The past marketing campaign targeted part of the customer base. Among other 1,000 clients, how do we identify the 100 that are keener to subscribe? We can build a model that learns from the data and estimates which clients are more similar to the ones that subscribed in the previous campaign. For each client, the model estimates a score that is higher if the client is more likely to subscribe. There are different machine learning models determining the scores and we use two well-performing techniques, as follows:

In the end, we need to choose one out of the two techniques. There are cross-validation methods that allow us to estimate model accuracy (see Chapter 6, Step 3 – Validating the Results). Starting from that, we can measure the accuracy of both the options and pick...