Turismaktiviteter till havs har kommit att få ett ökat intresse de senaste åren, där människor har upptäckt fördelen med kryssningsfärjor som transportmedel. De erbjuder ett varierat utbud av aktiviteter och upplevelser ombord, som både privat- och affärsresenärer kan ta del av. Detta omfattar flera kundgrupper med olika behov, vilket innebär att rederierna måste uppfylla kundernas förväntningar och vad de efterfrågar. I nuläget finns det en bred konkurrens på marknaden, där de olika aktörerna försöker skapa en egen nisch genom olika marknadsföringsstrategier i syfte att skapa långsiktiga relationer. Syftet med vår studie är att utreda hur Stockholms tre största rederier, Tallink Silja AB, Viking Line AB och Birka Cruises AB, arbetar för att behålla och vårda sina befintliga resenärer, samt vilka strategier som används för att nå nya kundsegment. Vi har även utgått ifrån kundens perspektiv för att undersöka hur de förhåller sig till företagens produkter och tjänster. Studien baseras på intervjuer med ledningsgruppen på respektive bolag, samt kundundersökningar. Relevanta teorier har valts ut för att analysera hur marknadsföringsstrategier i teorin stämmer överens med verkligheten. Trots att de undersökta kryssningsbolagen erbjuder likartade produkter och tjänster, visade resultatet att företagens affärsidé och varumärke skapade ett specifikt behov hos deras kunder. Detta medförde att företagets marknadsföringsstrategier var utmärkande på individnivå och därmed skapades ingen hög konkurrens mellan de berörda kryssningsbolagen. Samtliga rederier är under utveckling, där de fortfarande arbetar med att ständigt utveckla och anpassa sina kunderbjudanden för att bli ledande aktörer på marknaden. För att åstadkomma detta måste företaget upprätthålla sina imageskapande idéer genom att behålla bra service och erbjuda den kvalité som kunderna efterfrågar.

Bibliografia: p. 48-51 / TCC (especialização em Web Intelligence & Data Analytics) - Centro de Referência em Inteligência Empresarial (Universidade Federal do Rio de Janeiro), Rio de Janeiro, 2015. / O Banco Nacional de Desenvolvimento Econômico e Social (BNDES) é hoje o principal instrumento de financiamento de longo prazo para realização de investimentos em todos os segmentos econômicos no Brasil. Buscando atender a uma parcela crescente do empresariado nacional, nos últimos anos o BNDES tem aumentado a quantidade de operações com micro, pequenas e médias empresas, através dos agentes financeiros parceiros, que analisam e encaminham a solicitação de projeto ao banco. Essa estrutura não permite que o BNDES tenha um contato maior com o cliente final, o que levou o banco a estabelecer vários canais de comunicação de forma a atender as demandas desse público, como Serviço de Informação ao Cidadão (SIC), Central de atendimento, Ouvidoria, portal institucional e etc. A grande quantidade de informações gerada através desses canais está dispersa na organização, o que implica na falta de um repositório central que disponibilize essas informações, fazendo com que o banco não conheça de forma estruturada o seu próprio capital de relacionamento. Neste trabalho, buscou-se relacionar o big data, o capital de relacionamento e a gestão desse capital através da ferramenta tecnológica denominada CRM. O objetivo principal do projeto é integrar as bases com os dados de relacionamento do Banco, através da aplicação do modelo de ecossistema big data, para obter uma visão global de todas as ações de relacionamento realizadas com os clientes e clientes potenciais, com o fim de orientar as ações futuras da instituição. Com a implementação do projeto pretende-se conhecer as interações do cliente com o BNDES, independentemente do canal de comunicação utilizado; oferecer produtos e serviços que se adequem às necessidades do cliente; acompanhar mudanças no perfil e identificar oportunidades de atuação junto aos clientes. Pretende-se também, a partir da base de dados, gerar produtos, tanto internos como externos, e ações inovadoras junto ao cliente. O projeto será implantado por fases, visto que todos os canais de comunicação com o cliente serão integrados ao sistema. Apresentam-se também indicadores para o projeto, uma proposta de governança e uma breve explicação do que será realizado em cada fase do processo de implementação do ecossistema de big data no BNDES. / The National Bank of Development (BNDES) is currently the main long-term financing instrument for investments in all economic sectors in Brazil. Seeking to meet a growing share of the national business, in recent years BNDES has increased the amount of lending to micro, small and medium enterprises through partner financial agents, which analyze and send the financial resource request to the bank. This structure does not allow the BNDES has greater contact with the end customer, which led the bank to establish multiple communication channels to meet the demands of the public, as the Information Service to Citizens (SIC), Call Center, Ombudsman, institutional portal and etc. The large amount of information generated through these channels is dispersed in the organization, which implies the lack of a central repository where this information could be provided, causing the bank does not know their own relationship capital in a structured way. In this study, we relate the big date, the relationship capital and the management of the relationship capital through technological tool called CRM. The main objective of the project is to integrate the bases with relationship data from the Bank, through the application of big data ecosystem model to get an overview of all relationship activities carried out with customers and potential customers, in order to guide future actions of the institution. The implementation of the project aims to meet customer interactions with BNDES, regardless of the communication channel used; offer products and services to answer the customer's needs; monitor changes in the profile and identify performance opportunities with customers. It is also intended, from the database, generate products, both internal and external, and innovative actions with the client. The project will be implemented in stages, as all channels of communication with the client will be integrated into the system. Are also presented indicators for the project, a proposal for governance and a brief explanation of what will be done in each phase of the implementation process of the big data ecosystem in BNDES.

