Operating Location
A specific place where business is conducted under a brand. An operating location most often corresponds to a physical address, but a phone number is considered sufficient when no address can be identified. Operating location names may be distinct from the brand name to indicate something unique about that location (such as a franchise identifier or neighborhood qualifier).
GraphQL type: OperatingLocation
A Starbucks store at 123 Main St is an operating location. It has an address, phone number, operating status, and its own card transaction metrics.
Other Attributes
Additional attributes available on this Operating Location that are not part of the standard attribute groups.
Is Marketable (Operating Location)
Description
Contains a boolean value indicating whether the operating location is marketable.
Data Sources
An operating location is considered marketable if it meets certain criteria, like whether it has an open status with recent data, revenue in the last 12 months, or reviews in the last 12 months.
Pricing tier: Core
| Field | Name | Type | Description |
|---|---|---|---|
| Is Marketable | is_marketable | boolean | This field contains a boolean value indicating whether the operating location is marketable. |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Operating Location Location Type
Description
The location type of the operating location. Possible values include: professional service, retail, civic organization, hospitality, realestate, public venue, headquarters, office, trade service, business service, scientific, educational, supplier, government, residential, manufactoring, religious, agriculture, and medical. For example, a Target location where a customer can shop would have location_type of "retail", whereas a Target location where a Target employee would work would have location_type of "office".
Pricing tier: Core
| Field | Name | Type | Description |
|---|---|---|---|
| Location Type | location_type | string | The type of operating location (e.g. retail, office, etc.) |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Name
Description
The name of the operating location.
An operating location is a place where business is conducted under a brand. Most often is at a specific address. If an address cannot be identified, a phone number is considered sufficient.
An operating locations often have names that are distinct from the brand name. Operating location names may indicate something distinct about that location.
As an example, the operating location name "Target - Crossgates Mall" indicates both the brand "Target" and the location name "Crossgates Mall".
Pricing tier: Core
| Field | Name | Type | Description |
|---|---|---|---|
| Name | standardized_name | The name of the operating location. | |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Operating Status
Description
Indicates whether a location is actively functioning ("Open"), out of operation ("Temporarily Closed", "Closed"), or of uncertain status ("Unknown").
Time Series
We maintain the operating status as a time series. Each entry in the time series represents an unbroken period of time where we observed the same operating status. The rank property indicates the order of the time series and first_observed_date and last_observed_date indicate the beginning and end of the period.
- Rank = 0: Reflects Enigma's most recent, validated status observation.
- Higher ranks (1, 2, etc.): Represent older, previously recorded statuses, preserved for reference and limited historical tracking.
This structure lets you understand
- how the operating status has changed over time (e.g. temporary closures or seasonality)
- a lower bound for how long the business has been operating
- when a specific location has closed (this can be particularly helpful for evaluating openings and closings in businesses with multiple locations)
Data Sources
The operating status data is derived from:
- Publicly available business data and listings (Enigma observes the operating status at least every three months, however, in many cases we are taking more frequent observations)
- Privately verified business information
Operating Status Values
- Open: Verified as open and functional through credible evidence or manual validation.
- Temporarily Closed: Trusted data indicates the business has temporarily ceased operations, or the business is manually verified as temporarily closed.
- Closed: Trusted data indicates the business has ceased operations, or the business is manually verified as closed.
- Unknown: There is incomplete or insufficient information available to label the location as either Open or Closed.
Pricing tier: Core
| Field | Name | Type | Description |
|---|---|---|---|
| Operating Status | operating_status | string | Indicates whether a location is Open, Temporarily Closed, Closed, or its status is Unknown. |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Rank
Description
Indicates how the card revenue of this operating location compares to other operating locations of the same enigma industry within the geographical area.
For example, if Joe's Pizza has a position of 5 and cohort size of 17, this means, of all the pizza restaurants near Joe's Pizza, four locations have higher card revenue and twelve locations have lower card revenue.
The geographic area is defined as the H3 index (resolution 4) of the address of the operating location.
There are a few reasons why an operating location does not have an operating location rank
- we're unable to determine the card revenue for the operating location
- fewer than ten operating locations with card revenue exist nearby within the same industry (too few businesses to form a cohort)
Pricing tier: Plus
| Field | Name | Type | Description |
|---|---|---|---|
| Quantity Type | quantity_type | string | The quantity we're using to determine the ranking within a cohort. At present, ranks will always be based on card_revenue. |
| Period | period | string | The period we're using to determine the ranking within a cohort. At present, ranks will always be based on the most recent 12m for which revenue is available. |
| Position | position | integer | The absolute position of the operating location relative to its cohort. |
| Cohort Size | cohort_size | integer | The number of operating locations in the cohort. For our Joe's Pizza example (5 of 17), the cohort size is 17. |
| Period Start Date | period_start_date | date | The date on which the period begins. So if period_start_date is 2024-01-15 and period is 12m, this means the 12m period we're using to rank the operating location began on Jan 15, 2024. |
| Period End Date | period_end_date | date | The date on which the period ends. So if period_end_date is 2025-01-15 and period is 12m, this means the 12m period we're using to rank the operating location ends on Jan 15, 2025. |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Operating Location Revenue Quality
Description
Warnings and issues related to the revenue of this operating location.
