Telecommunication organizations are confronting in expanding client administration weight as they launch various user-desired services. Conveying poor client encounters puts client connections and incomes at danger. One of the metrics used by telecommunications companies to determine their relationship with customers is “Churn”. After substantial research in the field of churn prediction over many years, Big Data analytics with Data Mining techniques was found to be an efficient way for identifying churn. These techniques are usually applied to predict customer churn by building models, pattern classification and learning from historical data. Although some work has already been undertaken with regards to users’ perspective, it appears to be in its infancy. The aim of this thesis is to validate churn predictive heuristics from the operator perspective and close to user end. Conducting experiments with different sections of people regarding their data usage, designing a model, which is close to the user end and fitting with the data obtained through the survey done. Correlating the examined churn indicators and their validation, validation with the traffic volume variation with the users’ feedback collected by accompanying theses. A Literature review is done to analyze previous works and find out the difficulties faced in analyzing the users’ feeling, also to understand methodologies to get around problems in handling the churn prediction algorithms accuracy. Experiments are conducted with different sections of people across the globe. Their experiences with quality of calls, data and if they are looking to change in future, what would be their reasons of churn be, are analyzed. Their feedback will be validated using existing heuristics. The collected data set is analyzed by statistical analysis and validated for different datasets obtained by operators’ data. Also statistical and Big Data analysis has been done with data provided by an operator’s active and churned customers monthly data volume usage. A possible correlation of the user churn with users’ feedback will be studied by calculating the percentages and further correlate the results with that of the operators’ data and the data produced by the mobile app. The results show that the monthly volumes have not shown much decision power and the need for additional attributes such as higher time resolution, age, gender and others are needed. Whereas the survey done globally has shown similarities with the operator’s customers’ feedback and issues “around the globe” such a data plan issues, pricing, issues with connectivity and speed. Nevertheless, data preprocessing and feature selection has shown to be the key factors. Churn predictive models have given a better classification of 69.7 % when more attributes were provided. Telecom Operators’ data classification have given an accuracy of 51.7 % after preprocessing and for the variables we choose. Finally, a close observation of the end user revealed the possibility to yield a much higher classification precision of 95.2 %.

Den här studien syftar till att undersöka användarbortfall på webbaserad faktureringstjänst för småföretagare. Målsättningen var att, genom kartläggning av enkäter och intervjuer med användare, ta fram åtgärdsförslag för att förhindra framtida användarbortfall från tjänsten. Företaget bakom faktureringstjänsten har inte någon precis kunskap om varför nya användare väljer att lämna tjänsten. Detta eftersom man i dagsläget inte har några tydliga rutiner för att samla in denna information. Studien finner att tidigare användare av faktureringstjänsten har övergett denna för att de ansåg att designen på systemet var lite för inkonsekvent (bildbeskrivningen av webbsidorna motsvarar inte hur webbsidorna faktiskt ser ut) samt att priset inte stämde överens med förväntningarna de hade.

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As recommender systems have increasingly become prevalent to guide consumers to find their desired products in many industries, understanding the impact of recommender systems on consumer choices is critical to the business performance and raises important policy implications. In this thesis, we examine the role of different recommendation schemes, spanning from interpersonal recommendations in social environment given by peers to product display recommendations in physical shopping environment given by sellers on consumers’ switching and search behavior in two distinct case studies. In the first study, we look at the effect of peer recommendations on subscriber churn in a large mobile network. We find that consumers’ propensity to churn increases with the number of friends that churn and in particular with the number of strong friends that churn. In the second study, we implement an in-vivo randomized field experiment to measure the effect of product display recommendations as book placement on shopper behavior in a physical bookstore. We leverage video tracking technologies to monitor how shoppers respond to random book placement, which induces random search costs. We find that books recommended at the edge of the table are more likely to be picked and taken than those placed at the center of the table. More interestingly, we also find that conditional on being picked, shoppers are equally likely to take books placed at the edge and at the center of the table, suggesting that display recommendations positively affect consumer choice mainly through its effect on the search process and not through its effect on the consideration process. Therefore, we empirically show that provision of recommendations, although in different schemes, may generally help to reduce consumers’ search costs in product or service discovery process, relative to what they would do without such an intervention. Moreover, we perform a comparative analysis between offline and online applications of recommender systems to systematically investigate the current practices, future prospects and policy perspectives when applying recommender systems in physical retailing. All these issues highlight opportunities for physical retailers to design, implement and evaluate their recommender systems that offer convenience benefits and appropriate protection to consumers.

