transactions at a business across 1 month, 3 month and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`start_date`The date that the 1-month period begins, inclusive. `average_monthly_count`The average monthly number of transactions over the month leading up to and including end_date, Whether or not we have transactions for the given business in the 1-month period. Child Attributes`start_date`The date that the 3-month period begins, inclusive. `average_monthly_count`The average monthly number of transactions over the 3 months leading up to and including end_date, Whether or not we have transactions for the given business in the 3-month period. Child Attributes`start_date`The date that the 12-month period begins, inclusive. `average_monthly_count`The average monthly number of transactions over the 12 months leading up to and including end_date, Whether or not we have transactions for the given business in the 12-month period. |
{
"card_transactions": [
{
"end_date": "2020-08-31",
"1m": {
"start_date": "2020-08-01",
"average_monthly_count": null,
"present": true
},
"3m": {
"start_date": "2020-06-01",
"average_monthly_count": 140.25,
"present": true
},
"12m": {
"start_date": "2019-09-01",
"average_monthly_count": 250.30,
"present": true
}
}
]
}
Attributes |
|---|
A list of objects describing the distribution of credit and debit card transactions at a business across 1 month, 3 month and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`start_date`The date that the 1-month period begins, inclusive. `days_present`The number of days with card transactions in the month leading up to and including end_date. `daily_coverage_ratio`The ratio of days with card transactions to the total number of days in the month leading up to and including end_date. `weeks_present`The number of weeks with card transactions in the month leading up to and including end_date. `weekly_coverage_ratio`The ratio of weeks with card transactions to the total number of weeks in the month leading up to and including end_date. `months_present`1 if the month had any transactions, 0 otherwise. Raw values. ` monthly_coverage_ratio`1 if the month had any transactions, 0 otherwise. Child Attributes`start_date`The date that the 3-month period begins, inclusive. `days_present`The number of days with card transactions in the 3 months leading up to and including end_date. `daily_coverage_ratio`The ratio of days with card transactions to the total number of days in the 3 months leading up to and including end_date. `weeks_present`The number of weeks with card transactions in the 3 months leading up to and including end_date. `weekly_coverage_ratio`The ratio of weeks with card transactions to the total number of weeks in the 3 months leading up to and including end_date. `months_present`The number of months with card transactions in the 3 months leading up to and including end_date. ` monthly_coverage_ratio`The ratio of months with card transactions to the total number of months in the 3 months leading up to and including end_date. Child Attributes`start_date`The date that the 12-month period begins, inclusive. `days_present`The number of days with card transactions in the 12 months leading up to and including end_date. `daily_coverage_ratio`The ratio of days with card transactions to the total number of days in the 12 months leading up to and including end_date. `weeks_present`The number of weeks with card transactions in the 12 months leading up to and including end_date. `weekly_coverage_ratio`The ratio of weeks with card transactions to the total number of weeks in the 12 months leading up to and including end_date. `months_present`The number of months with card transactions in the 12 months leading up to and including end_date. ` monthly_coverage_ratio`The ratio of months with card transactions to the total number of months in the 12 months leading up to and including end_date. |
{
"card_transactions_stability" : [
{
"end_date": "2020-08-31",
"date_accessible": "2020-11-15",
"1m": {
"start_date": "2020-08-01",
"days_present": 25,
"weeks_present": 3,
"months_present": 1,
"daily_coverage_ratio": 0.8064,
"weekly_coverage_ratio": 0.75,
"monthly_coverage_ratio": 1
},
"3m": {
"start_date": "2020-06-01",
"days_present": 61,
"weeks_present": 6,
"months_present": 3,
"daily_coverage_ratio": 0.6777,
"weekly_coverage_ratio": 0.5,
"monthly_coverage_ratio": 0.6667
},
"12m": {
"start_date": "2019-09-01",
"days_present": 110,
"weeks_present": 15,
"months_present": 4,
"daily_coverage_ratio": 0.3013,
"weekly_coverage_ratio": 0.2884,
"monthly_coverage_ratio": 0.3333
}
}
]
}
Attributes |
|---|
A list of objects describing the daily average number of customers a business has, based on credit and debit card transactions, across 1 month, 3 month, and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`start_date`The date that the 1-month period begins, inclusive. `average_daily_count`The business's average daily customer count in the 1 month leading up to and including end_date, Child Attributes`start_date`The date that the 3-month period begins, inclusive. `average_daily_count`The business's average daily customer count in the 3 months leading up to and including end_date, Child Attributes`start_date`The date that the 12-month period begins, inclusive. `average_daily_count`The business's average daily customer count in the 12 months leading up to and including end_date, |
{
"card_customers": [
{
"end_date": "2020-08-31",
"1m": {
"start_date": "2020-08-01",
"average_daily_count": 10.20
},
"3m": {
"start_date": "2020-06-01",
"average_daily_count": 30.15
},
"12m": {
"start_date": "2019-09-01",
"average_daily_count": 70.68
}
}
]
}
Attributes |
|---|
A list of objects describing the refunds issued by a business, based on credit and debit card transactions, across 1 month, 3 month, and 12 month periods. Child Attributes`end_date`All fields below assume this is the final date, inclusive, of the calculation. Using the query param `lookback_months` the number of months of historical data being pulled can be configured.
