This study examined the customer asset management and the relationship between various constructs and firm characteristics on customer lifetime value(CLV).The relationship between marketing actions such as loyalty programs and the level of commitment and specifically the type of commitment and the type of loyalty that may be influenced by such a program were investigated.The main focus of the study was on the relationship between commitment and loyalty.Additional investigations were done on the impact that this may have on customer lifetime value.In terms of commitment,many researchers regard this as an important antecedent to customer retention but there have been conflicting or ambiguous empirical findings from various studies.In terms of loyalty ,many studies have similarly found that this concept is necessary for retention as well.This study examined the effects of the two dimensions of commitment on the two dimensions of loyalty.A survey was administered and a sample of 152 informants was analyzed using SEM with PLS-Graph 3.0 Build 1130 for inferential analysis and SPSS version 16.0 for descriptive analysis.The results show a significant relationship between affective commitment and attitudinal loyalty and behavioral loyalty and that continuance commitment is not significantly related to loyalty.In addition,the results indicate that affective commitment has a greater impact on loyalty than calculative commitment;however there was no significant relationship between attitudinal loyalty and CLV or between behavioral loyalty and CLV.

The fact that many banks today target students with concessional deals is no news. Students are a coveted group at the financial institutions, above all because they will most likely have a secure and well paid occupancy after they have finished their studies. This study will show the importance of banks attracting the students as customers and that the students will continue being customers even after having finalised their studies. It will also show that the banks market themselves towards the students as if students were a homogenous group as well as proving the benefits of calculating a student’s Customer Lifetime Value (CLV). The study is based on research articles within the subject, one interview with the CEO at one of the banks in Sweden and two surveys that were sent out to 10 000 people that are either part of a current student deal at a bank or has been. The result shows that the bank will increase its long-­‐term profitability if it has more students in the customer base. Given that the students remain as customers of the bank after their studies are finished. The results also show the significance of dividing the group "students" based on chosen variables depending on the banks objective and CLV. From this it is concluded that it is less expensive reaching out to the academic meritorious customers in an early stage then to obtain these customers hindsight. / Att många banker riktar sig mot studenter med förmånliga erbjudanden är ingen nyhet. Studenter  är  en  eftertraktad  målgrupp  hos  de  finansiella  institutionerna,  framför  allt eftersom chansen är stor att studenter efter studierna kommer att få välbetalda jobb. Den  här  studien  kommer  att  visa  vikten  av  att  banker  attraherar  studenter  som bankkunder och att studenter fortsätter att vara bankkunder efter avslutade studier. Den kommer även visa att banker marknadsför sig mot alla studenter som en homogen målgrupp, samt fördelarna med att räkna ut en students Customer Lifetime Value (CLV). Underlaget till studien är forskningsartiklar och rapporter inom ämnet, en intervju med en VD för en svensk bank och två enkäter som skickats ut till 10 000 personer som antingen är med i ett studenterbjudande hos en bank eller har varit det. Resultaten visar att  banker  skulle  öka  sin  långsiktiga  lönsamhet  om  de  hade  fler  studenter  som bankkunder, förutsatt att de stannar kvar som kunder efter avslutade studier. Resultatet visar även  betydelsen av  att  dela upp  studenterna i  mindre delsegment efter valda variabler beroende på bankens målsättning och CLV. Utifrån detta dras slutsatsen att det är mindre kostsamt att nå ut till de akademiskt meriterade kunderna i ett tidigt skede än att erhålla dessa kunder i efterhand.

[pt] Perdendo em média mais de 20 por cento da base de alunos todo semestre, a evasão de alunos no ensino superior privado representa um desafio para a gestão dessas instituições. Diferentes abordagens são utilizadas para combater este problema. Para a gestão de marketing de retenção, a identificação dos alunos é o primeiro passo necessário para aplicar uma estratégia de interação personalizada. Nesse sentido, este trabalho apresenta uma metodologia quantitativa para classificação de risco de evasão de alunos ativos. Baseado em dados históricos de alunos que evadiram ou se formaram, modelos gerados por algoritmos de machine learning foram calculados e comparados e, na sequência, utilizados para classificar alunos ativos. Por fim, estimou-se o lifetime value desses alunos para auxiliar na definição de estratégias de retenção. / [en] Losing more than 20 percent of its students each semester, the student attrition in private graduation courses challenges its institutions management. Different approaches to address this problem have been used. To retention marketing management the identification of students is the first necessary step to apply a personalized interaction strategy. In this sense, this work uses a quantitative methodology to classify its students by risk of attrition. Based in historic data of former students of an institution, models were generated by machine learning algorithms and its results compared. Then they were used to classify active students in the educational institution. Afterwards, their lifetime value were estimated in order to help in the definition of retention strategies.

