The Importance of Data Within Contemporary CRM

2010 ◽  
pp. 2041-2054
Author(s):  
Diana Luck
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Data Storage ◽  
Relationship Management ◽  
Cost Savings ◽  
Customer Relationship ◽  
Evidence Based ◽  
Essential Components ◽  
Collection Data ◽  
Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

The Importance of Data Within Contemporary CRM

2009 ◽  
pp. 96-109 ◽  
Author(s):  
Diana Luck
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Data Storage ◽  
Relationship Management ◽  
Cost Savings ◽  
Customer Relationship ◽  
Evidence Based ◽  
Essential Components ◽  
Collection Data ◽  
Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

Integrating Internet/Database Marketing for CRM

2005 ◽  
pp. 157-174
Author(s):  
Sally Rao ◽  
Chris O’Leary
Keyword(s):  
Action Research ◽  
Data Collection ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Cost Savings ◽  
Customer Relationship ◽  
The Internet ◽  
Database Marketing ◽  
Customer Information ◽  
Consumer Data

Firms have only just begun to fully use the Internet to obtain customer information in their database marketing processes to enhance customer relationship management (CRM). This chapter introduces a framework about how they can do this. Essentially, it argues that the advent of Internet/database marketing brings solutions to some of the difficulties in customer relationship management by providing one-to-one interactivity and customization. For example, the Internet offers benefits, such as increased consumer data collection accuracy and speed, cost savings in collecting data, greater interaction, and better relationships with customers. This chapter develops a framework for integrating the Internet and database marketing to help marketers improve customer relationship management through rigorous action research.

Enhancing the Electronic Customer Relationship Management through Data Mining

2010 ◽  
pp. 119-139
Author(s):  
M. Vignesh
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Customer Relationship Management ◽  
Business Intelligence ◽  
Relationship Management ◽  
Daily Basis ◽  
Customer Relationship ◽  
Data Driven Approach ◽  
Second Tier

According to the Moore’s law, the number of transistors per microprocessor will double in every two years. In no doubt, this exponential increase in the processing speeds would be flanked by the increasing amount of data that corporates contend on a daily basis. Hence all corporates are literally drowning in data. But definitely there exists a hiatus between the data storage and the information retrieval. One can ask an enigmatic question, how effectively a stored data can be utilised for the decision making in the long-term perspective. The answer is not yet arrived out. Hence the “Organizations are data rich, but information poor!”. If capturing and storing the relevant data is a hectic task, then analyzing and translating this data into the actionable information is the other corner stone in any information systems of a concern. This gap can be bridged or overruled by the concept of business intelligence. Business Intelligence (BI) can be simply defined in terms of data –driven approach rather than information driven which includes methods as decision support systems, online analytical processing (OLAP), statistical analysis, query and reporting, forecasting which can be primarily done by data mining. BI along with customer relationship management (CRM) software forms the second tier of a firm’s IT infrastructure. This chapter holds a bird’s eye view of the usage of datawarehousing approaches for a systematic business intelligence approach and its varied applications in view of electronic customer relationship management.

scholarly journals Penerapan Algoritma Fuzzy C-Means Dipadukan Dengan Model Fuzzy Recency Frequency Monetary (RFM) Untuk Customer Relationship Management (CRM) (Studi Kasus Di TokoSweet Amirah Medan)

2019 ◽  
Vol 15 (1) ◽  
pp. 7
Author(s):  
Yohanni Syahra ◽  
Yusnidah Y ◽  
Beni Andika
Keyword(s):  
Data Mining ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Fuzzy C Means

Konsumen merupakan aset yang sangat penting bagi perusahaan retail.Hal ini adalah alasan mengapa perusahaan retail harus merencanakan dan menggunakan strategi yang cukup jelas dalam memperlakukan konsumen.Dengan banyaknya jumlah konsumen yang dimiliki oleh suatu perusahaan retail, maka masalah yang dihadapi adalah bagaimana menentukan konsumen potensial.Dengan menerapkan konsep CRM (Customer Relationship Management), perusahaan dapat melakukan identifikasi konsumen potensial dengan melakukan segmentasi konsumen. Tujuan dari proses segmentasi konsumen adalah untuk mengetahui perilaku konsumen dan menerapkan strategi pemasaran yang tepat sehingga mendatangkan keuntungan bagi pihak perusahaan. Penelitian ini membahas tentang bagaimana proses data mining dari data konsumen di Toko Sweet Amirah, yaitu perusahaan retail yang khusus menjual perlengkapan dan peralatan bayi serta underwear pria dan wanita dewasa dan anak-anak dan berlokasi di Jalan Gedung Arca No. 29 B-C, Medan.ProsesData Miningini menggunakan data yang berasal dari data penjualan pada Toko Sweet Amirah dan bertujuan untuk mencari konsumen potensial.Model RFM merupakan model segmentasi yang umum digunakan pada perusahaan retail. Selanjutnya melakukan proses clustering menggunakan algoritma Fuzzy C-Means (FCM). Pada FCM jumlah cluster ditentukan. Hasil clustering dari algoritma tersebut digunakan untuk Aplikasidata miningmenggunakan MATLAB versi 7.10.0 dan memanfaatkan beberapatoolboxyaituFuzzy Logic ToolboxdanDatabase Toolbox

scholarly journals Implementasi Costumer Relationship Management (CRM) Pada Sistem Informasi Penjualan Ban Di Toko Lingga Ban Berbasis Web

