A machine-learning algorithm is trained with features relevant to a visual/video analysis performed on subjects conducting transaction at transaction terminals. The algorithm is also trained on weather data known at the time of the transactions and on selective details of the transactions. The algorithm produces as output predictions relevant to: whether a given subject for a current transaction is likely to enter a store, likely items that the given subject might purchase if the subject were to enter the store and likely amount of money that the subject would spend in the store, an effectiveness of providing an incentive for the subject to enter the store, and what type of incentive would most likely entice the subject to enter the store.
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