An option to customize the events used by the Frequently Bought Together (FBT) model has been released. Previously, customers reported that the FBT model did not recommend items that they expected to go together, partly because the model considered all conversion events, such as purchases, add-to-cart, and add-to-wishlist, which diluted the accuracy of recommendations. To address this, a new setting has been introduced in the FBT model configuration that allows users to specify which event types should be considered for training. This customization increases the relevancy of FBT recommendations and improves adoption rates. Customers can update their existing FBT configurations or set it up during the initial model setup to ensure the model is trained with the most accurate conversion data. This enhancement is part of a broader initiative to detect sufficient event data availability before training, reducing the likelihood of training failures.