Abstract: Systems and methods for providing warehousing services that utilize a machine learning model are provided. The system trains a machine learning model with training data comprising item attributes and transaction locations extracted from past transactions for each item category to identify a plurality of transaction zones where each item category has a highest probability for selling. Subsequently, the system receives a warehouse request to warehouse inventory in a remote location. At least one transaction zone is determined based on item attributes of the inventory by applying the trained machine learning model. Based on the determined at least one transaction zone, the system determines one or more warehouse spaces that satisfy a spacing requirement for the inventory and causes presentation of the warehouse recommendation. The warehouse recommendation can indicate the one or more warehouse spaces.

Abstract: In some embodiments, a multi-functional messaging system comprises a data collector to collect or receive product or temporal data over a network, associate the product or temporal data with a particular product, and store the product or temporal data and an association between the product or temporal data and the particular product in a database. The system also comprises a multi-channel messaging engine to generate a message for a targeted recipient based at least on one aspect of the product or temporal data stored in the database, and select a channel from a set of channels for transmission of the message to the targeted recipient based in part on a characteristic of the selected channel.