Determination of Customer Satisfaction using Improved K -means algorithm
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METHODOLOGIES AND APPLICATION
Determination of Customer Satisfaction using Improved K-means algorithm Hamed Zare1 • Sima Emadi1
Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Effective management of customer’s knowledge leads to efficient Customer Relationship Management (CRM). To accurately predict customer’s behaviour, clustering, especially K-means, is one of the most important data mining techniques used in customer relationship management marketing, with which it is possible to identify customers’ behavioural patterns and, subsequently, to align marketing strategies with customer preferences so as to maintain the customers. However, it has been observed in various studies on K-means clustering that customers with different behavioural indicators in clustering may seem to be the same, implying that customer behavioural indicators do not play any significant role in customer clustering. Therefore, if the level of customer participation depends on behavioural parameters such as their satisfaction, it can have a negative effect on the K-means clusters and has no acceptable result. In this paper, customer behavioural features—malicious feature—is considered in customer clustering, as well as a method for finding the optimal number of clusters and the initial values of cluster centres to obtain more accurate results. Finally, according to the organizations’ need to extract knowledge from customers’ views through ranking customers based on factors affecting customer value, a method is proposed for modelling their behaviour and extracting knowledge for customer relationship management. The results of the evaluation of the customers of Hamkaran System’s Company show that the improved Kmeans method proposed in this paper outperforms K-means in terms of speed and accuracy. Keywords Customer relationship management K-means Customer life cycle value Data mining Customer satisfaction
1 Introduction The interaction between organizations and customers has significantly changed so that there are no long-term guarantees of business continuity with customers. However, organizations need to properly identify their customers, anticipate their needs and expectations, and increase their productivity ¨ ztu¨rk 2016; Lauusing this type of information (Erdil and O don and Laudon 2015; Shatnawi et al. 2017). A simple example of Customer Relationship Management (CRM) is customers’ information for an organization, where
Communicated by V. Loia. & Sima Emadi [email protected] Hamed Zare [email protected] 1
Department of Computer Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran
management and sales staff or organization services can adapt their customers’ needs to their products, remind them of their service needs, or perform the right-time management. In this regard, marketing department in each company should work with an organized effort to collect and organize customer information. This information is valuable to sailing unit to contac
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