Merchant Transactions Guide

This guide is designed to answer common questions about Enigma’s merchant transactions data and give a framework for understanding where Enigma’s merchant transactions attributes are strong and where they are not, across both attributes and business segments.

For an overview of merchant transactions attributes, please first read our merchant transactions signals page.

To better understand this guide, readers should understand that the Enigma Business Location refers to transactions attributable to a specific address/location for a business, while an Enigma Business refers to holistic brand-level revenues. A Business incorporates both constituent Location transactions and transactions unresolvable to a location; all Enigma Locations belong to a Business. For an overview of the difference between business vs. business location revenues, please read our data structure page.

Common Questions

How does Enigma maintain its accuracy?

Enigma uses a third party data set from a processor to validate revenue attributed to businesses. By comparing transactions from card issuers against a card processor, Enigma is able to continuously maintain its merchant transaction data accuracy.

What are some reasons for underestimating revenue?

No corporate cards: Enigma does not collect transactions from any corporate cards and does not adjust for them. As a result, Enigma severely under-reports business-to-business revenue.


Recommendation - avoid using merchant transactions revenue for B2B companies; OK to use growth and transaction size

We recommend customers do not use Card Revenues for B2B businesses. However, customers may continue to use average transaction size and growth trends for businesses with a high proportion of B2B transactions.

Under-resolution or under-counting due to uncertain or mixed information about the merchant: Enigma only attributes a transaction description to a merchant if there is >95% precision that the transaction description is tagged correctly.

Enigma opts to under-reports revenue systematically so that Enigma revenue can always be used conservatively. This is by design, as credit risk customers have requested conservative estimates in order to be confident in underwriting loans to businesses.

The below is an example for how transactions with varying levels of information are tagged or not tagged:

Transaction descriptionEnigma entity attributionBusiness types that may contain this kind of transaction description
SHELL 842 5th AVE BROOKLYNBusiness Location ✅: Shell 842 5th Ave
Business ✅: Shell
Independent businesses; smaller chains - this is where Enigma is the strongest
SHELL NYBusiness Location ❌: None

Business ✅: Shell
Large chains, e.g. grocery or restaurant chains, may sometimes pass on only the Business name and not a full address to the card processor. Since there can be many SHELLs in the state of NY, we can tag to the business as a whole but not an individual address.

Alternative example: A business’s online revenue and platform revenue, e.g. food delivery apps, may not list an address in the card transaction description
SHWABusiness Location ❌: None

Business ❌:: None
There is not enough business name information or location information to safely tag to either a location or a business.

This affects certain brands with abbreviated or truncated names, or large chains with custom/atypical transaction descriptions.
PENNZOIL HOUSTON TXBusiness location ❌: None

Business ✅: Pennzoil
Brands with subsidiaries, e.g. Shell with Pennzoil, are more likely to be tagged to the subsidiary.

Other example: Channel sales with very different transaction descriptions operating names that Enigma is unable to link together

The Industry Coverage list at the bottom of the linked page shows where Enigma revenue is generally strong and has high coverage. Note that this general list may interact with the list above to produce some segments for which Enigma card data is less accurate - for example:

  • Fine dining chains (due to high corporate card proportion and large chains)
  • Ecommerce with a high proportion of channel sales (due to sales under very different transaction descriptions


Recommendation - using merchant transactions revenue as a floor:

Because Enigma is conservative in its estimate, many choose to use Enigma’s revenue as a floor for a business or business location’s card revenues. Furthermore, other attributes like growth and average transaction size generally hold true even if not every transaction is tagged.

What are some reasons for over-estimating revenue?

While revenue under-estimation is by design, revenue over-estimation or over-resolution are known issues that Enigma tries to tackle on a case-by-case basis. Unlike revenue under-estimates, which affects many businesses by a small amount, over-estimates affect a few businesses (~1-3% of the total asset) to a larger degree.

Some common reasons for over-estimated revenue are below:

Multi-tenancy and platforms: We believe ~1-3% of Businesses and Locations contain over-resolution problems because of several different locations that share a very common name and address. This is most common in multi-tenant buildings that also contain large chains of businesses, as well as certain platform channels. In the example below, it is likely that all transactions are tagged to a parent mall vs. the constituent stores:

Transaction descriptionEnigma Entity Attribution
MALL OF AMERICA GYMBOREE 123 MAIN STBusiness Location: Mall of America
Business: Mall of America
MALL OF AMERICA OLD NAVY 123 MAIN STBusiness Location: Mall of America
Business: Mall of America


Recommendation: Use outlier thresholds for different revenue segments

Some businesses will return much larger revenue than expected. Depending on your portfolio, you may set thresholds for revenue outlier thresholds that discard or ignore returned revenue if it exceeds those thresholds. For reference, the 5th/95th percentile for card revenue for every 4-digit NAICS code is here.

Incorrect website inputs: Occasionally, customers will include in their input file a website input that does not actually correspond to the business, or a larger platform (e.g. Enigma has removed the ability to match to the most popular platforms or services, but some may still remain.

Enigma WILL successfully match on a specific page name within a larger platform as illustrated in the example below.

Customer input nameCustomer input addressCustomer input website
Mike’s Coffee123 Main St Brooklyn, NY 11201❌ (incorrect website)
Mike’s Coffee123 Main St Brooklyn, NY 11201❌ (incorrect website, will fail to match)
Mike’s Coffee123 Main St Brooklyn, NY 11201✅ (valid platform page website)


Recommendation - ensure your website inputs are correct

Ensure your website inputs are correct. We also recommend having a Enigma Solutions Engineer enrich your file to catch mistakes and check for any errors that you may not catch by contacting [email protected].

Holistic vs single processor revenue: If you have ground truth card data on your side, i.e. you are a card processor, you may see that Enigma’s revenue may be greater than what you see on your side. Because Enigma’s data comes from the card swipe, it sees holistic revenue across many different processors, whereas you may only see revenue from your own processing.


Recommendation - use Enigma's merchant transactions revenue as a floor

If you are a card processor, by design, some businesses should see greater Enigma revenue than what you may see. You may use Enigma as a floor estimate. For instance, if you are using Enigma revenue to size lines of credit or merchant cash advances, if Enigma is greater than what you see, you may rely on Enigma’s card revenue.