scholarly journals CLASSIFICATION AND PREDICTION IN CUSTOMER RELATIONSHIP MANAGEMENT USING BACK PROPAGATION

2014 ◽  
pp. 173-178
Author(s):  
LEELA RANI KOMMA REDDY ◽  
G LOSHMA
Keyword(s):  
Neural Network ◽  
Business Process ◽  
Customer Relationship Management ◽  
Insurance Industry ◽  
Back Propagation ◽  
Relationship Management ◽  
Back Propagation Neural Network ◽  
Customer Relationship ◽  
Business Organization ◽  
Customer Classification

Customer Relationship Management provides a customer classification and prediction which is used for the optimization of business process. The classification and prediction which is used for the optimization of business process. This classification and prediction in CRM will help the company to study, analyze and forecast customers pattern of consumption, business transaction and purchasing CRM has become major activity in the enterprise based business organization using the CRM. CRM is an important activity in the enterprise business organization like banking industry, insurance industry, retail industry and manufacture industry. In the system we are using data mining techniques to implement customer classification in CRM as we need to analyze mass volume of data we are implementing an efficient and effective Neural Network based technique. Based on the existing system like Naïve Bayesian System, our proposed system implements Back propagation Neural Network techniques which would generate accurate results with less time complexity.

scholarly journals Penerapan Enterprise Resource Planning (ERP) dan Pengelolaan Hubungan dengan Pelanggan untuk Sistem Informasi Penjualan pada Toko SOVIAH

2016 ◽  
Vol 2 (2) ◽  
pp. 85-96
Author(s):  
Dhani Adiatma Rimen ◽  
Ricky Akbar
Keyword(s):  
Business Process ◽  
Customer Relationship Management ◽  
Enterprise Resource Planning ◽  
Process Model ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Use Case ◽  
Business Process Model ◽  
Use Case Diagram

Saat ini proses bisnis pembelian, persediaan, dan penjualan barang yang berjalan di Toko Soviah  masih dilakukan secara manual serta belum adanya data pelanggan tetap ditoko tersebut. Hal ini menyebabkan beberapa permasalahan antara lain, sering terjadi kesalahan pencatatan pembelian dan penjualan barang, perhitungan transaksi yang lama, lambatnya informasi ketersediaan barang di gudang serta belum adanya upaya untuk meraih loyalitas pelanggan dalam bisnis yang dijalankan. Oleh karena itu, perlu penerapan Enterprise Resource Planning (ERP) dan Customer Relationship Management (CRM) untuk sistem informasi pembelian, persediaan, dan penjualan barang serta pengelolaan hubungan dengan pelanggan yang bertujuan untuk mengatasi permasalahan tersebut. Tahapan penerapan ERP ini dimulai dengan studi pendahuluan. Aktivitasnya yaitu pengenalan perusahaan dengan wawancara dan observasi, mengidentifikasi proses bisnis pembelian, persediaan, dan penjualan barang yang sedang berjalan kemudian membuatkan usulan sistem secara terkomputerisasinya, yang digambarkan dengan menggunakan Business Process Model Notation (BPMN), serta penggambaran model kerja sistem yang akan diterapkan menggunakan use case diagram. Tahapan selanjutnya adalah melakukan studi literatur dari berbagai buku dan jurnal untuk mencari landasan teori dan penelitian terkait. Kemudian melakukan pemilihan perangkat lunak ERP, setelah itu melakukan konfigurasi dan kustomisasi modul perangkat lunak ERP tersebut, serta terakhir melakukan penerapan dan pengujian. Hasil yang diharapkan dari penelitian ini adalah dapat mengatasi permasalahan pada Toko Soviah. 

scholarly journals Prediction of customer behaviour through datamining assets

2009 ◽  
Vol 57 (3) ◽  
pp. 43-54
Author(s):  
Naděžda Chalupová
Keyword(s):  
Neural Network ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Marketing Strategies ◽  
Customer Relationship ◽  
Business Managers ◽  
Correct Decision ◽  
Commercial Success ◽  
Customer Behaviour ◽  
Managerial Decisions

Business managers accounting for commercial success or non-success of the organization have to gain knowledge needful for correct decision acceptance. These knowledge represent sophisticated information hidden in enterprise data. One possibility, how to extract mentioned knowledge from data, is to use so-called datamining assets.The paper deals with an application of chosen basic methods of knowledge discovering in da­ta­ba­ses for area of customer-provider relation and it presents, how to avail acquired knowledge as basis of managerial decisions leading to improving of customer relationship management. It solves prediction, whose aim is, on the basis of some attributes of exploring objects, to predict future be­ha­viour of objects with these attributes. This way acquired knowledge, as the output of prediction, then can markedly help competent enterprise manager with planning of marketing strategies, for example so-called cross-selling and up-selling. The contribution describes a whole operation of available data processing: from its purifying, over its preparation for mining task, to self processing by the help of SAS Enterprise Miner tool. Regression analysis, neural network and decision tree, whose principles are briefly explained in this paper too, were used for knowledge mining. The estimation of customer behaviour was tested by two mining task varying in attribute using and in categories number of one of predicive attributes. The results of these two tasks are confronted by the help of prediction fruitfulness charts.

Effectiveness of Customer Relationship Management Program in Insurance Companies

2013 ◽  
pp. 219-234
Author(s):  
Vikas Gautam
Keyword(s):  
Customer Relationship Management ◽  
Life Insurance ◽  
Insurance Industry ◽  
Private Insurance ◽  
Relationship Management ◽  
Management Program ◽  
Customer Relationship ◽  
Insurance Companies ◽  
Public And Private ◽  
Before And After

Customer relationship management in the insurance industry is in the nascent stage. Firms are framing new strategies to combat stiff competition. Public and private insurance companies are implementing customer relationship programs to attract more customers and retain existing customers. The objectives of this study are (1) to study the customer relationship management program of the Life Insurance Corporation of India, and (2) to assess the effectiveness of this customer relationship management program. The study is based on the opinion scores of 182 policyholders of Life Insurance Corporation of India, who have been with the company for more than the last five years. Based on the average opinion scores before and after the implementation of the Customer Relationship Management program, it was concluded that the program is effective, which was evidenced by the results obtained from statistical analysis (Paired sample t-test).

scholarly journals Development of Customer Relationship Management System in E-Commerce Based on BP Neural Network

2012 ◽  
Vol 6-7 ◽  
pp. 995-999
Author(s):  
Mei Ling Zhou ◽  
Jing Jing Hao
Keyword(s):  
Neural Network ◽  
Customer Relationship Management ◽  
Bp Neural Network ◽  
Management System ◽  
Customer Value ◽  
Relationship Management ◽  
Customer Relationship ◽  
Feed Forward Network ◽  
Neural Network Algorithm ◽  
Hidden Layer

BP neural network can learn and store a lot of input - output mode mapping, without prior reveal the mathematical equations describe the mapping. The model based on BP neural network algorithm is constituted by an input layer, output layer and one hidden layer, three-layer feed forward network. CRM is to acquire, maintain and increase the methods and processes of profitable customers. The core of CRM is the customer value management, customer value; it is divided into the de facto value, potential value and model value. The paper presents development of customer relationship management system in e-commerce based on BP neural network. The experiment shows BP is superior to RFCA in CRM.

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