Improving sale performance prediction using support vector machines

Research highlights? A system capable of predicting salesmen performance with acceptable accuracy is developed. ? Only three features which measures agreeableness, openness to experience and sociability are required to obtain accurate results. ? A salesmen performance prediction system reduces considerable the company costs. In this article, an expert system based on support vector machines is developed to predict the sale performance of some insurance company candidates. The system predicts the performance of these candidates based on some scores, which are measurements of cognitive characteristics, personality, selling skills and biodata. An experiment is conducted to compare the accuracy of the proposed system with respect to previously reported systems which use discriminant functions or decision trees. Results show that the proposed system is able to improve the accuracy of a baseline linear discriminant based system by more than 10% and that also exceeds the state of the art systems by almost 5%. The proposed approach can help to reduce considerably the direct and indirect expenses of the companies.

• Publication year

  2011

• Venue

  Expert systems with applications

• Publication date

  2011-05-01

• Fields of study

  Business, Computer Science

• Identifiers
  DOI 10.1016/j.eswa.2010.10.003
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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