Discovering and Inducing Rules to Categorize Sales Personnel

Abstract: In sales, it is presumed that the behavior of sales personnel differs depending on what part of sales they are in. However, to the best of our knowledge, there are no studies about conducting a segmentation of sales personnel based on behavioral data from Salesforce, the world’s largest Customer Relationship Management platform. Previous research describes how to segment different customers based on their behavioral data, but no one has yet attempted to segment sales personnel. In this thesis, we extracted Salesforce behavioral data about sales staff and clustered them into previously unknown segments. Using a mixture of supervised and unsupervised learning we created six profiles that describe how different sales personnel work in Salesforce. Our findings helped the company Brisk to improve their knowledge about sales personnel.