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Retention Period Prediction for Pension Policies
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2019) Bayır, Ömer; Güney, Evren
Customer Retention in Pension market refers to the activities and actions companies and organizations take to reduce the number of customer defections. How long the customer will be with our company or will stay in the system is retention. There are already workings in my company and other companies in the market about customer retention. Existing works generally contains how to measure customer retention and how to define distribution channels are successful in customer retention. Also existing predictive models are working on the feature set customer fund, total collection, un-paid premium frequency in general. In pension market companies have small margin of profit from pension policies. To make a profit from pension policies the companies have to retain their customer for long years. It ‘s approximately nine year to make profit from a pension policy because of high sales costs. Therefore to gain a new customer is less profitable than retaining present customers in Pension Market. In my project, I want to look retention in the pension application phase of customer. My main purpose is when the customer applied for pension product predict its retention period. If I produce an applicable model, It will be used in my company’s sales channels.
Predicting Customer Satisfaction Via Structed and Unstructured Data Using Classification and Regression
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2019) Danışman, Efehan; Küçükaydın, Hande
According to different studies, retaining existing customers is five or more times more costly than acquiring new ones. This study aim to understand what customers expect from an airline using machine techniques. Dataset is scraped from Skytrax’s Airline Quality website and consists of 65947 observations with 17 columns consisting of one free format column that includes customer review. In order to do predict whether a customer recommends an airline or not, we try to utilize classification and regression algorithms. In addition to insights, this study also aims to compare the performance of the models and viability of using only free text in order to predict customer satisfaction.
Underlying the Bias for Human Music Evaluation
(MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2017) Yıldırım, Burak; Çakar, Tuna
Predictive analysis is the process of using data analytics to predict the future over historical data. Data analytics is the use of statistical modelling and / or machine learning methods to measure the future. In short, it is one of the data mining techniques for predictive analysis that focuses on creating a predictive model for the future by extracting relationships from the data.

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