OHASHI, Fabio Kazuo et al. Recommender System Architecture to support salesperson using Sales Force Automation Systems In large product portfolio companies. []. , 42, pp.46-61.   30--2021. ISSN 1646-9895.  https://doi.org/10.17013/risti.42.46-61.

Wholesale distribution companies usually have a large number of items sold by different manufacturers in their product portfolio. Finding and recommending products to the customer among thousands of possibilities is a challenge for the sales team. In addition, there are also new product releases and promotions that are added to the portfolio frequently. This paper proposes to develop an architecture to implement a Sales Force Automation system supported by Artificial Intelligence that can recommend products online to a sales professional when making a purchase order. To achieve this objective, the following methods and experiments were used: systematic literature review, qualitative and quantitative exploratory research, experiments, case study, proof of concept, and survey with the Delphi method. The proposed architecture was applied by building a proof of concept in an auto parts distribution company in which the system was able to provide recommendations for four different algorithms.1cm.

: Recommender systems; Sales force automation; Knowledge management; Knowledge dissemination.

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