Block, Inc.
Using combined eCommerce and brick-and-mortar data to produce intelligent recommendations for web page editing

Abstract:

Using combined eCommerce and brick-and-mortar data to produce intelligent recommendations for website editing is described. In an example, brick-and-mortar transaction data associated with a first merchant and second merchant(s) can be compared to identify a subset of the second merchant(s) that are similar to the first merchant. Performance metrics associated with eCommerce graphical user interfaces (GUIs) presented on behalf of the subset of the second merchant(s) can be determined based on aggregated transaction data associated with eCommerce point-of-sale (POS) transactions associated with the subset of the second merchant(s) and a recommendation based on content, a layout, and/or a design of at least a portion of the eCommerce GUIs can be generated. The recommendation can be sent to a computing device operable by the first merchant for use in creating or editing an eCommerce GUI to be presented on behalf of the first merchant.