Child Attributes`average_transaction_size`The average size in dollars of a card refund issued directly from the business in the 1-month period, The ratio of the business’s dollar amount of card refunds to the business’s positive card spend in the 1-month period, The change in the business’s refund to revenue ratio in the 1-month period, The date that the 1-month period begins, inclusive. `amount`The total dollar amount of card refunds issued directly from the business in the 1-month period, Child Attributes`average_transaction_size`The average size in dollars of a card refund issued directly from the business in the 3-month period, The ratio of the business’s dollar amount of card refunds to the business’s positive card spend in the 3-month period, The change in the business’s refund to revenue ratio in the 3-month period, The date that the 3-month period begins, inclusive. `amount`The total dollar amount of card refunds issued directly from the business in the 3-month period, Child Attributes`average_transaction_size`The average size in dollars of a card refund issued directly from the business in the 12-month period, The ratio of the business’s dollar amount of card refunds to the business’s positive card spend in the 12-month period, The change in the business’s refund to revenue ratio in the 12-month period, The date that the 12-month period begins, inclusive. `amount`The total dollar amount of card refunds issued directly from the business in the 12-month period, |
{
"refunds": [
{
"end_date": "2020-08-31",
"1m": {
"average_transaction_size": null,
"revenue_ratio": 0.0,
"revenue_ratio_growth_rate": null,
"start_date": "2020-08-01",
"amount": 0.0
},
"3m": {
"average_transaction_size": -23.35,
"revenue_ratio": 0.0,
"revenue_ratio_growth_rate": -0.95,
"start_date": "2020-06-01",
"amount": -70.04
},
"12m": {
"average_transaction_size": -198.88,
"revenue_ratio": 0.0,
"revenue_ratio_growth_rate": 18.12,
"start_date": "2019-09-01",
"amount": -1591.05
}
}
]
}
Attributes |
|---|
The score from 0 to 1 represents Enigma’s confidence, based on the verification components below. Child Attributes`score` `components``components`Child Attributes`data_freshness`The recency of data observed about the business `source_quality`The trustworthiness of sources in which the data is found `data_footprint`The breadth of data available about the business `business_activity`A measure of recent activity observed in our data sources |
{
"verification": {
"score": 0.86,
"components": {
"data_freshness": 1.0,
"source_quality": 1.0,
"data_footprint": 0.53,
"business_activity": 1.0
}
}
}
Attributes |
|---|
Whether the business has filed for bankruptcy and a list of the bankruptcy filings’ chapter type, filing date, and case number Child Attributes`bankruptcy_flag`Yes/No whether the business has at least one bankruptcy record `bankruptcy_records``bankruptcy_records`Child Attributes`chapter_type`Chapter 7, 11, or 13 `filing_date`Date of bankruptcy filing `case_number`Case number corresponding to bankruptcy filing |
{
"business_bankruptcy": {
"bankruptcy_flag": true,
"bankruptcy_records": [
{
"chapter_type": "11",
"filing_date": "2020-03-15",
"case_number": "2:13-bk-39635"
},
{
"chapter_type": "7",
"filing_date": "2020-04-19",
"case_number": "2:14-bk-17090"
}
]
}
}
Attributes |
|---|
The overall number, value, and status of loans the businesses have received from the SBA, as well as individual loan details. Child Attributes`total_number`The total number of SBA loans
The total amount approved in USD
The total number of active loans
The total amount active in USD
The number of loans with charge offs
The total amount active in USD
Child Attributes`approval_date` `loan_status` `gross_approval_amount` `loan_type` |
{
"sba_loans": {
"total_number": 5,
"total_value": 1200000.5,
"total_number_active": 1,
"total_value_active": 200000.5,
"total_number_charged_off": 0,
"total_value_charged_off": 0.0,
"loan_details": [
{
"approval_date": "2017-10-01",
"loan_status": "PIF",
"gross_approval_amount": 25000.5,
"term_months": 120,
"loan_type": "7a"
}
]
}
}
Attributes |
|---|
A list of all construction contractor licenses this business has been awarded, state-by-state, in the states we cover. Child Attributes`state`The state in which this license was issued. Child Attributes`has_license_history`Whether or not the business has a license in that state. `licenses`A list of all contracts the business has in that state, each with four standard fields. Child Attributes`license_number`A standard field pulled from whichever column in `details` most closely represents the license number. `start_date`A standard field pulled from whichever column in `details` most closely represents the license's start date. `end_date`A standard field pulled from whichever column in `details` most closely represents the license's end date. `classification`A standard field pulled from whichever column in `details` most closely represents what type of work the license is for.
