Designing Combo Recharge Plans for Telecom Subscribers Using Itemset Mining Technique

Now a days Machine Learning has become an integral part of human research. People are tending to select more automatic system rather than going with the manual handling. Data mining has the huge effect on business analysis as all business relies on their behaviour of customers. Mining the behaviour of customers can help the very existence of the company. This paper has proposed the way to satisfy customers in telecommunication market by knowing the customer’s recharge pattern. It can enhance their will to use the same service provider. By mining the recharge pattern of individual customer, this system will help telecom service providers to prepare combo plans, which will indeed be less than the individual recharges. For mining such kind of data, we are using FP Growth algorithm, it allows frequent item set discovery without candidate item set generation. FP Growth is two step approach, first it builds a compact data structure called the FP-tree and then Extracts frequent item sets directly from the FP-tree

Churn classification model for local telecommunication company based on rough set theory

Customer care plays an important role in a company especially in managing churn for Telecommunication Company. Churn is perceived as the behaviour of a customer to leave or to terminate a service. This behaviour causes the loss of profit to companies because acquiring new customer requires higher investment compared to retaining existing ones. Thus, it is necessary to consider an efficient classification model to reduce the rate of churn. Hence, the purpose of this paper is to propose a new classification model based on the Rough Set Theory to classify customer churn. The results of the study show that the proposed Rough Set classification model outperforms the existing models and contributes to significant accuracy improvement.Keywords: customer churn; classification model; telecommunication industry; data mining;rough set

Correspondence Analysis of Indonesian Retail Banking Personal Loans Top Up

Customer experience can be developed through good database management, and this is an important thing to do in the era of tough retail banking competition especially in the personal loan market competition. Through good database management, banks can understand the transaction pattern and customer behavior in each bank service’s contact point. This research aimed at identifying the personal loans correspondence between socioeconomic variables and top up transaction by using the secondary data from one of Indonesian retail banking. The research method used the correspondence analysis and regression. The result of the research showed that the socioeconomic factors that influenced the debtors to top up personal loans at the confidence level of 5% (0.05) included Age, Marital Status, Dependent Number, Living Status, Education, Region, Job Type, Work Length, Salary, Debt Burdened Ratio (DBR), Credit Tenure, and Credit Limit, and only Gender had no effect on personal loan top up. The socioeconomic factors that were close correspondence with the personal loan top up transactions included bachelor degree, State-Owned Enterprises and goverment civil servant employee, income starting from Rp 5 million, credit period starting from 4 years, dan credit limit starting from Rp 50 million. The findings in this study are expected to be useful for marketers of the banks in developing personal loan products and also in preparing a more targeted marketing strategy so that it becomes more effective and efficient for the banks. In addition, the expected implication is that the customer experience will be better because the product developed will be more customer centric. Keywords: bank, correspondence analysis, personal loans, regression, top u

Intelligent approach for attracting churning customers in banking industry based on collaborative filtering

During recent years, increased competition among banks has caused many developments in banking experiences and technology, while leading to even more churning customers due to their desire of having the best services. Therefore, it is an extremely significant issue for the banks to identify churning customers and attract them to the banking system again. In order to tackle this issue, this paper proposes a novel personalized collaborating filtering recommendation approach joint with the user clustering technology. In the proposed approach, first a hybrid algorithm based on Particle Swarm Optimization (PSO) and K-mean cluster the loyal customers. The clusters of loyal customers are used to identify the features of the churning customers. Finally, the list of appropriate banking services are recommended for the churning customers based on a collaborative filtering recommendation system. The recommendation system uses the information of loyal customers to offer appropriate services for the churning customers. We applied successfully the proposed intelligent approach to return the churning customers of an Iranian bank.http://www.jise.ir/article_16171.htm

Predicting time-to-churn of prepaid mobile telephone customers using social network analysis

Mobile phone carriers in a saturated market must focus on customer retention to maintain profitability. This study investigates the incorporation of social network information into churn prediction models to improve accuracy, timeliness, and profitability. Traditional models are built using customer attributes, however these data are often incomplete for prepaid customers. Alternatively, call record graphs that are current and complete for all customers can be analysed. A procedure was developed to build the call graph and extract relevant features from it to be used in classification models. The scalability and applicability of this technique are demonstrated on a telecommunications data set containing 1.4 million customers and over 30 million calls each month. The models are evaluated based on ROC plots, lift curves, and expected profitability. The results show how using network features can improve performance over local features while retaining high interpretability and usability

Investigating the consumer decision-making process and determinants of choice for prepaid services from mobile network service providers

The mobile telecommunications industry has been a fundamental and an important enabler in the advancement of the South African economy, with mobile network providers investing billions of rands in mobile infrastructure and facilitating a functional and progressive global marketplace (ICASA Annual Performance Plan, 2020/21). South Africa’s telecommunications system is one of the most sophisticated in the emerging markets, and according to Gillwald, Mothobi, and Rademan (2018, p.6), various indices including the ICT Development Index corroborate this view. The deployment of wireless communications networks in the country has had immeasurable social benefits for many consumers. The most rural areas of the country are now able to experience the convenience and ubiquity that comes with having access to mobile network technology. Though mobile network provision is making progress in terms of bridging the digital divide, inhibitors exist within the mobile competitive landscape that prevent consumers from exploring the full benefits of the advanced technologies at their disposal. According to Chinembiri (2020, p.6), mobile data costs remain high and out of reach for the average South African consumer, despite the recent requisite data price reduction by the dominant mobile network service providers. The prepaid segment is dominated by customers who either carry multiple SIM cards or switch between mobile network operators. The adoption by ICASA of the Mobile Number Portability (MNP), the process through which customers switch between mobile operators and keep their mobile number (Yadav, Dabhade, & Dabhade, 2013, p.1), resulted in significant reduction in switching costs thus perpetuating the migration of subscribers between mobile network providers. According to Olufemi and Strydom (2018, p. 52), the fiercest competition experienced by South African mobile providers is in the prepaid market.Thesis (MBA) -- Faculty of Business and Economic Sciences, Business School, 202

Investigating the consumer decision-making process and determinants of choice for prepaid services from mobile network service providers

The mobile telecommunications industry has been a fundamental and an important enabler in the advancement of the South African economy, with mobile network providers investing billions of rands in mobile infrastructure and facilitating a functional and progressive global marketplace (ICASA Annual Performance Plan, 2020/21). South Africa’s telecommunications system is one of the most sophisticated in the emerging markets, and according to Gillwald, Mothobi, and Rademan (2018, p.6), various indices including the ICT Development Index corroborate this view. The deployment of wireless communications networks in the country has had immeasurable social benefits for many consumers. The most rural areas of the country are now able to experience the convenience and ubiquity that comes with having access to mobile network technology. Though mobile network provision is making progress in terms of bridging the digital divide, inhibitors exist within the mobile competitive landscape that prevent consumers from exploring the full benefits of the advanced technologies at their disposal. According to Chinembiri (2020, p.6), mobile data costs remain high and out of reach for the average South African consumer, despite the recent requisite data price reduction by the dominant mobile network service providers. The prepaid segment is dominated by customers who either carry multiple SIM cards or switch between mobile network operators. The adoption by ICASA of the Mobile Number Portability (MNP), the process through which customers switch between mobile operators and keep their mobile number (Yadav, Dabhade, & Dabhade, 2013, p.1), resulted in significant reduction in switching costs thus perpetuating the migration of subscribers between mobile network providers. According to Olufemi and Strydom (2018, p. 52), the fiercest competition experienced by South African mobile providers is in the prepaid market.Thesis (MBA) -- Faculty of Business and Economic Sciences, Business School, 202