Best Transaction Datasets, Databases & APIs

What is Transaction Data?

Transaction Data is information about all the recorded and related transactions of a business or a consumer. This information may include orders, purchase history, invoice, payments, and credit card payments and etc. The information included in any transaction data must have a time frame, numerical value and may refer to multiple products purchased. Transaction data is used to target consumers based on their buying patterns and capacity to purchase again. 

How is Transaction Data collected?

Transaction data is collected and gathered from different sources. These sources may include retail store purchases, e-commerce stores, credit card payments, bank statements of account, utility payment and rental payments, orders, banks, invoices, shipping documents, insurance claims, and online surveys. This information must be based on credible sources, and it must be validated and verified. The collected information is compiled and turned into accurate transaction datasets.    
 

What are the typical attributes of Transaction Data?

Transaction Data is a list of a recorded transaction of a business or an individual. Here are some typical attributes of transaction data:

• Consumer Attributes: this refers to the personal information of the consumer like name, address, employment status, geographical location, and preferences.
• Transaction Attributes: this refers to the type of transaction made, how often the purchase is, price of the product or service.
• History attributes: this refers to the capacity of a consumer to buy products, payment history, credit score, mode of payment, and other related information.

What is Transaction Data used for?

Transaction Data is used by marketers and advertisers. Marketers used this data to target consumers based on their previous transaction and their propensity to purchase a product or service. They can also use this data to target location-based marketing strategy. Furthermore, advertisers can use this data to create customized ads based on their preferences and purchase patterns. Lending institutions and banks can also use this data as a reference for the borrower’s capacity to pay based on their transaction data.      

How can a user assess the quality of Transaction Data?

In order to assess the quality of transaction data, users must first identify where the data providers got their sources. The source of information must be credible and reliable. Users should understand how the data providers process their data to acquire their datasets. The data must be genuine and free from error. Another quality is the scope of transaction nformation. Similarly, if users want to assess the quality of data, they can read online reviews.  

Where can I buy Transaction Data?

Data providers and vendors listed on Datarade sell Transaction Data products and samples. Popular Transaction Data products and datasets available on our platform are Alternative Data | US and Canada Foot-Traffic and Transaction Data by SafeGraph, QueXopa ‘s Paper Receipt Data - OCR Product (sku) Level Transactions - France, Spain and Belgium by QueXopa, and QueXopa Debit & Credit Card Transaction Data (Mexico) - Uniquely Refined Transactions Datasets by QueXopa.

How can I get Transaction Data?

You can get Transaction Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Transaction Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Transaction Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to Transaction Data?

Transaction Data is similar to Consumer Review Data, Product Data, Ecommerce Data, Shopper Data, and Brand Data. These data categories are commonly used for Market Share Analysis and Operational Intelligence.

What are the most common use cases for Transaction Data?

The top use cases for Transaction Data are Market Share Analysis, Operational Intelligence, and Transaction Data Enrichment.