Aplikace statistických metod při výpočtu celoživotní hodnoty zákazníka

This bachelor thesis pay attention on statistical methods managing relationship with customers and different approaches of estimation customer lifetime value for the company in long time period. It is an empirical type of bachelor thesis, where we will test the theoretical assumptions on the real data. During this paper we research and measure customers behavior in order to obtain quantitative outputs to adaptation marketing strategy, efficient allocation of resources and choosing key clients. On the basis of past and present behavior we simulate expected in future level of purchasing behavior and thus try to determine the most profitable target groups for high-quality application of marketing tools. Main purposes of thesis are describing various attitudes to modeling CLV, applying the model Pareto/NBD on real date of the company Práce pro Vás, to evaluate forecast applicability in practice. Following tasks will be resolved in this paper: to introduce advantages and disadvantages of each modeling CLV approach, to evaluate quality of Pareto/NBD model and to determine the advanced extensions of the research in this issue. There are various attitudes to estimation of CLV, which are described in theoretical chapters, but practical part of this paper focuses primarily on application of probability model Pareto/NBD. With the help of Pareto/NBD managers can get the information about future customers activity, i.e. expected number of transactions from real behavior a probability that customer will be active in observation period. In nowadays reality of overloaded market, almost in every business sector, every company should rely on quantitative base of marketing and choose target clients, on which to focus their marketing efforts. Exactly this need matches with described and applied in this bachelor thesis model Pareto/NBD, with it help we will estimate customer lifetime value for strategic decisions and managing relationship with customers. Finally, we will resolve continuous tasks and will achieve all the determined goals.