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Point of sale data


Point-of-sale (POS) systems are most often associated with transactions generated at a retail outlet. However, many of these systems are starting to be deployed in temporary locations, such as a community fair or a high school event. The typical POS system incorporates a cash register based on a PC or embedded system, monitor, receipt printer, display, barcode scanner, and debit/credit card reader. Historically, POS systems were either not connected or managed on a dedicated private network. Thanks to the rise of the Internet of Things (IoT), these systems are being connected directly to cloud platforms that make remotely administering these devices from a central location much simpler. There’s no longer a need to dispatch IT personnel to manually update each system. This is critical because a POS failure can result in longer lines that inconvenience customers and potentially lead to lost revenue. A negative customer experience can easily translate to customers opting to shop somewhere else in a retail industry that is intensely competitive. 

Machine data generated by POS systems provides organizations with real-time insight into everything from what’s sold, how it’s paid for, as well as the pace at which it’s being sold. Organizations can use this data to monitor revenue in real time, which can feed into how to better market 1:1 against customers, track product placement and sales in a store, or detect potentially fraudulent transactions in real time. POS data also delivers visibility into the customer experience, such as which coupons are most popular or the combinations of products that are selling together. 

Before looking at documentation for specific data sources, review the Splunk Docs information on general data ingestion: 

Use cases for Splunk Observability Cloud