Specialty: 075 Marketing.
Degree: Bachelor. Semester: 5.
ECTS: 5 (2020 entry year).
Form of final knowledge control: Exam.
Author: Inna Kostenko, senior lecturer at the Department of Economic Cybernetics.
Abstract: The purpose of the course is to acquire theoretical and practical studies of the basics of Internet analytics, develop skills in working with web analysis tools for data analysis and optimization of web resources.
The course is aimed at students consistently acquiring skills in working with
web analytics systems such as Google Analytics Universal, Google Analytics 4,
as well as separate sections in Google Search Console, Google Ads and Facebook
Ads, "open-sourse” services such as Google Trends, Similarweb,
Alexa, Semrush, Serpstat , Moz,
Majestic, GemiusAudience, Seoquick,
mastering the basics of data collection and analysis, understanding key digital
business metrics.
The
content of the training course is structured in such a way as to gradually
immerse the student in the world of data analysis, that is, from simple to
complex: at the very beginning, this is an introduction to the concepts of
offline and online business conversions, the formation of a business strategy
based on clear real examples, the beginning of working with web tools
analytics, their settings, and upon completion, an understanding of the logic
of search algorithms, the features of setting up advertising campaigns,
monitoring KPIs, creating analytical reports, dashboards and forecasting the
KPIs of a digital business.
Structurally, the course is divided into 15 topics, each of which contains 4-7
questions and necessarily an overview of various web analytics tools in each
topic. Features of the formation of a competitive analysis of websites based on
open digital business metrics (benchmarking) are given.
A
significant part of the educational material is work with Google Analytics (to
configure data collection from your own educational site). Practical examples
of statistical data analysis and visualization in the environment of Power BI,
Excel, Googlesheets,
Data Studio application software are presented. The methodology and applied
aspects of A/B testing (based on Google Optimize, Google Ads and Facebook Ads)
are considered.