Churn analysis is an important tool for companies as it can reduce the costs that are related to customer churn. Churn prediction is the process of identifying users before they churn, this is done by implementing methods on collected data in order to find patterns that can be helpful when predicting new churners in the future.The objective of this report is to identify churners with the use of surveys collected from different golfclubs, their members and guests. This was accomplished by testing several different supervised machine learning algorithms in order to find the different classes and to see which supervised algorithms are most suitable for this kind of data.The margin of success was to have a greater accuracy than the percentage of major class in the datasetThe data was processed using label encoding, ONE-hot encoding and principal component analysis and was split into 10 folds, 9 training folds and 1 testing fold ensuring cross validation when iterated 10 times rearranging the test and training folds. Each algorithm processed the training data to create a classifier which was tested on the test data.The classifiers used for the project was K nearest neighbours, Support vector machine, multi-layer perceptron, decision trees and random forest.The different classifiers generally had an accuracy of around 72% and the best classifier which was random forest had an accuracy of 75%. All the classifiers had an accuracy above the margin of success.K-folding, confusion-matrices, classification report and other internal crossvalidation techniques were performed on the the data to ensure the quality of the classifier.The project was a success although there is a strong belief that the bottleneck for the project was the quality of the data in terms of new legislation when collecting and storing data that results in redundant and faulty data. / Churn analys är ett viktigt verktyg för företag då det kan reducera kostnaderna som är relaterade till kund churn. Churn prognoser är processen av att identifiera användare innan de churnas, detta är gjort med implementering av metoder på samlad data för att hitta mönster som är hjälpsamma när framtida användare ska prognoseras. Objektivet med denna rapport är att identifiera churnare med användning av enkäter samlade från golfklubbar och deras kunder och gäster. Det är uppnå att igenom att testa flera olika kontrollerade maskinlärnings algoritmer för att jämföra vilken algoritm som passar bäst. Felmarginalen uppgick till att ha en större träffsäkerhet än procenthalten av den dominanta klassen i datasetet. Datan behandlades med label encoding, ONE-hot encoding och principial komponent analys och delades upp i 10 delar, 9 träning och 1 test del för att säkerställa korsvalidering. Varje algoritm behandlade träningsdatan för att skapa att klassifierare som sedan testades på test datan. Klassifierarna som användes för projekted innefattar K nearest neighbours, Support vector machine, multi-layer perceptron, decision trees och random forest. De olika klassifierarna hade en generell träffssäkerhet omkring 72%, där den bästa var random forest med en träffssäkerhet på 75%. Alla klassifierare hade en träffsäkerhet än den felmarginal som st¨alldes. K-folding, confusion matrices, classification report och andra interna korsvaliderings tekniker användes för att säkerställa kvaliteten på klassifieraren. Projektet var lyckat, men det finns misstanke om att flaskhalsen för projektet låg inom kvaliteten på datan med hänsyn på villkor för ny lagstiftning vid insamling och lagring av data som leder till överflödiga och felaktiga uppgifter.

High prepaid subscriber churn impacts on the service provider's profitability, financial evaluation and resource utilisation. Simultaneously it deprives subscribers of improved service because service providers are committing resources to subscriber acquisition and the management of subscriber retention instead of committing these resources to improving the value propositions offered to subscribers. A prepaid churn rate of just less than 50% in South Africa (2009) highlights the need for research into the factors that influence churned prepaid subscribers' choice of mobile-service provider. This in turn will increase the knowledge of retention and acquisition of prepaid subscribers. Using a telephonic survey on a sample of 861 prepaid subscribers, quantitative research was conducted to determine those factors that churned prepaid subscribers consider important when choosing a mobile-service provider. By making use of Analysis of Variance 4 out of 11 factors that, prepaid subscribers considered very important were identified when choosing a mobile-service provider. These included, in order of importance, Customer service quality, Mobile tariffs, Prepaid airtime and Starter-pack availability and Promotions. Discriminant Analysis highlighted 9 factors to be used to predict and classify groups of subscribers based on average monthly spend. The discriminate equation coefficients highlighted how these two groups of subscribers view the 9 factors when choosing a mobile-service provider. / Dissertation (MBA)--University of Pretoria, 2011. / Gordon Institute of Business Science (GIBS) / unrestricted

