Systems and methods for predicting lost demand using machine learning architectures

A system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable storage devices storing computing instructions configured to run on the one or more processors and perform:
• providing, via an electronic platform, access to one or more order placement user interfaces;
• collecting order placement information associated with the one or more order placement user interfaces, the order placement information at least indicating (a) actual availability of order placement options during client sessions involving the one or more order placement user interfaces and (b) whether or not the client sessions were converted to actual orders;
• analyzing, by a conversion determination network of a machine learning architecture, the order placement information;
• generating, using the conversion determination network of the machine learning architecture, actual conversion information for the client sessions based on the actual availability of the order placement options during the client sessions;
• generating, using the conversion determination network of the machine learning architecture, predicted conversion information for the client sessions based on a full availability of all of the order placement options during the client sessions;
• and
• generating lost demand information based, at least in part, on the actual conversion information and the predicted conversion information.