Managers and researchers have become increasingly interested in linking marketing activities to firm financial performance. That is, they desire to make marketing more financially accountable. One approach to achieving this goal has been to “valuate” customers to determine their degrees of profitability over the lifetime of their relationships with firms. However, traditional customer valuation techniques are largely based on quantitative factors and do not account for softer measures such as a customer’s behavior and performance both during and after service encounters. Additionally, while customer profitability is commonly valuated, employees are not generally assessed in this manner in profit linkage frameworks. This indicates that employee factors have not been deemed to have an equivalent, direct impact on the bottom line. Instead, if included at all, employee factors have mainly been positioned as antecedents to customer factors in past linkage models. Because both customers and employees play essential roles in determining the success of service encounters, both customer and employee factors should be fully considered before profitability is determined. In this dissertation, an innovative theoretical model is presented in which past profit linkage research is extended to include nonfinancial considerations. This research merges traditional financial valuation methods with nonfinancial metrics to assess organizational performance. Furthermore, a conceptually parallel framework is developed in which both employee and customer factors are hypothesized as links through which service encounter dynamics can be connected to firm financial performance. This research examines the linkages between service interactions, customer and employee outcomes, and overall financial performance. Within the contexts of two studies, the overall structural model is dissected into comparable performance models and examined within the retail banking and computer services industries. The overall empirical findings provide some evidence of a positive flow of interconnected relationships between service encounter dynamics and firm financial performance. Accordingly, this research presents some indication of the importance of service encounters as antecedents to outcome behaviors that have critical financial consequences.

Ingeniero Civil Industrial / En el mundo competitivo de hoy, el conocimiento de los clientes puede transformarse en una ventaja para las empresas. Lo anterior se debe a que cada individuo es diferente y pueden presentar distintos comportamientos, existiendo algunos que son más rentables que otros, por lo que detectarlos y enfocarse en los clientes correctos representa potenciales ganancias a futuro. En base a lo anterior, en este proyecto se propone el desarrollo de una metodología de valoración de clientes de una importante empresa del sector automotriz, específicamente en el subsector de camiones medianos de una de las marcas que representa. El método propuesto tiene como objetivo apoyar a las áreas comerciales a focalizar la retención y fidelización de los clientes más valiosos mediante la generación de recomendaciones de distintos tipos de acciones de marketing a enfocar en diferentes grupos de clientes para así mejorar su gestión. Lo anterior implica la estimación del valor futuro de los clientes, para lo cual se utiliza la métrica de CLV (Customer Lifetime Value). Para estimarla, se proponen 2 modelos ampliamente utilizados en distintas industrias para la estimación del número de transacciones: Uno probabilístico (BG-NBD) y uno econométrico (Logit-Poisson-Markov). Por otro lado, para la estimación de los montos se utiliza el modelo probabilístico Gamma-Gamma. Las métricas de ajuste utilizadas para validar los modelos indican que el modelo econométrico es el que presenta el mejor desempeño para la estimación del número de transacciones, el cual se utiliza en conjunto con el modelo probabilístico que estima los montos para así proyectar el valor futuro de los clientes. Utilizando el valor histórico generado por los clientes y su valor proyectado para el año actual y para un plazo de 5 años (utilizando el modelo desarrollado) se propone una agrupación de clientes en base a estas 3 variables. A partir de la agrupación propuesta se realizan recomendaciones de acciones de marketing a los distintos grupos generados, logrando así apoyar a las áreas comerciales a la focalización de los esfuerzos a realizar con la cartera de clientes. Los clientes más valiosos para el plazo de 5 años utilizados resultan ser los clientes tipo empresa que se desempeñan en el rubro "R2" y que además de tener vehículos medianos poseen vehículos livianos y/o pesados dentro de la misma marca. Estos representan un valor promedio de $ 101.522.185 en el plazo señalado. El modelo de valoración y su utilización propuesta significan el punto de partida para la empresa en la búsqueda de un enfoque relacional, que busca comprender, mejorar y aumentar las relaciones que posee actualmente con su cartera de clientes.