Preprint Concept Paper Version 1 Preserved in Portico This version is not peer-reviewed

Customer Churn - Prevention Model – Prediction Model

Version 1 : Received: 2 June 2021 / Approved: 3 June 2021 / Online: 3 June 2021 (12:48:22 CEST)

How to cite: Grijalba Facundo, J. E. Customer Churn - Prevention Model – Prediction Model. Preprints 2021, 2021060113. Grijalba Facundo, J. E. Customer Churn - Prevention Model – Prediction Model. Preprints 2021, 2021060113.


The strategy of any organization is based on the growth of its customer base, and one of 5 its principles is that selling a product to an existing customer is much more profitable than acquiring 6 a new customer. However, this approach has several opportunities for improvement, since it usu- 7 ally has a totally reactive approach, which does not give opportunity to the areas specialized in 8 customer experience and recovery, to give an effective response for that moment, since the customer 9 is gone at the time of the intervention. This happens because usually a diagnostic analysis of cus- 10 tomers who have stopped buying products or services in a defined period, commonly three (3) pe- 11 riods or months, is performed. This paper challenges the way to face this problem, and proposes 12 the development of a complete solution, which does not focus exclusively on the prediction of 13 churn, as is usually done in the state of the art research, but to intervene in different interactions 14 that can be carried out with customers. The above focused not only to prevent customer churn, but 15 to generate an added value of continuous improvement in sales processes, increase customer pene- 16 tration, leading to an improvement in customer experience and consequently, an increase in cus- 17 tomer loyalty.


Churn 1; customer churn; customer segmentation; churn prevention; predictive churn 20 model; recommendation system engine.


Computer Science and Mathematics, Algebra and Number Theory

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