Le football professionnel est devenu une industrie du spectacle audiovisuel dont il tire une partie importante de ses revenus. Cependant, les recettes dites Matchday et les revenus annexes de la billetterie constituent un gisement de croissance important pour les clubs français. Ceux ci devraient pouvoir maitriser les capacités offertes au public du spectacle vivant dans les stades et devenir propriétaires de leurs enceintes en utilisant la technique des baux emphytéotiques. Les politiques de prix variables ou de prix dynamiques conduites dans d’autres secteurs comme les transports, l’hôtellerie ou les centres de loisir sont applicables dans la gestion de la billetterie. La digitalisation de l’offre ouvre de nouvelles perspectives de relation client. Elle améliore la traçabilité des consommateurs et permet de déterminer leur propension optimale à payer. Les solutions de CRM, Customer Relationship Management améliorent la connaissance client et permettent de mieux segmenter l’offre pour mieux adresser les différents publics du stade. Dans une activité fondée sur l’incertitude du résultat mais sur la certitude des coûts de production, les ressources digitales permettent de fidéliser les différentes catégories de fans et d’augmenter le panier moyen. Les clubs français très engagés dans la gestion à court terme ont négligé les outils du pricing et tardent à adopter les solutions digitales qui ont donné des résultats satisfaisants dans des secteurs comparables. Nous formulons des propositions adossées à des expérimentations concrètes pour augmenter les performances de la billetterie dans le secteur de l’industrie du football en France. / Football has become a major industry of entertainment for TV networks and also for companies running football squads. TV rights represent at least 50% of the French clubs incomes. Meanwhile, most of them have disregarded Matchday revenues. For a large majority of them, they don’t own their arenas. Moreover, they play in (too) large stadiums with overcapacities according to average attendances. This is why average prices are below the European average price when we compare French League One with the other major’s championships in Europe. In this field, we suggest long-term leases between public owners and football firms in order to transfer both property and ability to refit arenas and stadiums. In addition, French firms running football clubs have not yet fully used technics of variable prices and dynamic prices. They should also display CRM resources in order to address each segment of costumers, including fans, year ticket holders, walk in customer or families. The target is to hit as close as possible the willingness to pay of each category of customers. We have experienced such policies for Year ticket holders in French third division. Digital resources increase customer insights and sustain cross selling policies increasing revenues as it is done in other comparable sectors such as air transportation, leisure parks, hotels and resorts. We make some suggestions and recommendations to strengthen home revenues in the French professional football League.

