03999ntm a22005177i 4500 000681347 CZ-PrVSE 20210206111302.0 m d cr n|||||||||| 210206s2020 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Veverka, Lukáš ISIS:118820 dis Ekonometrická analýza efektu TV reklam na přirozenou webovou návštěvnost eng Econometric analysis of the effect of TV advertisements on organic webpage visits / Lukáš Veverka 2020 ?? stran : digital, PDF soubor Vedoucí práce: Vladimír Holý Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2021 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2021 Do people react to TV ads or do they just watch them? To answer that, data about organic webpage visits with a minute frequency from Google Analytics and data about TV spots from Nielsen is combined. Since the webpage visits have a strong diurnal pattern, it is decomposed by Kernel smoothing and the residuals are passed into the extraction of significant deviations caused by ads. Since ads, in general, have a lagged effect, the time series have to be treated as a dynamic model. However, the Koyck transformation which is commonly used to establish the dynamic link between advertising and the following response has some limitations, therefore a method eliminating them is proposed. The two methods are compared and the proposed one looks promising. The results of the estimation confirm the ability of TV to drive an immediate response which means that people are willing to turn to their phone to look up some information communicated in the TV spot. On contrary, most of the ads do not have a significant effect on the website traffic which opens another question – which ad qualities cause the highest incremental uplift? The estimated ad effects strongly depend on the amount of impressions caused by the ad. Hence, before further research, the impact of impressions is separated with a linear regression (which proves to be a robust solution). Thereafter, a random forest is built to reveal the complex and non-linear dependencies. As it is difficult to interpret almost all machine learning models, it is necessary to use the method of plotting partial dependencies to understand the outputs from the random forest. Apart from the strong effect of the number of impressions generated by the ad, the motive, TV channel and hour were found significant ad qualities affecting the ability to generate the website traffic. Based on this knowledge it is possible to optimize the TV buying process in order to get the most traffic out of the ads. Způsob přístupu: Internet ekonometrie a operační výzkum [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Data-driven marketing Dynamic models Random forest Kernel smoothing Koyck transformation Holý, Vladimír ISIS:116093 ths Zouhar, Jan, 1982- vse2009539908 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/71010/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/71010 Hlavní práce https://insis.vse.cz/zp/71010/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/71010/posudek/oponent/68808 Oponentura https://insis.vse.cz/zp/71010/podrobnosti dc:identifier NEPOSILAT VSKP vse71010 210204 71010