A list of additional fields that come directly from the source. There will be a different set with more or fewer fields depending on the state and license classification. The ones listed below are for illustration to give a sense of what this could look like. Child Attributes`issue_date`Date on which the license was issued `reissue_date`Date on which the license was re-issued, if applicable `effective_date`Effective date for the license `expiration_date`Expiration date for the license `license_number`Identifying number for the license `primary_status`The primary purpose for which the construction license is used `license_type`The type of construction activities covered by the license |
{
"construction_contractor_licenses": {
"CA": {
"has_license_history": true,
"licenses" : [
{
"license_number": "78210512",
"start_date": "2017-01-01",
"end_date": "2022-12-31",
"classification": "Cementing",
"details": {
"issue_date": "2012-01-01",
"reissue_date": "2016-01-01",
"effective_date": "2017-01-01",
"expiration_date": "2022-12-31",
"license_number": "78210512",
"primary_status": "Commercial",
"license_type": "Cementing"
}
}
]
},
"FL": {
"has_license_history": false,
"licenses" : []
},
"MD": {
"has_license_history": false,
"licenses" : []
},
"NC": {
"has_license_history": false,
"licenses" : []
},
... // additional states
}
}
Attributes |
|---|
A list of the predicted industries of this company according to Enigma’s industry taxonomy, as well as mappings to common industry classification systems for integration purposes. Child Attributes`enigma_industry`Enigma's custom classification for the industry that describes the business' activities `sector`The sector in which the business operates, as classified by predicted GICS `industry_group`The high-level industry group in which the business operates `industry`The specific industry category in which the business operates `sub_industry`The detailed, granular industry category in which the business operates `predicted_naics_code`The predicted NAICS code corresponding to the business' industry classification `predicted_gics_code`The predicted GICS code corresponding to the business' sector classification _“GICS” is the trademark of Standard & Poor’s Financial Services LLC (S&P) and MSCI. Use of "GICS" does not imply any affiliation with or endorsement by S&P or MSCI._ |
{
"industry_beta": [
{
"enigma_industry": "Construction and Engineering",
"sector": "Industrials",
"industry_group": "Capital Goods",
"industry": "Construction and Engineering",
"sub_industry": "Construction and Engineering",
"predicted_naics_code": 23,
"predicted_gics_code": 20103010
},
{
"enigma_industry": "Construction Materials",
"sector": "Materials",
"industry_group": "Materials",
"industry": "Construction Materials",
"sub_industry": null,
"predicted_naics_code": 23,
"predicted_gics_code": 15102010
}
]
}
Attributes |
|---|
One entry per WARN notification containing details on the number of employees and date of layoff. The Worker Adjustment and Retraining Notification (WARN) Act of 1988 is a federal law that requires companies that employ more than 100 employees to give 60-day advance notice if they intend to lay off more than 50 employees at a single site. Thus, this is a leading indicator of business health and headcount. Child Attributes`layoff_or_closing`either "layoff" or "closing" depending on what the notification was.
The date on which the notice was received.
The number of employees impacted.
The total headcount before the layoff.
The percent of employees laid off
The date on which the layoffs will occur.
Unforeseeable business circumstances prompted by COVID-19 |
{
"warn_act_notifications": [
{
"layoff_or_closing": "layoff",
"notice_received_date": "2019-03-20",
"employees_impacted": 52,
"total_employees": 100,
"percentage_impacted": 0.52,
"layoff_or_closing_date": "2019-03-19",
"reason": "Unforeseeable business circumstances prompted by COVID-19"
}
]
}
Attributes |
|---|
List of a company's corporate registrations, with full details Child Attributes`business_name`The business name as it appears in the corporate registration
"Domestic", "foreign", or "unknown"
The mailing address of the business address as it appears in the corporate registration
The main address of the business as it appears in the corporate registration
the physical address of the business as it appears in the corporate registration
The physical address of the business as it appears in the corporate registration
The business state of jurisdiction as it appears in the corporate registration |
{
"corporate_registration_details": [
{
"business_name": "ENIGMA TECHNOLOGIES, INC.",
"is_domestic": "foreign",
"mailing_address": "245 5TH AVENUE, 17TH FLOOR, NEW YORK, NEW YORK, 10016, UNITED STATES",
"registered_agent_address": "245 5TH AVENUE, 17TH FLOOR, NEW YORK, NY, 10016",
"registered_business_address": "245 5TH AVENUE, 17TH FLOOR, NEW YORK, NEW YORK, 10016, UNITED STATES",
"site_address": "ENIGMA TECHNOLOGIES, INC., 245 5TH AVENUE, 17TH FLOOR,NEW YORK,NEW YORK,10016",
"state_jurisdiction": "DE"
}
]
}