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-04-08T12:07:56Z No. of bitstreams: 1 Samuel Ongaratto.pdf: 1337304 bytes, checksum: 14198512c9cbcad30e81483b17403288 (MD5) / Made available in DSpace on 2015-04-08T12:07:56Z (GMT). No. of bitstreams: 1 Samuel Ongaratto.pdf: 1337304 bytes, checksum: 14198512c9cbcad30e81483b17403288 (MD5) Previous issue date: 2010-08-20 / Nenhuma / O objetivo deste estudo é ajudar as empresas na tomada de decisão com relação à base de clientes e ajuste de suas promoções de mercado num contexto de risco de crédito comercial. O resultado da pesquisa é a proposição de um novo modelo. Como contribuições teóricas, pode ser citado o desenvolvimento de um modelo de risco de crédito capaz de estimar um risco de inadimplência para cada pagamento efetuado por um cliente. Isso difere dos modelos encontrados na literatura, que estimam apenas um risco para cada cliente. Outra contribuição é o desenvolvimento de um modelo baseado na métrica de Customer Lifetime Value com componentes inéditos (assimetria entre prazos de pagamento e recebimento e risco de crédito). Esta pesquisa é dividida em três fases distintas: uma fase exploratória, resultado de uma pesquisa realizada na literatura em busca de conceitos e elementos alinhados ao objetivo; a segunda é a proposição do método e do modelo propriamente ditos, e a terceira e última fase foi a aplicação do modelo a um estudo de campo, o qual utilizou dados de 14.259 faturas e 229 clientes. Os dados são de dezembro de 2007 a agosto de 2009. O modelo de risco de crédito integrado ao modelo proposto classifica as faturas pagas com 75,52% de assertividade média. Os resultados do estudo de campo ajudaram a empresa estudada a realizar uma série de mudanças na sua base de clientes, resultando com essas medidas num ganho estimado de mais de R$ 2,5 milhões para 2010. / The objective of this research is to help companies in decision making regarding the customer base and adjust their marketing promotions in the context of commercial credit risk. The result of this research is to propose a new model. As theoretical contributions can be mentioned the development of a model of credit risk can estimate a default risk for each payment made by a client. This differs from the other models in the literature that estimate only one risk for each client. Another contribution is the development of a model based on metrics of Customer Lifetime Value with components unpublished (asymmetry between receiving and payment terms and credit risk). This research is divided into three distinct phases: an exploratory phase, where it performed a literature review in search of concepts and elements aligned to the goal. The second phase is the proposition of the method and the model itself. The third and final phase was the implementation of the model to a field study. The field study used data from 14 259 bills and 229 customers. Data are from December 2007 to August 2009. The model of credit risk built into the proposed model classifies invoices paid on average 75.52% of assertiveness. The results of the field helped the company studied conducting a series of changes in its customer base. Changes made resulting in an estimated gain of more than R$ 2.5 million in 2010.

A gestão de clientes é um processo que envolve a tomada de decisões estratégicas, que influenciam a composição do portfólio de clientes da companhia, e operacionais, que afetam o relacionamento dos clientes com a empresa no dia a dia. O framework sugerido nesta tese propicia a integração dessas duas perspectivas, permitindo aos gestores alocarem melhor os recursos de marketing, por possibilitarem (a) o incremento da eficiência da carteira de clientes, a partir da sua otimização, e (b) a identificação dos clientes mais propensos a gerarem lucros futuros, com base na modelagem de customer lifetime value (CLV) desenvolvida. A abordagem de otimização do portfólio de clientes foi elaborada para auxiliar os gestores a definirem os segmentos que devem ser alvo dos investimentos de marketing e tem como objetivo indicar a composição da carteira de clientes que proporcionará a rentabilidade, a diversificação do risco e a lucratividade desejadas pelos acionistas. A abordagem sugerida é uma adaptação para o marketing da teoria financeira do portfólio. Foram incluídas restrições específicas para a área de gestão de clientes que asseguram a exequibilidade dos portfólios recomendados, tanto em relação à necessidade de aquisição de clientes ou de redução da participação dos segmentos na carteira, quanto em relação à manutenção da lucratividade da empresa. Ademais, foram incorporadas opções de estimação do retorno, tais como a inclusão da tendência à série com base na modelagem SUR, além de serem avaliadas a utilização de duas proxies para o risco, a variância e o Conditional Value at Risk. De acordo com o framework de gestão de clientes proposto, a implementação das decisões estratégicas é viabilizada a partir da integração da análise dos resultados obtidos pela