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B2B Sales Leads Generation Using Commercial Payments Data: A Novel Application of Recommender Systems

Author(s): Vibhu Goenka, Amit Udata

Abstract

In this paper, we describe a novel case study on the application of recommender systems to generate sales leads for merchants in a B2B environment. A user based collaborative filtering algorithm is used on corporate payments data to generate new client recommendations for the merchants based on the existing clients of similar merchants. Client recommendations or prospects, if generated accurately, can have huge business potential for the merchants by aiding them in expanding their business. Hence the paper describes an application of recommender systems which has significant business impact and value. Despite finding lots of use cases in the B2C environment, recommender systems have till date very limited applications in the B2B arena. By providing a concrete step-by-step account of how to apply this powerful machine learning technique, our paper aims to firstly, bring to light, the significant business impact the use of recommender systems may have in B2B space and secondly, serve as evidence to be referred to for further applications.

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