Abstract— Customer churn is a business term used to describe the loss of customer. It describes those customers or clients who leave or switch to competitors. In the telecommunication industry, customers have multiple choices of services and they frequently switch from one service to another. In this competitive market, customers demand best products and services at low prices, while service providers constantly focus on getting hold of as their business goals. So that’s why there is very higher rate of customer churn in telecommunications industry experiences an average of 30-35% annual churn rate. The purpose of this paper is to propose an efficient Customer Churn Prediction Model based on classification techniques, which will help the telecommunication company to predict the customer churn rate to know about which customers are loyal to them. I. INTRODUCTION Data mining is very famous technique for churn prediction and it is used in many fields. Data mining refers to the process of analyzing data in order to determine patterns and their relationships. It is an advanced technique which goes deep into data and uses machine learning algorithms to automatically shift through each record and variable to uncover the patterns and information that may have been hidden. There is a lot of work done in data mining for churn prediction in different fields. It is used to solve the customer churn problem by identifying the customer behavior from large number of customer data. Problem Statement: Customer churn refers to the periodic loss of customers in an organization. Customer churn is a very common problem of every organization all over the world. In the competitive market it’s a very big challenge for any organization to retai... ... middle of paper ... ...iningMart: Proceedings of the workshop on data mining and …, 2005 – Citeseer [16] Mozer M. C., Wolniewicz R., Grimes D.B., Johnson E., Kaushansky H. Predicting Subscriber Dissatisfaction and Improving Retention in the Wireless Telecommunication Industry. IEEE Transactions on Neural Networks, Special issue on Data Mining and Knowledge Representation (2000). [17] Mutanen,Teemu. Customer churn analysis- a case study, Research Report VTTR0118406, March 15, 2006. [18] De Oliveira, J.V., Pedrycz W. (editors) (2007) Advances in Fuzzy Clustering and its Applications, John Wiley & Sons Ltd. [19] J. Hadden, A. Tiwari, R. Roy, and D. Ruta. Churn Prediction using Complaints Data. International Journal of Intelligent Technology, 13:158{163, May 2006. [20] H. Van Khuu, H.-KieLee, and J.-Liang Tsai. “Machine learning with neural networks and support vector machines”, 2005.
Verizon Wireless cellular service is inelastic because the products and services it offers makes them the dominant leader in the wireless industry; therefore, a 10% change in calling plan prices (monthly access fees) would not affect the quantity demanded. Verizon Wireless can depend on this inelasticity in their pricing model because of the strength of its brand and the wealth of products and services it offers. Verizon Wireless' competitive advantage comes from its ultra-low churn rate (the percentage of customers who disconnect their service is less than one percent of its 60 million customer base). This indicator suggests that customers are satisfied with the service Verizon Wireless offers and a slight price increase probably would not drive its customers to the competition. This data also suggests that customers probably stay with Verizon Wireless because of its continued expansion of new technologies and services such as its all-digital nationwide CDMA network, EVDO' or its advanced data network (used to wireless send and receive email and other data almost anywhere in the US), and VoIP (Voice over Internet Protocol) that they use for their Push to Talk products. Verizon Wireless markets to a nearly all demographics nationwide and most of its services are offered in the smaller rural markets as a direct result of the one billion dollars per quarter it spends on improving its network as well as acquiring smaller wireless networks to make their nationwide network stronger and larger.
In today’s telecommunication market there is a lot of competition by industry giants such as Sprint, MCI, and AOL, but simultaneously the very high cost involved with entering and competing in this industry also makes it very unattractive for new entrants. These are just some of the big names who are planning to and are presently providing parts of the pipe dream that AT&T seems to seek. In this industry it is very important to have customer awareness of the line of products you carry. Most of the public hears the name AT&T or Sprint or MCI and they think telephone bills but many consumers do not realize that these companies have expanded their field of services from cellular phones to wireless web services. The reason mainly being the lack of marketing, and direct consumer advertising provided by these firms on the other line of p...
Service/Satisfaction- AT&T has settle to be adequate in Customer Service by changing is “Customer Rules” to just “Earning Industry Leading Retention”. Although they have made tremendous strides in reducing their churn from 2.1% to 1.6% in two years validating their commitment to provide a better system to their customers after the merger.
Customer loyalty comes from the personal relationship that is developed between the customer and the business. One method used to understand the customer relationship is called customer relationship intensity and Life-cycle segmentation (UOP, 2007). This process includes classifying all the customer relationships into one of five groups.
RBC Financial Group uses a customer relationship management (CRM) strategy that provides a variety of services for a variety of clients. The strategy allows for individual customers to trust RBC and develop a personal relationship with each and every client. One major factor that allows CRM to operate effectively is the use of technologies and analytics to help classify each client’s financial situation. These customer profitability-based techniques allowed RBC to categorize their clients into A, B, and C groups so that the sales teams could optimize their efforts in catering to these different clients. This strategy holds the following strengths: optimizing sales efforts to different customers, easily accessible electronic sales leads, centralized and standardized financial decisions, and building personalized and sustainable customer relationships. There are a few weaknesses to the system though including the complexity in predicting future positions of companies despite the use of analytics as well as the complexity in creating consistency when using these
Companies must understand the potential hazard that high turnover rate may cause company. By analyzing banks, one can understand what and where the problem lies.
Churn Rate is the number of customers who cut relations with the company (Store) during a given time period. Tracking of churn rate will be useful to the company in preventing to lose relations with an existing customer by taking appropriate measures. Churn Prediction emphasizes on predicting the probability that a customer will stop buying from the store and ...
This chapter gives the overview of the Association Rule Mining. It gives the importance of the Market Basket Analysis and its usefulness in increasing the sales of the supermarket. This chapter also provides an overview of the data mining process used in market basket analysis and the proposed approaches. The works of a few scientists are cited and utilized as proof to confidence the ideas clarified in the theory. Every such proof utilized is recorded as a part of the reference area of this thesis.
Buyer power is very low in this market because one customer’s decision to use the service or not to use it will not affect the overall market. Likewise, one customer’s dissatisfaction will not influence a significant number of other c...
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Singh, Y. & Chauhan, A. (2009). Neural networks in data mining. Journal of Theoretical and
By 2002-03, Indian market has grown highly competitive. Due to fall in ARPU (average monthly revenue per customer unit), players fought to capture new subscribers. With industry consolidation, the focus is switching from having a national footprint to the ability to provide value-added services. Opera...
The dynamics of our society bring many challenges and opportunities to the business world. Within the last decade, hundreds of jobs have emerged particularly in the technology sector to help keep up with the ever-changing world and to compete on a larger and better scale than the competition. Two key job markets and the basis of this research paper are business intelligence or BI and data mining or DM. These two fields play a very important role in small to large companies and are becoming higher desired sectors within the back offices of the workplace. This paper will explore what the meaning of BI and DM really is, how they are used and what we can expect as workers and learners of the technology and business fields for the future.
The objectives are to ascertain best market share of telecom providers, switching attitude of population, most crucial influence in affecting switching behaviour and purchasing a SIM card.
There are many description and theory of customer loyalty. We should research and compare which theory is suitable for our business.