Recent research has focused attention on the concerns of migration in and out of Florida and within the counties themselves. In 1949, Cape Canaveral was established and the boom was on. The character of the state dramatically transformed after 1965, when plans were announced to convert twenty-seven thousand acres of swampland into Walt Disney World. Since then, Orlando's evolution is divided into two eras: before and after Walt Disney World. Orlando has changed from a quiet town whose function was to service the surrounding citrus growing regions in a sparsely populated Orange County to a booming metropolis. Has the growth been for the best? While geographical mobility is frequently analyzed in terms of in-migration, out-migration, and net migration, this thesis will examine the population churn, the sum of in- and out-migration divided by population size. The simple descriptive questions in this thesis are, first, how do Orange County and the Orlando metro area "stack up" against other Florida cities, counties, and metro areas such as: Tampa, Jacksonville, and Miami. Secondly, across 67 Florida counties, what county level characteristics predict the rate of churn? The sample will consist of intra-migration and intermigration movers from a dataset drawn from the 2000 U. S. Census, IRS data, and local data by county, such as, F Cat, Index Crime Rate, and Domestic Violence Rate. The U.S. Census data are compiled from the Census of 2000; most estimates come from data collected by the CPS (Current Population Survey), which the U.S. Census conducts. The Internal Revenue Service migration flow data shows migration patterns by county based on changes in the addresses entered on individual tax returns. Correlation analysis is used to show the strength of association between population churn and the other variables.

O aumento da competição global tem aumentado os custos associados à atração de novos consumidores, impondo às empresas o desafio de mudar sua forma de atuação perante seus exigentes consumidores a fim de mantê-los. Diante desse desafio, este trabalho visa aprofundar o estudo do relacionamento entre a empresa e o cliente, identificando em que consiste o gerenciamento de churn e seu papel para a melhoria de ações de marketing para reter clientes. No intuito de alcançar o objetivo proposto, realizou-se uma pesquisa bibliográfica sobre o assunto, seguida de uma pesquisa de campo com abordagem qualitativa do tipo exploratória a partir de estudos de casos múltiplos em organizações de serviços do setor de telecomunicações no Brasil. A pesquisa de campo foi norteada pelo protocolo que abordou, entre outros pontos, os critérios de escolha dos casos, o roteiro de entrevistas e a forma de análise dos dados coletados. A escolha do setor foi motivada tanto por sua representatividade em nível nacional e internacional, quanto pelas mudanças que vem enfrentando na sua estrutura de competição, principalmente após os processos de privatização. Além disso, a indústria de telecomunicações é especialmente rica para este estudo, visto que suas empresas estão especialmente voltadas ao gerenciamento do churn. Os resultados obtidos ajudaram a compreender o processo de gerenciamento de churn, como este está inserido na gestão das empresas e suas aplicações. Nota-se seu papel no auxilio à identificação dos consumidores mais propensos a abandonar a empresa, assim como daqueles que ela deseja atrair e reter para ser capaz de desenvolver práticas eficientes e lucrativas. As limitações deste trabalho são fundamentalmente associadas à metodologia da pesquisa de campo. Além disso, colocam-se como possibilidades para desdobramentos futuros a condução de pesquisas quantitativas que visem testar, mensurar e avaliar os resultados do gerenciamento e pesquisas para compreender o impacto ambiental em suas práticas e resultados. / The rise in global competition has increased costs related to attracting new consumers, bringing companies the challenge of changing their behavior towards their ever more demanding clients in order to keep them. To assist in this challenge, this paper aims to deepen the studies regarding the company and the client, identifying what is considered churn management and its role to improve marketing actions to capture clients. With the aim of achieving the proposed goal, a bibliographic research was conducted as well as a qualitative field research in the exploratory type, which through multiple case studies, in organizations of the telecommunications sector, within Brazilian context. The field research was directed by a protocol and approached the criteria to choose the cases to be studied, the interviewing script and the form of analysis of the information gathered. The choice for this sector was driven for its national and international representation as well as for the changes the sector has been undergoing especially after its privatization. Moreover, the sector is specially recommended for the study as its companies are especially concerned with churn management. The obtained results helped understand the churn management process and how this is input in business administration and its applications. We can note its role in helping to identify consumers who are more likely to abandon the company and to identify the consumers the company wishes to attract and capture to be able to develop the necessary actions. The limitations of this paper are relative to the methodology of the field research. Besides this, conducting quantitative research which aims to test, measure and evaluate the results of management as well as to comprehend the environmental impact, the business model in practice and its results is considered for future studies.

