DECISION MAKING WITH TOPSIS AND K-MEDOIDS: AN APPLICATION ON CUSTOMER RECOVERY WITH R PROGRAMMING LANGUAGE

Abstract

Large companies prefer the most profitable customers when they try to recover their old customers who left the company and acquired by the competitors. This choice requires many variables to be evaluated simultaneously under the constraints of cost and time. TOPSIS method is a decision- making technique for multi-criteria problems and is used in a wide range of applications such as: supplier and facility location selection, production systems, enterprise resource planning and marketing, management, health, safety and environmental management problems etc. In this study, data of 1145 customers such as usage of voice, data service and other value added services usage are analyzed by TOPSIS method. The customers analyzed in this study are churned by a competitor of a telecommunication company. In order to determine the most valuable customers to company’s profit,TOPSIS scores are clustered into four segments by k-medoids clustering algorithm. As a result of the analysis, customers are segmented into four groups and totally 37 customers which were placed in the third segment identified as golden customers, thus the company should start churn activities with the customers placing in this segment

Keywords

• TOPSIS,K-Medoids Algorithm,Customer Recovery

TOPSIS VE K-MEDOIDS YÖNTEMLERİYLE KARAR VERME: R PROGRAMLAMA DİLİ İLE MÜŞTERİ GERİ KAZANMA UYGULAMASI

Abstract

Büyük işletmeler, kendisinden ayrılan ve rakip işletmelere geçen eski müşterilerine yönelik gerikazanma faaliyetleri düzenleyeceği zaman, kârlılığa en çok katkı yapan müşterileri tercih etmektedir. Bu seçim, çoğu zaman maliyet ve zaman kısıtları altında birçok değişkenin aynı anda değerlendirilmesini gerektirmektedir. TOPSIS yöntemi, çok kriterli problemler için oluşturulmuş bir karar verme tekniği olup, tedarikçi ve kuruluş yeri seçimi, üretim sistemleri, pazarlama yönetimi, sağlık,güvenlik ve çevre yönetimi gibi geniş bir uygulama alanında kullanılmaktadır. Bu çalışmada, bir telekomünikasyon işletmesinin rakip firmalara geçen 1145 müşterisine ait ses, veri ve katma değerliservilerle alakalı kullanım bilgileri TOPSIS yöntemi ile analiz edilmiştir. Elde edilen TOPSIS skorları işletme kârlılığına katkı sağlayan en değerli müşterileri tespit etmek amacıyla, k-medoids (k-ortaylar)kümeleme algoritması kullanılarak dört segmente ayrılmıştır. Çalışma sonucunda, dört segmenteayrılan müşterilerden üçüncü segmentte yer alan toplam 37 müşteri altın müşteri olarak tespit edilmiş ve geri kazanma faaliyetlerine bu müşterilerden başlanması gerektiği ortaya çıkmıştır.

Keywords

• TOPSIS,K-Medoids Algoritması,Müşteri Kaybı

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