RECOMMENDATION TECHNIQUES FOR TARGET EXECUTION

Multi-modal techniques are described for identifying a recommendation corresponding to a system-defined target strategy. A machine-learning model configured to generate output data from input data may be trained or otherwise obtained. The machine-learning model being trained using an unsupervised machine-learning algorithm and a data set comprising a recurrent data instance, a historical user data instance, and a catalog data instance, to generate output data comprising one or more classification labels for the one or more data instances. Using those classification labels and underlying data, a recommendation for implementing a system-defined target strategy can be identified and presented at a user interface. Upon receiving user approval, a number of corresponding operations may be executed to implement the system-defined target strategy.