Dropout Prediction: A Systematic Literature Review

Dropout predicting is challenging analysis process which requires appropriate approaches to address the dropout. Existing approaches are applied in different areas such as education, telecommunications, retail, social networks, and banking services. The goal is to identify customers in the risk of dropout to support retention strategies. This research developed a systematic literature review to evaluate the development of existing studies to predict dropout using machine learning, following the guidelines recommended by Kitchenham and Peterson. The systematic review followed three phases planning, conducting, and reporting. The selection of the most relevant articles was based on the use of Active Systematic Review tool using artificial intelligence algorithms. The criteria identified 28 articles and several research lines where identified. Dropout is a transversal problem for several sectors of economic activity, where it can be taken countermeasures before it happens if detected early

A SLR on Customer Dropout Prediction

Dropout prediction is a problem that is being addressed with machine learning algorithms; thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as which features should be selected and how to measure accuracy while considering whether the features are appropriate according to the business context in which they are employed. To solve these questions, the goal of this paper is to develop a systematic literature review to evaluate the development of existing studies and to predict the dropout rate in contractual settings using machine learning to identify current trends and research opportunities. The results of this study identify trends in the use of machine learning algorithms in different business areas and in the adoption of machine learning algorithms, including which metrics are being adopted and what features are being applied. Finally, some research opportunities and gaps that could be explored in future research are presented.info:eu-repo/semantics/publishedVersio

A SLR on Customer Dropout Prediction

Dropout prediction is a problem that is being addressed with machine learning algorithms; thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as which features should be selected and how to measure accuracy while considering whether the features are appropriate according to the business context in which they are employed. To solve these questions, the goal of this paper is to develop a systematic literature review to evaluate the development of existing studies and to predict the dropout rate in contractual settings using machine learning to identify current trends and research opportunities. The results of this study identify trends in the use of machine learning algorithms in different business areas and in the adoption of machine learning algorithms, including which metrics are being adopted and what features are being applied. Finally, some research opportunities and gaps that could be explored in future research are presented.info:eu-repo/semantics/publishedVersio

Customer Churn Prediction in Telecom Industry Using Deep Learning Techniques

In recent times, the telecommunications request has beenveritably competitive. The cost of retaining telecom guests is lower thanattracting new guests. A telecom company must understand client churn through client relationship management. Therefore, CRM analyzersare demanded to prognosticate which guests will change. In this design, aclient abandonment vaticination model was proposed that uses the Decision Treealgorithm, Random timber algorithm, and Deep literacy algorithm to identify thechurn guests. In Deep Literacy, a Multilayer Perceptron Neural Network has beenused to produce the vaticination model. The performance of all the algorithmswill be compared and estimated in terms of delicacy. The advanced performancevaticination model can be used in the telecom sphere for prognosticatingwhether the guests will churn or not. By knowing the significant churn factorsfrom client data, CRM can ameliorate productivity, recommend applicableelevations to the group of likely churn guests grounded on analogous getspatterns, and exorbitantly ameliorate marketing juggernauts of the company

An experimental analysis of overconfidence in tariff choice

Consumers regularly have to choose between a pay-per-use and a flat-rate option. Due to the increasing number and range of (digital) services, the frequency at which consumers have to make tariff-choice decisions to use these services has become even more prevalent. Prior work has demonstrated that consumers’ tariff choices are often systematically biased and identified overconfidence as one of the key drivers. Yet, prior research is non-experimental and focused on the so-called flat-rate bias. By contrast, we examine the effects of overconfidence on the choice between a pay-per-use and a flat-rate option using an experimental approach. We develop an incentive-compatible experiment to provide causal evidence for the effect of overconfidence on tariff-choice decisions. We find that overconfident (underconfident) consumers underestimate (overestimate) their actual usage, which leads them to choose a pay-per-use (flat-rate) option relatively more frequently. Based on the results, we discuss theoretical and managerial implications as well as avenues for future research

An Empirical Investigation of Customer Retention: Addressing Unique Challenges in Customer-Firm Relationships

Effective customer retention is vital to the survival and prosperity of any customer-centric organization. Systematic examination of different aspects of the customer’s relationship with the firm has the potential to provide valuable insights to support retention efforts. However, the nature of the purchasing options and relationship patterns inherent in each industry require managers to shift their focus on varied aspects of the relationship, thus posing unique challenges. One such challenge is examined in the first essay of this dissertation, in a setting where customer-firm relationships are intermittent, with customers being lost to and won back again by the firm. A unifying model for joint estimation of the customers’ second lifetime duration, multiple repeat churn reasons, and heterogeneity in exhibiting a related churn reason is developed to study this relationship. The findings support the existence of a cured group of returning customers, defined as those who are not susceptible to churn due to a repeated reason. Another challenge is examined in the second essay, which involves a setting where the structure of the purchasing options is a combination of contractual and noncontractual services. The complexities and dynamics of the customer-firm relationship and customers’ underlying commitment to it are modeled through a hidden Markov model, incorporating the dependency between the two purchase processes. The findings suggest that contractual and noncontractual purchase behaviors are distinct but interrelated

How to improve customer retention and lifetime value on subscription-based models: In company project with "The Bam and Boo" toothbrush

