Systems and methods are disclosed to implement an item metric prediction system that predicts a metric for an item using a feature-based model built using other similar items. In embodiments, the system is used to predict item influence values (IIVs) of items indicating an expected amount of subsequent transactions that is caused by an initial transaction of the items. In embodiments, a sample of item transaction data is distributed to a plurality of task nodes, which execute in parallel to determine the items' observed IIVs from the transaction data. Subsequently, a new IIV is determined for an item whose observed IIV has a low confidence level. A set of similar items is selected, and a set of parameters of a feature-based model are tuned to fit the model to the observed IIVs of the similar items. A new IIV having a high confidence level is then obtained using the model.