Retention Strategy for Existing Users of Mobile Communications

Ding, Yi-Fan

doi:10.1007/978-981-16-5857-0_39

Cited by 3 publications

(2 citation statements)

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“…It is identified that every sector of the economy now relies upon wireless technologies such as in banking, agriculture, transportation, healthcare, education, and many more [1]. Todays, the development of 4G to 6G services, mobile network, high-speed data, wireless sensor network and broadband services have become the most important sources of mobile communications operation services [2,3]. Population changes using mobile phone data has been investigates and the social networking sites use and college students' academic performance on testing for an inverted Ushaped relationship using automated mobile app usage data also has been analyzed [4].…”

Section: Introductionmentioning

confidence: 99%

Campus Quality of Services Analysis of Mobile Wireless Communications Network Signal among Providers in Malaysia

Kassim¹,

Hisam²,

Ismail³

2022

IJACSA

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Wireless communication is very important in this generation where todays 5G internet connection is still unconfirmed and 4G communication is still needed. Network in Malaysia has been supported by many telecommunication companies and the Quality of Services is still poor supported especially in the campus area. This research presents a performance analysis of Quality of Services for 4G wireless Communication among Providers supported in a campus area in Malaysia. A 4G Nemo Outdoor wireless analyzer was used to collect the Reference Signal Received Power (RSRP) signal data based on the identified campus road maps. Digi and U-Mobile Network was identified and compared as two telecommunications providers in the testing. The identified road maps were analyzed along the routes while testing signals are collected while driving. It is identified that Digi supports better for the Mobile broadband network which shows an excellent of 1% and good connections of 29 % and 0% signal loss in the drive areas. RSRP signal for U-Mobile shows there is 8% signal loss and the connections provided only at the Mid-Cell for 43% and Cell Edge connections for 48%. This concludes that the 4G signal strength in the campus area having average signal strength, but some medium signal strength is also identified based on the road locations. This research is significant for QoS of supports mobile network in a campus area.

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Section: Introductionmentioning

confidence: 99%

Campus Quality of Services Analysis of Mobile Wireless Communications Network Signal among Providers in Malaysia

Kassim¹,

Hisam²,

Ismail³

2022

IJACSA

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“…As the number of mobile operators increases, consumers can switch from one telecommunication operator to another if they are not satisfied with the service. Competition between operators for current consumers is becoming increasingly intense (Ding, 2022). Clients are a highly important asset in any business.…”

Section: Introductionmentioning

confidence: 99%

Customer churn prediction model: a case of the telecommunication market

et al. 2022

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The telecommunications market is well developed but is characterized by oversaturation and high levels of competition. Based on this, the urgent problem is to retain customers and predict the outflow of customer base by switching subscribers to the services of competitors. Data Science technologies and data mining methodology create significant opportunities for companies that implement data analysis and modeling for development of customer churn prediction models. The research goals are to compare different approaches and methods for customer churn prediction and construct different Data Science models to classify customers according to the probability of their churn from the company’s client base and predict potential customers who could stop to use the company’s services. On the example of one of the leading Ukrainian telecommunication companies, the article presents the results of different classification models, such as C5.0, KNN, Neural Net, Ensemble, Random Tree, Neural Net Ensemble, etc. All models are prepared in IBM SPSS Modeler and have a high level of quality (the overall accuracy and AUC ROC are more than 90%). So, the research proves the possibility and feasibility of using models in the further classification of customers to predict customer loyalty to the company and minimize consumer’s churn. The key factors influencing the customer churn are identified and form a basis for future prediction of customer outflow and optimization of company’s services. Implementation of customer churn prediction models will help to maintain customer loyalty, reduce customer outflow and increase business results

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Identification of churn affecting factors for customer satisfaction in telecommunication industry using Deep Learning

Gurumoorthy,

Suresh

2023

2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication

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Retention Strategy for Existing Users of Mobile Communications

Cited by 3 publications

References 0 publications

Campus Quality of Services Analysis of Mobile Wireless Communications Network Signal among Providers in Malaysia

Campus Quality of Services Analysis of Mobile Wireless Communications Network Signal among Providers in Malaysia

Customer churn prediction model: a case of the telecommunication market

Identification of churn affecting factors for customer satisfaction in telecommunication industry using Deep Learning

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