Pricing tier: Plus
| Field | Name | Type | Description |
|---|---|---|---|
| Issue Reason | issue_reason | string | The reason for the revenue quality issue. The reasons signify the following: - OVER_100X_REVENUE_AND_20M_ANNUAL_REVENUE_EXTRAPOLATION (HIGH severity): 100x and $20M annual revenue extrapolated by our models from raw revenue sources. - OVER_100X_REVENUE_EXTRAPOLATION (HIGH severity): 100x revenue extrapolated by our models from raw revenue sources. - OVER_20M_ANNUAL_REVENUE_EXTRAPOLATION (HIGH severity): $20M annual revenue extrapolated by our models from raw revenue sources. - REVENUE_DECREASE_TO_0_PCT_LOCATION_OPEN (HIGH severity): Revenue drops to zero and location status is currently open. - REVENUE_DECREASE_TO_20_PCT_LOCATION_OPEN (HIGH severity): Revenue drop to 20% of the median revenue over the past 12 months and location status is currently open. - CLOSED_BUT_STILL_HAVE_POSITIVE_REVENUE (HIGH severity): Operating location is identified as Closed or Temporarily Closed for over 2 months but still has positive revenue. - 12M_REVENUE_LOWER_THAN_5K (HIGH severity): 12m revenue <$5K for operating location that is card-accepting, mostly offline, not newly open. - REVENUE_INCREASE_TO_250_PCT_IN_LAST_18M (HIGH severity): Revenue increase to 250% of the median revenue for 3 months in the past 18 months. - REVENUE_INCREASE_TO_250_PCT_ALL_TIME (HIGH severity): Revenue increase to 250% of the median revenue for 3 months at any point in its revenue history. - GREATER_THAN_10X_INTERQUARTILE_RANGE_ABOVE_Q3_WITHIN_BRAND (HIGH severity): Operating location revenue in the last 12 months is 10x IQR over p75 of operating locations within brand. - GREATER_THAN_5X_INTERQUARTILE_RANGE_ABOVE_Q3_WITHIN_BRAND (MEDIUM severity): Operating location revenue in the last 12 months is 5x IQR over p75 of operating locations within brand. - OVERLY_HIGH_PCT_OF_BRAND_REV (MEDIUM severity): Operating location contributes very high portion of revenue for the brand. - >10% brand revenue for brands with >= 100 open operating locations - >30% brand revenue for brands with >= 10 open operating locations - >50% brand revenue for brands with >= 4 open operating locations - REVENUE_DECREASE_TO_0_PCT_LOCATION_UNKNOWN (MEDIUM severity): Revenue drop to zero and location status is currently unknown. - REVENUE_DECREASE_TO_20_PCT_LOCATION_UNKNOWN (MEDIUM severity): Revenue drop to 20% of the median revenue over the past 12 months and location status is currently unknown. - EXCEED_P99_WITHIN_4_DIGIT_NAICS (MEDIUM severity): Operating location revenue is greater than 99th percentile revenue within its 4-digit naics code in last 12m. |
| Issue Severity | issue_severity | string | The severity of the revenue quality issue. |
| Issue Description | issue_description | string | A description of the revenue quality issue. |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Seasonality Index (Operating Location)
Description
The Seasonality Index identifies operating locations with recurring seasonal revenue patterns, measuring both the overall concentration of revenue across months and the specific month in which revenue consistently peaks.
It answers two questions for every eligible operating location:
- Is the business seasonal at all? →
gini_scoremeasures how concentrated revenue is across months. - If so, when is the peak? →
recurring_peak_monthidentifies the calendar month where revenue is most concentrated.
For example, a ski resort will show high revenue concentration in winter months (high gini_score) with recurring_peak_month = December. A tax preparation office will show concentration in early spring with recurring_peak_month = April. The index captures the pattern itself, but the underlying cause can vary: weather (ice cream shop), regulatory deadlines (tax preparer), academic calendars (school supply store), holidays (Christmas tree farm), or other factors.