The goal of customer support is to help clients achieve maximum value in their services and products. Customer support is the public face of a company, which means that it is important to give the customer a positive experience and live up to customer expectations. Efficient customer support has become more important and studies show that customers who leave a company do so because of poor service. Customers' growing demands for higher quality and easier access to services means that companies must recognize the need to satisfy each customer. It is important that each customer receives the attention required and that customer needs are met quickly and flawlessly. The primary objective for an efficient customer support is to provide quick answers and solutions to achieve customer satisfaction. This master thesis aims to examine how the support and case management process can be improved for smaller software companies with customer support. The thesis deals with four issues: how should the support process be designed in smaller software companies, which important aspects must be considered in the support-handling process, how can a case management system contribute to a better customer support and what is the customer role in the management process. Case company for this thesis has been Medius in Linköping, which is a provider of process-related IT support. Interviews have been conducted with both employees at Medius and customers to Medius. The thesis has resulted in a framework and a recommendation for how efficient customer support should be handled in a small software company. To obtain an efficient customer support it is important that the client knows how the customer support should be contacted and what information is required. It should be possible for the customer to contact the customer support through multiple communication channels. The customer support has to work efficiently internally. It is important to prioritize, escalate and document tasks. Between the customer support and the customer, it is beneficial to have a satisfactory communication with regular feedback. Ultimately, it is also important to regularly measure and evaluate the customer support service in order to maintain efficient customer support. A case management system that supports the business is required for the customer support. The case management system is needed to solve problems faster and to provide the support with an overview of the business. A case management system also acts as a knowledge database with relevant information. This thesis work has combined existing frameworks and theories about customer support. This has been supplemented with interviews in order to adapt the framework to smaller software companies. An efficient customer support is achieved by using the authors' framework and recommendations. / Målet med kundsupport är att hjälpa sina kunder uppnå maximalt värde i deras tjänster och produkter. Kundsupporten är ett företags ansikte utåt, vilket innebär att det är viktigt att ge kunden en positiv upplevelse och leva upp till kundens förväntningar. Effektiv kundsupport har blivit allt viktigare och studier visar att de kunder som lämnar företag gör det på grund av dålig service. Kundernas ökade krav på högre kvalité och enklare tillgång till service har lett till att företag måste inse vikten av att tillfredställa varje enskild kund. Det är viktigt att varje enskild kund erhåller den uppmärksamhet som krävs och att kundens behov tillgodoses snabbt och felfritt. Det primära för en effektiv kundsupport är att ge snabba svar och lösningar för att uppnå kundnöjdhet. Det här examensarbetet syftar till att undersöka hur support- och ärendehanteringsprocessen kan förbättras för mindre mjukvaruföretag med kundsupport. Examensarbetet behandlar fyra frågeställningar: hur bör supportprocessen utformas i ett mindre mjukvaruföretag, vilka viktiga aspekter ska beaktas i supporthanteringsprocessen, betydelsen av ett ärendehanteringssystem samt kundens roll i supporthanteringsprocessen.   Fallföretaget för det här examensarbetet har varit Medius i Linköping som är en leverantör av processrelaterat IT-stöd. Intervjuer har genomförts med såväl anställda på Medius som kunder till Medius. Examensarbetet har resulterat i ett ramverk samt en rekommendation för hur effektiv kundsupport ska hanteras i ett mindre mjukvaruföretag. För att kundsupporten i ett mindre mjukvaruföretag ska fungera effektivt krävs att kunden vet hur kundsupporten ska kontaktas och vilken information som ska tillhandahållas. Det ska vara möjligt för kunden att kontakta kundsupporten via flera olika kommunikationskanaler. Kundsupporten ska i sin tur fungera effektivt internt. Det är viktigt att prioritera, eskalera och dokumentera ärenden på ett korrekt sätt. Mellan kundsupporten och kunden ska det finnas en tillfredställande kommunikation med regelbunden återkoppling. I slutändan är det viktigt att regelbundet mäta och utvärdera kundsupportens servicenivåer för att kunna upprätthålla en effektiv kundsupport. För att kundsupporten ska kunna fungera effektiv internt krävs ett ärendehanteringssystem som stödjer verksamheten. Ett ärendehanteringssystems behövs för att kunna lösa problem snabbare och för att ge supporten en överblick över verksamheten. Ärendehanteringssystemet fungerar också som en kunskapsdatabas med relevant information. Det här examensarbetet har kombinerat befintliga ramverk och teorier kring kundsupport. Detta har kompletterats med intervjuer för att anpassa ramverket till det mindre mjukvaruföretaget. Genom att använda författarnas ramverk och rekommendationer kommer en effektiv kundsupport att erhållas.

