Evaluation of Potential Clients: a Dynamic System for Prospect Rating

Need

A company offering subscription services has encountered limitations in its systems for evaluating potential clients. The traditional method used is based primarily on creditworthiness, without taking into account other important factors that determine the client’s true value. The company needs a system that integrates such variables, such as the payment method and the products offered, in order to optimise acquisition and reduce credit risk.

Solution

At Moxoff we have implemented a Machine Learning system that calculates the expected value of each individual customer, also taking into account key variables such as the expected contract lifetime and the net present value (NPV) in relation to the specific commercial offers. The model associates each customer with numerous possible combinations based on the selected products and adopted payment methods. The results of the analysis are made available in real time to sales agents through a dedicated web platform, enabling them to optimise acquisition decisions more effectively and with greater awareness.

Benefits

  • Greater accuracy in commercial decision-making: targeted analyses that support the sales force comprehensively, including at the geographical level.
  • Reduction of credit risk: more accurate estimation of the customer’s value and expected behaviour over time.
  • Engagement of higher-profitability customers: direct commercial efforts towards prospects with higher expected value.
  • Greater operational efficiency: automated decision-making process that reduces evaluation time and costs.
Innovation starts
with the right question

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Moxoff S.r.l.
Via Felice Casati, 29
20124 Milano

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