Layer 1 — Overall revenue concentration (gini_score)
The Gini score measures how concentrated card revenue is across months. It ranges from 0 (revenue perfectly flat) to 1 (all revenue in a single month). A score of 0.4 or above indicates meaningful seasonal concentration and is the recommended threshold for identifying seasonal businesses.
Interpretation guide:
- < 0.4: Revenue roughly flat year-round — not considered seasonal (e.g. restaurant, gas station)
- 0.4–0.6: Moderate seasonality — clear peak but revenue spread across several months (e.g. ice cream shop, garden center)
- 0.6–0.8: Strong seasonality — most revenue concentrated in a short window (e.g. tax preparation, farm)
- > 0.8: Extreme concentration — nearly all revenue in 1–2 months (e.g. Halloween costume store, Christmas tree farm)
Layer 2 — Recurring peak month (recurring_peak_month, peak_month_revenue_share)
Identifies the recurring peak month where revenue is most concentrated. The peak month must be consistent across all observed periods, not just a single year.
Data Sources
Derived from historical card transaction revenue over a rolling 36-month observation window. Eligibility criteria are applied to ensure the seasonal signal is based on sufficient history and transaction volume to produce a reliable result. An operating location is eligible if:
- It has at least $10,000 in card revenue in each 12-month period in the observation window.
- It has at least ~4 years of revenue history to calculate a reliable seasonal pattern.
Seasonality is measured directly from each business's own revenue history rather than inferred from industry or geography. Not all tax preparers are seasonal, and not all ice cream shops are. A Miami ice cream shop may have flat revenue year-round while a Minnesota one peaks sharply in summer. This individual-level approach lets the data speak for each business rather than relying on categorical assumptions.
Pricing tier: Premium
| Field | Name | Type | Description |
|---|---|---|---|
| Gini Score | gini_score | double | A score from 0 to 1 measuring how concentrated a business's card revenue is across months. Computed as the Gini coefficient of monthly revenue shares within each 12-month period, then taking the minimum across the three periods as a conservative floor. A higher score indicates greater revenue concentration across fewer months. Scores of 0.4 and above indicate meaningful seasonality. |
| Recurring Peak Month | recurring_peak_month | string | The month (e.g. "July") where card revenue is most concentrated across observed periods. Only populated when the peak month accounts for at least 20% of annual revenue in every observed period. NULL indicates no consistent seasonal peak was detected. Note: only the single dominant peak month is surfaced. Businesses with multiple seasonal peaks will show only the month with the highest recurring revenue share. As 65% of seasonal businesses at the recommended threshold have a single peak, this captures the majority of cases. |
| Peak Month Revenue Share | peak_month_revenue_share | double | The revenue share of the peak calendar month, expressed as a value between 0 and 1. For example, a value of 0.20 means the peak month accounts for at least 20% of annual revenue in every observed period. When this value reaches 0.20, recurring_peak_month is populated. As a reference point, a perfectly flat non-seasonal business would show ~0.08 (1/12 ≈ 8%) for every month, so the 0.20 threshold means the peak month contributes at least 2.5x what a flat business would show. |
| ID | id | long | |
| First Observed Date | first_observed_date | string | |
| Last Observed Date | last_observed_date | string |
Operating Location Data
Attributes and metrics directly available on an Operating Location entity.
Industry
CoreThe industry within which the business operates.
Technologies Used
PremiumIndicates third-party technologies being used at a particular operating location.
Card Transactions
PlusContains quantitative information about the card transactions processed by the operating location.
Legal Entity
PremiumBusinesses which have become legal entities by registering with a U.S. Secretary of State (SoS).
Brand - Card Transactions
PlusContains quantitative information about the card transactions processed by the brand.
Also available: ID (.id), Name (.name), Operating Status (.operatingStatus, .lastObservedDate).
Connected Data
Data accessed through Operating Location's relationships to other entities. These fields are available when querying an Operating Location but live on connected entities.
Address
A physical street address for the business, standardized to USPS conventions.
Reviews
A time-series summary of publicly available customer reviews for a business location, including review count and average score.
Registrations
A business registration filed with a U.S. Secretary of State, either domestic (creating the entity) or foreign (often a requirement to operate in that state).
Registrations - People
A natural person associated with a business as an owner, officer, or contact.
Contacts
A natural person associated with a business as an owner, officer, or contact.
Brand
The customer-facing identity of a business, representing the name and presence under which it engages with customers.
Also available: Website (via website), Phone (via phone number).
Relationships
Operating Location connects to other entities in the Enigma graph:
| Direction | Relationship | Target Entity |
|---|---|---|
| ← | operates at | Brand |
| ← | owns location | Legal Entity |
| → | can be called at | Phone Number |
| → | is subject of | Review Summary |
| → | operates at | Address |
| → | operates website | Website |
| ← | is performed at | Role |