The theme of this diploma thesis is an analysis of an enterprise information system in the selected company, middle sized company operating in the construction industry. The work is divided into two separate units. First one - the theoretical part contains the main concepts and issues that are subsequently elaborated in the practical part. Individual chap-ters of the theoretical part of the thesis contain the definition of information system, intro-duces basic concepts in this area, enterprise information systems and related processes and also strategic management of information processes. The practical part of the thesis focuses on the selected company. The goal and output of the practical part are the analyzes of information strategy and current state of the information system of the selected company and its evaluation.

The thesis "Credit risk from Basel II point of view" deals with new capital concept with main focus on the credit risk. The particular emphasis is laid on the chief issue of Basel II concept i.e. internal models. The thesis quite in detail describes the usage of basel parameters - LGD particularly - in various day-to-day business processes of credit institutions. An individual part of the thesis is devoted to credit risk mitigants and their impacts on the amount of capital requirements. The analysis carried out precedent Basel II implementation indicated the launching of Basel II should imply risk weighted assests to credit risk decline. This documents the last chapter.

The subject of my diploma thesis CRM and its application in the company Znovín Znojmo Inc. is analysis of the temporary usage of CRM in the company among other things based on the survey, which results will be used to draft potential improvements. Thesis is divided into six chapter divided into practical and theoretical parts. The theoretical part of thesis describes the marketing and commercial communications, defined CRM as customer relationship management and analyze the economic environment focusing on the Czech wine market. In the practical part is introduced company Znovín Znojmo Inc., is applied SWOT analysis and described marketing communication of company. At the core is the introduction of CRM in the company Znovín Znojmo, survey through customers and then are designed recommendations for improvements.

This diploma work deals with marketing problems of bank services. The theory of marketing bank mix is described in it, creation of marketing campaign and control of relations with clients. The goal is a detection of an embarrassment of marketing methods and campaigns used in Česká spořitelna, then evaluation of this methods and finally making some concept how to solve this situation.

Die Forschung zum Informationsverhalten in Archiven hat wiederholt gezeigt, dass der Zugang zu Archivbeständen durch einen grundlegenden Wissensmangel über die Informationsbedürfnisse von Archivnutzern eingeschränkt wird. Das Ziel der vorliegenden Studie ist die Vertiefung des empirischen Verständnisses der spezifischen Informationsbedürfnisse von Archivnutzern und damit die Leistung eines grundlegenden Beitrags zur Verbesserung von archivischen Informationssystemen. Dazu untersucht die primäre Forschungsfrage die Möglichkeit der Erarbeitung einer Ontologie, die in angemessener Weise das Erkenntnisinteresse von Nutzern an Archive repräsentiert, und auf formale Anfragen, adäquate Antworten erzeugt. Zu diesem Zweck analysiert die Studie schriftliche Nutzeranfragen an das Bundesarchiv und das Nationalarchiv von Norwegen (Arkivverket). Die primären Forschungsergebnisse umfassen einen methodischen Ansatz, der eine interpretative Analyse schriftlich formulierter Fragen an Archive vertritt und, als Ergebnis seiner erfolgreichen Anwendung, das Archival Knowledge Model (AKM) erarbeitet. Das AKM ist eine ontologische Repräsentation des Gegenstandbereichs, der typischerweise als das Erkenntnisinteresse von Fragen an Archiven erscheint. Die Studie zeigt, dass derartige Anfragen dominante, grundlegende ontologische Muster aufweisen, die auf einen relativ kleinen Satz ontologischer Entitäten formalisiert werden können. Das AKM repräsentiert damit formal und explizit die Informationsbedürfnisse von Archivnutzern in Form einer Ontologie. Diese stellt ein konstitutives Modell für die Evaluierung bestehender Archivinformationssysteme und Datenschemata zur Verfügung und kann die Entwicklung neuer Katalogisierungsregeln oder musterbasierter Abfrageanwendungen unterstützen. / Research on the information behaviour of archive users has repeatedly shown that access to archival knowledge bases such as via finding aids is hindered by a certain deficiency in knowledge about users and their information needs. The objective of this study is to increase our empirical understanding of the information needs of archive users in order to facilitate access to archival information systems. The primary research question explores the possibility of creating an ontology that can reasonably represent archival inquiries and their probable interpretations as formal queries to the model of the archival target world that would generate an adequate response. For this purpose, the study analyzes archival information needs as expressed in written natural language questions submitted to the German Federal Archives (Bundesarchiv) and the National Archives of Norway (Arkivverket). The primary results point to a methodological approach that advocates an interpretative analysis of written natural language inquiries and, as the result of its practical and successful application, the Archival Knowledge Model (AKM). This constitutes an ontological representation of the subject matter typically appearing as the interest of archival inquiries. The study thus shows that written natural language questions submitted to archives exhibit dominant fundamental ontological patterns, which can be formalized to a relatively small set of entities utilizing the CIDOC CRM and compatible extensions wherever its semantics are found to be inadequate. The AKM formally and explicitly represents the information needs of archive users in the form of an ontology, thus providing a constitutive model for the evaluation of existing archive information systems and data schemas and may inform the development of new cataloguing rules or pattern-based query applications.

TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. The goal of this research work is to present an ML-based solution that predicts the Resolution Times (RTs) of the TV cases in each TV delivery service type, therefore how long the cases will take to be solved. The approach taken to provide meaningful results consisted in utilizing four Machine Learning (ML) algorithms to create 480 models for each of the two scenarios. The results revealed that Random Forest (RF) and, specially, Gradient Boosting Machine (GBM) performed exceptionally well. Surprisingly, hyperparameter tuning didn’t significantly improve the RT as expected. Some challenges included the initial data preprocessing and some uncertainty in hyperparameter tuning approaches. Thanks to these predicted times, the company is now able to better inform their costumers on how long the problem is expected to last until is resolved. This real case scenario also considers how the company processes the available data and manages the problem. The research work consists in, first, a literature review on the prediction of RT of Trouble Ticket (TT) and customer churn in telecommunication companies, as well as the study of the company’s available data for the problem. Later, the research focuses in analysing the provided dataset for the experimentation, the preprocessing of the this data according to the industry standards and, finally, the predictions and analysis of the obtained performance metrics. The proposed solution is designed to offer an improved resolution for the company’s specified task. Future work could involve increasing the number of TV cases per service for improving the results and exploring the link between resolution times and customer churn decisions. / TV-distribution och leverans av strömningsinnehåll via internet består av komplexa nätverk, inklusive CDNs, kablar och slutanvändarutrustning. Detta gör det känsligt för problem på olika nätverksnivåer som kan påverka slutkundens TV-tjänster. När ett problem påverkar kunden och hindrar en korrekt TV-leveranstjänst rapporteras det genom ett samtal. Ett ärende öppnas, och företagets kundhanteringsagenter övervakar det för att lösa problemet så snabbt som möjligt. Målet med detta forskningsarbete är att presentera en maskininlärningsbaserad lösning som förutsäger löstiderna (RTs) för TV-ärenden inom varje TV-leveranstjänsttyp, det vill säga hur lång tid ärendena kommer att ta att lösa. För att få meningsfulla resultat användes fyra maskininlärningsalgoritmer för att skapa 480 modeller för var och en av de två scenarierna. Resultaten visade att Random Forest (RF) och framför allt Gradient Boosting Machine (GBM) presterade exceptionellt bra. Överraskande nog förbättrade inte finjusteringen av hyperparametrar RT som förväntat. Vissa utmaningar inkluderade den initiala dataförbehandlingen och osäkerhet i metoder för hyperparametertuning. Tack vare dessa förutsagda tider kan företaget nu bättre informera sina kunder om hur länge problemet förväntas vara olöst. Denna verkliga fallstudie tar också hänsyn till hur företaget hanterar tillgängliga data och problemet. Forskningsarbetet börjar med en litteraturgenomgång om förutsägelse av RT för Trouble Ticket (TT) och kundavhopp inom telekommunikationsföretag samt studier av företagets tillgängliga data för problemet. Därefter fokuserar forskningen på att analysera den tillhandahållna datamängden för experiment, förbehandling av datan enligt branschstandarder och till sist förutsägelser och analys av de erhållna prestandamätvärdena. Den föreslagna lösningen är utformad för att erbjuda en förbättrad lösning för företagets angivna uppgift. Framtida arbete kan innebära att öka antalet TV-ärenden per tjänst för att förbättra resultaten och utforska sambandet mellan löstider och kundavhoppbeslut.