Sellers Characterization in Direct Selling Systems through Data Mining and Analytics

Abstract

The direct selling industry presents many opportunities for people who wish to obtain income through the generation of their own business, based on a sales network. In this business model, direct sellers have objectives that transcend the sales activities themselves, such as establishing sustainable interpersonal relationships with their clients in the medium and long term and abilities in administration and management. In this work, we study the performance of direct sellers using traditional data in combination with personality traits and personal profiles of sellers through the DISC test. Results are subjected to statistical analysis, using Data Mining techniques and analytics, such as Principal Component Analysis and Clustering. Results validate those desirable traits for a traditional seller in this industry and show how they are combined with traditional data to identify and describe different groups of behaviour. Besides, we approach the guidelines for an optimal process of sales engineering in this industry.