otimização com a avaliação proporcionada pelo modelo de CLV sugerido. Este, além de englobar a evolução do comportamento do cliente ao longo do relacionamento da empresa, considera o retorno e a matriz de probabilidade de troca de segmento de maneira individualizada. A heterogeneidade da matriz de Markov foi alcançada a partir da combinação convexa da matriz de transição geral com a matriz personalizada de cada cliente, possibilitando, assim, a priorização de clientes pertencentes a um mesmo segmento. O framework sugerido foi aplicado na base de clientes de uma grande empresa que atua nacionalmente na indústria de serviços financeiros. Após a constatação de que os segmentos podem gerar diferentes retornos e representar distintos níveis de risco para a companhia, foi feita a comparação dos resultados dos portfólios recomendados com o realizado. Os portfólios sugeridos desempenharam melhor de maneira consistente em termos de lucratividade e de eficiência, medida a partir do sharpe ratio. Em relação ao modelo de CLV, os resultados foram comparados com os obtidos a partir do modelo de Pfeifer & Carraway (2000), utilizado como ponto de partida para o seu desenvolvimento. As modificações incorporadas, além de possibilitarem a individualização por cliente, aumentaram a precisão da previsão dos valores individuais e a qualidade do ordenamento, mantendo a capacidade de avaliação do valor da base. Para resumir, foi proposto um framework de gestão de clientes que inclui a avaliação do risco, possibilitando aos gestores uma visão holística do negócio e particular de cada cliente. / Customer management is a process that involves strategic decision-making, which influence the composition of the customer portfolio, and operational decision making, which affect the relationship of each customer with the company. The proposed framework provides the integration of the strategic and operational perspectives, empowering managers to better allocate marketing resources as it enables (a) the increase of the efficiency of the customer portfolio, through its optimization, and (b) the identification of the customers that are more likely to bring profit in the future, through the customer lifetime value (CLV) model developed. The customer portfolio optimization method was built to help managers to define the customer segments that should be the target of their marketing investments. Its purpose is to indicate the customer portfolio composition that will provide the return, profitability and risk diversification desired by shareholders. The suggested approach is an adaptation to marketing of financial portfolio theory. In this way, customer management specific constrains were included to ensure the applicability of the recommended portfolios in terms of either the necessity of acquiring new customers or reducing the importance of a given segment in the portfolio as well as in terms of maintaining the company’s profitability. Furthermore, options of estimating return were incorporated such as the inclusion of the trend in the time series based SUR modeling as well as the optimizations were evaluated considering two proxies for risk, variance and Conditional Value at Risk. According to the proposed framework, the implementation of the strategic decisions concerning the changes needed in the customer portfolio become possible through the integration of the results of the optimization with the estimation of the value of each customer provided by the CLV model developed. In this model, besides accounting for the evolution of the customer behavior throughout the duration of his relationship with the company, we also consider, for each customer, his individual return and his individual transition matrix. The heterogeneity of the Markov matrix was reached with a convex combination of the general transition matrix and the personalized matrix of each customer. It, therefore, enables managers to priorize customers of the same segment. The suggested framework was applied to the customer database of a large national company from the financial services industry. Once evidenced that the customer segments can generate different returns and can have different levels of risk for the company, we compared the results of the recommended with the current. The portfolios suggested by the optimization performed consistently better in terms of profitability and efficiency, measured through sharpe ratio. Concerning the CLV model developed, we compared the results with Pfeifer & Carraway (2000) model, which was used as the start point for our model. The improvements implemented not only allowed the estimation of CLV at the individual level, but also increased the precision of the predictions for the customer lifetime values and for the customer ranking, maintaining the quality of the customer equity forecast. To sum up, our proposed framework which includes risk assessment enables marketing managers to have a holistic vision of their customer portfolio and to drilldown into a particular vision of each customer.

