Analiza zajema analitičnih podatkov v Google Analytics 4 in primerjava z Universal Analytics

Selimović, Alena (author), Hladnik, Aleš (mentor)

Metode zbiranja, obdelave in analize podatkov v digitalnem marketingu v zadnjih letih pridobivajo vedno večji pomen. Razvijajo se nova analitična orodja in metode, ki omogočajo poglobljen vpogled v vedenje spletnih uporabnikov, možnost predvidevanja njihovih nadaljnjih korakov in njihovo segmentacijo v kategorije glede na interese, demografske podatke, nakupne navade in pretekla iskanja. Eno takih orodij je Google Analytics, ki je bil oktobra 2020 nadgrajen v novo različico, imenovano Google Analytics 4. Namen magistrskega dela je bil pregled dostopne dokumentacije za implementacijo omenjene različice analitične storitve ter analiza razlik v podatkovnem modelu in načinu beleženja statistik v primerjavi s predhodno različico, tj. Universal Analytics. Raziskavo smo izvedli z analitično implementacijo obeh različic s pomočjo orodja Google Tag Manager. Na podlagi implementiranih analitičnih dogodkov smo zastavili testne scenarije, s katerimi smo preverili proženje in beleženje analitičnih dogodkov ter pripadajočih parametrov v različnih okoliščinah. Na podlagi rezultatov zastavljenih testnih scenarijev smo nato lahko izračunali in primerjali razlike v statističnih metrikah obiska spletnih mest ter konverzijskih metrikah, zabeleženih v različicah Universal Analytics in Google Analytics 4. Izračunane vrednosti in razhajanja med vrednostmi so omogočili, da smo potrdili oziroma ovrgli zastavljene hipoteze, z rezultati testnih scenarijev pa smo podali tudi razloge oziroma odgovore, zakaj prihaja do razlik v zabeleženih vrednostih metrik.

• Language: Slovenian
• Keywords: Universal Analytics, Google Analytics 4, analitični dogodek, seja, konverzija
• Work type: Master's thesis/paper
• Organization: NTF - Faculty of Natural Sciences and Engineering
• Year: 2022
• PID: 20.500.12556/RUL-139787
• Publication date in RUL: 07.09.2022

Secondary language

• Language: English
• Title: Analytical data collection analysis in Google Analytics 4 and comparison with Universal Analytics

Abstract

Methods of data collection, processing and analysis in digital marketing have become increasingly important in recent years. New analytical tools and methods are being developed that provide a more comprehensive insight into the behaviour of online users, the ability to predict their next steps and enable their segmentation into categories according to interests, demographic data, shopping habits and previous searches. One such analytical tool is Google Analytics, which was upgraded in October 2020 to a new version called Google Analytics 4. The purpose of the master's thesis was to review the available documentation for the implementation of this new version and to analyse the differences in the data model and recorded statistics compared to the previous version, ie. Universal Analytics. We conducted the research through an analytical implementation of both versions using the Google Tag Manager tool. Based on the implemented analytical events, we set up test scenarios in order to verify the triggering and recording of analytical events and the associated parameters under various conditions. The results of the test scenarios allowed us to calculate and compare the differences in statistical metrics of website visits and conversion metrics recorded in Universal Analytics and Google Analytics 4. The calculated values and the discrepancies between them made it possible for us to confirm or refute the set hypotheses, while the results of the test scenarios provided us with answers as to why there are differences in the recorded values of metrics.

• Keywords: Universal Analytics, Google Analytics 4, analytical event, session, conversion