The researchers extracted six variables to represent first-time customers’ acquisition behavior, including whether the purchase was made online or offline, number of items purchased, prices, discounts, whether the purchase was made during a holiday period, and whether the customer purchased a newly released product. With only those six variables, the authors show how the algorithm can better identify future heavy spenders and those who will be most responsive to future email promotions after just one transaction.
In particular, they found that people who bought more products at the first transaction, especially those who did so in stores, were more likely to be repeat buyers in the future. Likewise, the algorithm tagged people who bought newly released products as potential high-value customers who would keep coming back.
On the other hand, those who bought discounted products, especially those who did so on Black Friday or during other holiday periods, were “lower-value,” often one-time customers.