Sensemaking is often associated with processing large or complex amount of data obtained from diverse and distributed sources. Sensemaking enables leaders to have a better grasp of what the data represents and what insights they can get from it. Thus, sensemaking is considered extremely important in mature markets where the competition is fierce. To-date, the research base on sensemaking has not moved far from the conceptual realm, however. In response, this research provides a conceptual framework that explains the core processes of sensemaking - noticing, interpretation and action - and examines how emerging technologies such as Social Network Analysis (SNA) and Machine Learning (ML) techniques help to enhance the human sensemaking process in generating valuable insights during data analysis. Design Science Research (DSR) is adopted as a research methodology in the context of financial transactional data analysis, aiming to make sense of the data while exploring conceptions of customer value for a mainstream commercial bank alongside the perceived need for banking products. Three analytical models are introduced, examining Connected Customer Lifetime Value (CCLV), Network Relationship Equity (NRE) and product purchasing frequency based on customer 'personas'. The former models employ SNA techniques in providing novelty, the latter combines the outcomes of SNA with ML clustering algorithms to provide a base on which product holdings and purchase frequency analysis are overlaid - providing a novel form of recommendation. Ongoing evaluation of the developed models is used to explore the nuances of the sensemaking process and the ability of such models to support that process (in the given domain).

<p>Varje dag använder sig miljontals svenskar av någon form av medlems- eller kundklubbskort när de handlar i butik, kontaktar en kundtjäst eller loggar in på ett företags hemsida. Motiven till detta kan förstås vara olika - det kan vara smidigt, lönsamt eller nödvändigt för att överhuvudtaget få den hjälp och service man önskar. För företagen är denna registrering å andra sidan ett effektivt sätt att samla information om sina kunder som ett led i deras lojalitetsskapande arbete mot kund. Tidigare, internationella studier av CRM visar dock på att företagen inte utnyttjar den information de har om kunder för att verkligen styra verksamheten.</p><p>Syftet med denna uppsats är att studera om detta är ett aktuellt problem även bland svenska företag genom en enkätundersökning riktad till CRM- och kundklubbsansvariga vid svenska företag. Denna undersökning har utarbetats utifrån Cuthbertsons tre kriterier för att avgöra om en organisation är kundorienterade eller ej.</p><p>Resultat visar att de flesta företag som deltog i studien inte använder informationen man samlar in från kunderna i någon större utsträckning. Däremot visar resulataten att företag med äldre kundklubbar samt med höga medlemsantal generellt är bättre på att sprida och använda den kunskap som kundklubben samlar in. Skälen till att kundinformation inte används i större utsträckning beror enligt vår analys på frånvaron av fungerande intern infrastrauktur för att sprida inhämtad kunddata, kundklubben har för få medlemmar och låg ålder vilket påverkar dess interna status samt att kundklubben främst betraktas som ett register för riktad marknadsföring snarare än som ett redskap för att styra företagens verksamhet i stort.</p>

Varje dag använder sig miljontals svenskar av någon form av medlems- eller kundklubbskort när de handlar i butik, kontaktar en kundtjäst eller loggar in på ett företags hemsida. Motiven till detta kan förstås vara olika - det kan vara smidigt, lönsamt eller nödvändigt för att överhuvudtaget få den hjälp och service man önskar. För företagen är denna registrering å andra sidan ett effektivt sätt att samla information om sina kunder som ett led i deras lojalitetsskapande arbete mot kund. Tidigare, internationella studier av CRM visar dock på att företagen inte utnyttjar den information de har om kunder för att verkligen styra verksamheten. Syftet med denna uppsats är att studera om detta är ett aktuellt problem även bland svenska företag genom en enkätundersökning riktad till CRM- och kundklubbsansvariga vid svenska företag. Denna undersökning har utarbetats utifrån Cuthbertsons tre kriterier för att avgöra om en organisation är kundorienterade eller ej. Resultat visar att de flesta företag som deltog i studien inte använder informationen man samlar in från kunderna i någon större utsträckning. Däremot visar resulataten att företag med äldre kundklubbar samt med höga medlemsantal generellt är bättre på att sprida och använda den kunskap som kundklubben samlar in. Skälen till att kundinformation inte används i större utsträckning beror enligt vår analys på frånvaron av fungerande intern infrastrauktur för att sprida inhämtad kunddata, kundklubben har för få medlemmar och låg ålder vilket påverkar dess interna status samt att kundklubben främst betraktas som ett register för riktad marknadsföring snarare än som ett redskap för att styra företagens verksamhet i stort.