03434ntm a22005057i 4500 000664534 CZ-PrVSE 20200523092500.0 m d cr n|||||||||| 200523s2020 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Sokol, Ondřej ISIS:85564 dis Analýza klientské a produktové báze : Specifika maloobchodních transakčních dat eng Analysis of Client and Product Base : Specifics of Retail Transaction Data Ondřej Sokol 2020 ?? stran : digital, PDF soubor Vedoucí práce: Michal Černý Disertační práce (Ph.D.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2020 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2020 Every retail transaction must be recorded. This means thousands to millions of transaction data rows per day for retail chains. Automatic processing of this data is crucial for the company's competitiveness. The importance of efficient processing using data driven methods -- which minimize the analyst's personal opinion in order to maximize automation -- is increasing. The proposed methods are based on the assumption that there is a large amount of data describing the purchase of a particular product, along with additional information such as baskets, links to a particular customer and his properties, and location and time of purchase.Based on this information, methods are proposed for (1) clustering the products into groups of mutual substitutes, (2) segmentation of customers based on their shopping mission, and (3) estimating the number of unique customers of a~retail chain.Methods are formulated as optimization problems. Their properties are verified by simulation studies, or compared with alternative approaches.All methods are applied to real data from a Czech retail chain.The results show that the presented methods are better or at least comparable with the common used methods. Their main advantage is a high degree of automation resulting in efficiency. The methods proposed are robust and allow to get additional new information that cannot be obtained by other methods. Způsob přístupu: Internet ekonometrie a operační výzkum [obor disert. práce] disertace fd132024 czenas dissertations eczenas Customer Behavior Cluster Analysis Retail Business Analytics Černý, Michal mzk2005275013 ths Kukal, Jaromír opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/72234/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/72234 Hlavní práce https://insis.vse.cz/zp/72234/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/72234/posudek/oponent/65420 Oponentura https://insis.vse.cz/zp/72234/posudek/oponent/65482 Oponentura https://insis.vse.cz/zp/72234/podrobnosti dc:identifier NEPOSILAT VSKP vse72234 200519 72234