2018 ◽  
Vol 12 (1) ◽  
Author(s):  
Ipan Supandi ◽  
Fahmi Yusuf ◽  
Fauziah F
Keyword(s):  
Information System ◽  
Data Storage ◽  
Customer Relationship Management ◽  
Effective Means ◽  
Relationship Management ◽  
Customer Relationship ◽  
Programming Technique ◽  
Web Based ◽  
Testing Method ◽  
White Box Testing

The store Lingga Tires is a trademark unit engaged in the sale of the tires. The store Lingga Tires only rely on the conventional sales namely the subscriber must come into the store and doing transaction at the store. This makes the customer became less know the products in the market and the existing promotion. The store Lingga Tires want to provide a satisfactory services with want to deliver innovation and convenience for customers. To store the Lingga Tires need a means to support the sales transaction and media promotions effective means of implementing the method Customer Relationship Management (CRM) web-based. CRM is one of the means to build a good relationship with customers and to acquire new customers. Web-based Sales information system is built by the method of software development waterfall , the language of PHP programming technique, MySQL database as data storage and testing method using the black box & white box testing this system can be used by the administrator, customers and direction. The administrator is the person who manages the whole system. Customers can make your reservation, payment confirmation and have points shopping. The direction of instructions view report, this system is expected to be a solution to overcome the problems and to be able to increase sales in the Store Lingga Tires.Key Words: Information System,Sale,CRM, Web, Store Lingga Tires

scholarly journals IMPLEMENTASI ALGORITMA FUZZY C-MEANS DAN METODE RECENCY FREQUENCY MONETARY (RFM) PADA APLIKASI DATA MINING UNTUK PENGELOMPOKAN PELANGGAN

Sebatik ◽  
2018 ◽  
Vol 22 (2) ◽  
pp. 88-94
Author(s):  
Nindya Rahmawati Syarif ◽  
Windarto Windarto
Keyword(s):  
Data Mining ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Fuzzy C Means ◽  
Rfm Model ◽  
Total Data

Pada dunia retail, konsumen merupakan salah satu aset yang sangat berpengaruh. Oleh sebab itu konsumen menjadi alasan perusahaan retail harus merencanakan dan mempunyai strategi yang baik dalam memperlakukan konsumennya. Dengan banyaknya jumlah konsumen yang dimiliki oleh suatu perusahaan retail, maka masalah yang harus dihadapi adalah bagaimana menentukan konsumen potensial dan menerapkan strategi pemasaran yang tepat sehingga mendatangkan keuntungan bagi pihak perusahaan. Maka dari itu, dengan menerapkan konsep CRM (Customer Relationship Management), perusahaan dapat melakukan penerapan konsumen potensial dengan melakukan segmentasi pengelompokan konsumen. Penelitian ini membahas tentang proses data mining menggunakan data konsumen dan data transaksi pada PT Eka Cipta Rasa. Proses data mining dimulai dengan melakukan proses clustering menggunakan algoritma Fuzzy C-Means (FCM). Output dari FCM adalah deretan pusat cluster dan beberapa derajat keanggotaan untuk setiap titik data. Hasil clustering digunakan untuk melakukan segmentasi kelas konsumen dengan menggunakan model Fuzzy RFM. Model Fuzzy RFM yaitu dengan menggabungkan teori himpunan fuzzy dengan model RFM dengan segmentasi berdasarkan atribut Recency, Frequency, dan Monetary. Umumnya perusahaan retail menggunakan metode ini untuk proses segmentasi konsumennya. Pengelompokkan (cluster) pelanggan berdasarkan karakteristik dan sifat saat bertransaksi dapat dijadikan suatu alternatif dalam pemecahan masalah. Dalam hal  ini, pelanggan akan dibagi menjadi 4 kelompok atau cluster pelanggan diantaranya  Golden, Silver, Bronze, dan Iron adapun variabel yang menjadi acuan pengelompokannya adalah tanggal pembelian akhir , frekuensi beli, dan total pembelian. Data yang digunakan merupakan data transaksi pelanggan periode Januari sampai Juni 2016. Total data adalah 4007 transaksi dari 328 pelanggan. Setelah data tersebut diolah dengan algoritma Fuzzy C-Means dan metode RFM, hasil akhir pada proses ini menunjukkan iterasi berakhir pada iterasi ke – 9 dengan total fungsi objektif sebesar 102,2 dan perubahan fungsi objektif sebesar 51,1. Cluster pelanggan yang dihasilkan adalah Golden : 38, Silver: 186, Bronze : 103 dan Iron : 0 .

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