Receipt Data: Best Receipt Datasets & Databases
What is Receipt Data?
Receipt data is information that is collected from receipts which are generated whenever a purchase is made. It's used by businesses and retailers to analyze their store performance and track spending habits of their consumers. Datarade helps you find the best receipt datasets.Learn more
Recommended Receipt Data Products
Granular e-receipt transactional data for USA and continental Europe
Invoices, Payslips, & receipts Document dataset | Global Coverage | PDF JPEG format | Datasets updated frequently with high variety of templates
QueXopa 's Paper Receipt Data - OCR Product (sku) Level Transactions - France, Spain and Belgium
Shopper Data | Retail Transaction Data | In-Store Data on Spending Patterns
India Email Receipt Panel Dataset (Direct from Data Originator) *No PII*
EDI Universal Depository Receipts database with over 3300 records
Granular E-receipt Data for Middle East
Photon Commerce - Invoice and receipt extraction, OCR, and reconciliation
Data Collection by Shaip: Text, Audio, Image, Video for AI & ML Training
QueXopa Email Receipt Data (Brazil, UK, Spain, France & Germany) - SKU/Product Level Data on Brazil's Top E-Commerce Companies
More Receipt Data Products
The Ultimate Guide to Receipt Data 2023
What is Receipt Data?
Receipt data is information collected from receipts which are generated when consumers make purchases both in-store and online. These receipts contain a huge amount of information about people’s shopping habits as well as retailers information and also serve as proof of purchase which can be useful as a store performance indicator. Companies and businesses use this information to track the spending habits of their customers and to evaluate the performance of their store in regards to their competitors.
How is Receipt Data collected?
Receipt data is collected whenever a sale is made as this process automatically causes the creation of a purchase receipt. While a receipt may seem simple at first, the amount of information it contains is huge. It can tell you about when the purchase was made, what was bought and the price of the products as well as where it was bought (online or in-store, and if it was in-store, where the store itself was). This data can then be analyzed to provide useful sales insights that tell you about both the performance of the store itself and the spending habits of its consumers. If purchases are made online or using a loyalty card scheme, these can then be attributed to specific customers to provide detailed information about their purchasing habits and whether they have a sense of customer loyalty or not.
What are the attributes of Receipt Data?
A basic receipt itself will give you simple information, like that mentioned above. It can contain details about the purchase, the product price and the location as well as if discount codes were applied. However, what is key is that this data can then be analysed to generate detailed insights.
Receipt datasets can tell you the receipt count by store, where a real store or online one as well as share of basket information, which tells you the other products your consumers are buying outside of your brand on the same shopping trip. It can also give you receipt count by day, geography or highlight which retailers have the most brand programme engagement. Finally, it can also give you a full basket analysis of each consumer’s shopping trip to highlight what products they are buying, as well as the regularity of their purchases and whether they return to the same stores or tend to look elsewhere after an initial purchase.
What is Receipt Data used for?
Retailers and consumers use receipt data for the analytics it provides on their store performance. They can use this information to track sales and, crucially, in comparison to their competitions to evaluate how their business is performing in the market. They also use this data to track the spending habits of their customers and tailor marketing campaigns accordingly in order to generate high profit margins and optimize the workings of their business.
How can a user assess the quality of Receipt Data?
A high quality receipt dataset will provide comprehensive information and analytics about purchase data that is recorded by receipts. It is important to have information that is comprehensive and up to date with the latest analytics to ensure that you can judge your business’ performance with the latest details.
Historical receipt data is equally important in a high quality dataset because it can show how purchase trends and consumer spending habits have developed over time. This information is crucial to analyzing store performance over an extended period of time and for highlighting areas that could be made more effective in order to maximize profit production.
Where can I buy Receipt Data?
Data providers and vendors listed on Datarade sell Receipt Data products and samples. Popular Receipt Data products and datasets available on our platform are Granular e-receipt transactional data for USA and continental Europe by Measurable AI, Invoices, Payslips, & receipts Document dataset | Global Coverage | PDF JPEG format | Datasets updated frequently with high variety of templates by TagX, and QueXopa ‘s Paper Receipt Data - OCR Product (sku) Level Transactions - France, Spain and Belgium by QueXopa.
How can I get Receipt Data?
You can get Receipt Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Receipt 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 Receipt Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Receipt Data?
Receipt Data is similar to Consumer Review Data, Product Data, Ecommerce Data, Shopper Data, and Brand Data. These data categories are commonly used for Operational Intelligence.
What are the most common use cases for Receipt Data?
The top use cases for Receipt Data are Operational Intelligence.