This is additional information added to the transaction to denote its importance, such as the profitability of the transaction as a whole or the profitability of the individual products in the transaction. In the case of the preceding binary matrix, a column called weight is added to store the importance of the transaction.

In this chapter, we will show you how to use transaction data to support cross-selling campaigns. We will see how the derived user product preferences, or recommendations from the user's product interactions (transactions/weighted transactions), can fuel successful cross-selling campaigns. We will implement and understand the algorithms that can leverage this data in R. We will work on a superficial use case in which we need to generate recommendations to support a cross-selling campaign for an imaginative retailer.