The present In-Company project aims to study how subscription-based business models can improve their retention and customers lifetime value. This project was made in collaboration with ‘The Bam and Boo’ Toothbrush, a Portuguese brand bamboo toothbrushes subscription service that is in the market since June 2017 and currently accounts with more than 22.000 active subscribers. To achieve these project results we have used quantitative data from the company database reports, and qualitative data collected on a focus group session with a group of participants that resembles the brand’s target. From this data we were able to trigger some critical stages of retention and consumption patterns, and valuable insights regarding consumers behaviors and purchase profiles. Some of the critical questions that needed to be answered were related to – understand the moment of customers churns, which are the motives that led customers to make this action, and how is the company able to improve its customers lifetime and value. We present solutions on areas such as Communication, Customer Relationship Management, Product, and Organizational Strategy, in order to improve the company retention rates and overall results. For that the company should consider delivering a more personalized service and content to its customers, run a stronger email marketing strategy, rethink its portfolio, and share the company values and mission with its community.O presente projeto-empresa visa estudar de que forma conseguimos melhorar a retenção e o valor dos clientes em modelos de subscrição. Este projeto foi realizado em colaboração com a empresa 'The Bam and Boo', um serviço de subscrição de escovas de dentes de bambu. A marca portuguesa está no mercado desde Junho, 2017 e atualmente conta com mais de 22.000 subscritores ativos. De forma a alcançar os resultados propostos neste projeto recorremos a dados quantitativos, obtidos através da base de dados de clientes da empresa, e dados qualitativos, recolhidos de uma sessão com um grupo focal no qual os participantes representavam o target da marca. Assim, foi-nos possível detetar pontos críticos em relação aos padrões e comportamento dos consumidores, e os seus perfis de compra. As questões principais que pretendemos responder neste projeto são – compreender o momento em que os clientes desistem das suas subscrições, por que motivos o fazem e de que forma a marca pode aumentar o valor e a retenção dos seus clientes. Apresentamos soluções em áreas como – comunicação, gestão e relacionamento com os clientes, produto e estratégia da organização; com o fim de melhorar as taxas de retenção e os resultados da empresa como um todo. Para isso, a empresa deve reconsiderar algumas das suas políticas e oferecer um serviço mais personalizado e diversificado aos seus clientes, montar uma estratégia de email marketing mais forte, reconsiderar o seu portfólio de produtos, e a forma de partilha dos seus valores e missão com a sua comunidade

A mediating effect of customer retention on the Customer Lifetime Value Achievement among fitness industry in Malaysia: A study on the fitness industry in Malaysia and the creation of Customer Lifetime Value to enhance customer retention

The fitness business is an industry that is receiving an immense amount of attention and growth in Malaysia. With the growing awareness of Malaysians to seek methods to live a balanced lifestyle, fitness has now become a trend in most social media news. However, most fitness gyms are unable to retain their customers for long as these businesses lack the knowledge of creating a concrete and innovative business strategy which provides a direction towards innovation and long-term relationships. Customer Lifetime Value may be the solution to retain quality customers. Fitness studio owners need to apply the knowledge acquired from understanding the reasons members of the fitness studio subscribe to their membership and use that knowledge to invoke or ignite their desire through their business strategy. The inability of management to ‘see the light’ and act upon the concept of investing in customer lifetime value as a more profitable avenue than acquiring new clients prove to be the fall of many organizations in the fitness industry. This business research will be practising the philosophy of positivism with quantitative data being retrieved from members of the boutique fitness studios through a survey questionnaire and data collected from boutique gym owners through semi structured interviews. This is in line with the current research as the perspective of both members and fitness studio owners is taken into consideration. This business research is carried out in the fitness industry particularly with boutique fitness studios in Klang Valley which fills the gaps in academic literature regarding the use of Customer Lifetime Value in Customer Retention Strategies but also in the context of boutique fitness studios rather than big box gyms. The current study is done in Klang Valley, Malaysia which also contributes to the Asian context while most studies have been done in the Western countries

Possessions and the Self: Downstream Consequences of Ownership and Sharing What We Own

My dissertation is based on the premise that possessions are an extension of the self. Beyond simple functional benefits that possessions provide us, I question whether possessions affect our self-perception and behavior. Specifically, I focus on two aspects of possessions: Ownership (Essay 1) and Sharing (Essay 2). In Essay 1, I find that feeling a sense of product ownership has downstream consequences in one’s representation of who s/he is. Here I reveal that salient feelings of product ownership activate a product-related self in one’s mind, but more importantly deactivate product-unrelated self. By identifying simultaneous identity activation and deactivation, I show that an individual can only hold a limited number of salient selves, and activating one’s self aspect requires a trade-off. This finding updates the prior assumption in the literature that an individual can hold an unlimited number of selves, and further suggests that there is still a finite limit to what can be salient at a given time. My interest in ownership extends to Essay 2, where I examine another behavioral aspect of consumers: sharing. Sharing behavior has received much attention lately due to the rise of sharing economy platforms, which provide new opportunities for consumers to share personal belongings with others. In Essay 2, I mine people’s latent motivation behind sharing by using a transaction dataset from one of the largest sharing economy platforms, Airbnb. Here I find that people are driven by not only monetary, but also non-monetary reasons, such as desires to meet others and share the beauty of their homes. Then I explore how each motivation affects people’s engagement on the sharing economy platform and their continued effort to share. This second essay highlights individuals’ new role as micro-entrepreneurs in this new era of the 21st century

2019 SDSU Data Science Symposium Program

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