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1	Analytické CRM v bankovnictví / Analytical CRM in banking Nebřenský, Aleš January 2008 (has links) The thesis studies the topic of Business Intelligence applications specialized to enhance the analytical, planning and control capabilities of commercial banks in areas such as marketing, sales and customer care. The goal of the diploma work is to give a complex view on analytical CRM in the context of banking industry, to analyze the solution from different perspectives and to design functions, processes and data corresponding to a business model of commercial banking. The theoretical part of the work investigates the customer relationship management strategy, general principles of relationship marketing, current situation in the area of Customer Intelligence and keystones of IS/ICT applications which are applicable to implement the CRM strategy. The following chapters deal with the actual development in Czech banking industry, banking activities and IS/ICT application architecture in the context of banking industry. The main part of the work is focused on analysis and design of functions, processes and data of analytical CRM in the context of banking industry. The results of the analysis suggest implementing a propensity to buy model as an analytical CRM function applicable to manage customer acquisition and customer selection for direct marketing campaigns. Similarly, a function providing the probability of customer churn can be of great value for activities aimed at customer retention. The thesis contributes to the existing literature by designing input variables for propensity to buy modeling, customer retention modeling and customer segmentation. Additionally, the work introduces process models which define the main steps of data analysis and also the performance metrics for these processes. Finally, the part dedicated to data principles of analytical CRM contributes by designing key customer data aggregations and by analyzing different possibilities of data layer integration within the IS/ICT architecture of commercial banks.
2	Binary classification for predicting propensity to buy flight tickets. : A study on whether binary classification can be used to predict Scandinavian Airlines customers’ propensity to buy a flight ticket within the next seven days. / Svensk titel: Binär klassificering applicerat på att prediktera benägenhet att köpa flygbiljetter. Andersson, Martin, Mazouch, Marcus January 2019 (has links) A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics and search history is showed to be insignificant. / En kunds benägenhet att göra ett visst köp är ett allmänt undersökt område som applicerats i flera olika branscher. I den här studien visas det att statistiska binära klassificeringsmodeller kan användas för att prediktera Scandinavian Airlines kunders benägenhet att köpa en resa de kommande sju dagarna. En jämförelse är presenterad mellan logistisk regression och stödvektormaskin och logistisk regression med reducerat antal parametrar väljs som den slutgiltiga modellen tack vare sin enkelhet och träffsäkerhet. De förklarande variablerna är uteslutande bokningshistorik medan kundens demografi och sökdata visas vara insignifikant. statistics classification machine learning logistic regression support vector machine rbf significance prediction propensity to buy flight tickets ai artificiell intelligens walds test sas scandinavian airlines statistik klassificering maskininlärning logistic regression support vector machine rbf signifikans walds test prediktion benägenhet att köpa flight biljett flyg ai artificial intelligence sas scandinavian airlines Probability Theory and Statistics Sannolikhetsteori och statistik

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Analytické CRM v bankovnictví / Analytical CRM in banking