Abstract As deregulation and new competitors open up the telecommunications industry, the cellular phone market has become more competitive than ever. To survive or maintain an advantage in such a competitive marketplace, many telecommunications companies are turning to data mining techniques to resolve such challenging issues as fraud detection, customer retention, and prospect profiling. In this thesis, we focused on developing and applying data mining technique to support the churn prediction. Constrained by limited customer profiles and general demographics, the proposed approach applied a decision tree induction technique (i.e., C4.5) to discover a classification model for churn predication solely based on the call records. To deal with the training data with a highly skewed distribution on decisions (i.e., around 2% churners and 98% non-churners), a multi-expert strategy was adopted. The empirical results showed that the proposed technique was effective in predicting at-risk cellular phone customers (i.e., potential churners). The proposed technique could identify 50.64% churners by selecting 10.03% of the population, and 68.62% churners by selecting 29.00% of the population.

O aumento da competição global tem aumentado os custos associados à atração de novos consumidores, impondo às empresas o desafio de mudar sua forma de atuação perante seus exigentes consumidores a fim de mantê-los. Diante desse desafio, este trabalho visa aprofundar o estudo do relacionamento entre a empresa e o cliente, identificando em que consiste o gerenciamento de churn e seu papel para a melhoria de ações de marketing para reter clientes. No intuito de alcançar o objetivo proposto, realizou-se uma pesquisa bibliográfica sobre o assunto, seguida de uma pesquisa de campo com abordagem qualitativa do tipo exploratória a partir de estudos de casos múltiplos em organizações de serviços do setor de telecomunicações no Brasil. A pesquisa de campo foi norteada pelo protocolo que abordou, entre outros pontos, os critérios de escolha dos casos, o roteiro de entrevistas e a forma de análise dos dados coletados. A escolha do setor foi motivada tanto por sua representatividade em nível nacional e internacional, quanto pelas mudanças que vem enfrentando na sua estrutura de competição, principalmente após os processos de privatização. Além disso, a indústria de telecomunicações é especialmente rica para este estudo, visto que suas empresas estão especialmente voltadas ao gerenciamento do churn. Os resultados obtidos ajudaram a compreender o processo de gerenciamento de churn, como este está inserido na gestão das empresas e suas aplicações. Nota-se seu papel no auxilio à identificação dos consumidores mais propensos a abandonar a empresa, assim como daqueles que ela deseja atrair e reter para ser capaz de desenvolver práticas eficientes e lucrativas. As limitações deste trabalho são fundamentalmente associadas à metodologia da pesquisa de campo. Além disso, colocam-se como possibilidades para desdobramentos futuros a condução de pesquisas quantitativas que visem testar, mensurar e avaliar os resultados do gerenciamento e pesquisas para compreender o impacto ambiental em suas práticas e resultados. / The rise in global competition has increased costs related to attracting new consumers, bringing companies the challenge of changing their behavior towards their ever more demanding clients in order to keep them. To assist in this challenge, this paper aims to deepen the studies regarding the company and the client, identifying what is considered churn management and its role to improve marketing actions to capture clients. With the aim of achieving the proposed goal, a bibliographic research was conducted as well as a qualitative field research in the exploratory type, which through multiple case studies, in organizations of the telecommunications sector, within Brazilian context. The field research was directed by a protocol and approached the criteria to choose the cases to be studied, the interviewing script and the form of analysis of the information gathered. The choice for this sector was driven for its national and international representation as well as for the changes the sector has been undergoing especially after its privatization. Moreover, the sector is specially recommended for the study as its companies are especially concerned with churn management. The obtained results helped understand the churn management process and how this is input in business administration and its applications. We can note its role in helping to identify consumers who are more likely to abandon the company and to identify the consumers the company wishes to attract and capture to be able to develop the necessary actions. The limitations of this paper are relative to the methodology of the field research. Besides this, conducting quantitative research which aims to test, measure and evaluate the results of management as well as to comprehend the environmental impact, the business model in practice and its results is considered for future studies.