Web analytics

Spletna analitika

Course credits:

6.00 ECTS / 60 (30 hours of lectures, 30 hours of exercises, 0 hours of seminars, 0 hours other forms of work)

Course holder:

izr. prof. dr. Andraž Petrovčič

Lecturers:

• Tch. Asst. Miha Matjašič

Type:

Elective expert

Language:

English

Semester:

Second semester

Study degree

1. level

Course execution:

• Undergraduate Programme of Social Informatics

Prerequisits:

Students are allowed to participate in the course provided that they have completed the enrolment procedure. It is recommended that students have attended the course Statistics or Statistics in data analytics.

Objectives and competences

This course is intended to provide students with both a conceptual and applicable understanding of web analytics that will enable them to collect, analyze, and report website traffic data. The course will give students the knowledge of how to translate web analytics into specific operational models for the planning, execution, and optimization of internet marketing campaigns that involve SEO and online advertising. Students will obtain the following capabilities: 1. Define web analytics and familiarize with its value for research in internet marketing and social science domains. 2. Understand how web analytics is used to collect, analyze, report, and optimize website traffic. 3. Apply best practices in online and offline SEO, including the ethical and legal principles to combine the use of web analytics with SEO. 4. Identify and use key metrics (e.g., visits, bounce rate, conversion rate) to benchmark website traffic and analyze the reports generated by analytics tools. 5. Apply basic concepts such as KPIs, funnels, segmentation, attribution and understand the sources and limitations of web-analytics data. 6. Learn to implement and use key tools for web analytics. 7. Identify and develop web analytics strategies and evaluation techniques for email marketing, social media and multi-channel campaigns. 8. Understand the capabilities of web analytics in relation to other quantitative methods (e.g., clickstream analysis, A/B testing, surveys, eye tracking) for the analysis of digital data.

Content (Syllabus outline)

Students will first learn about the definition, history and importance of web analytics in digital economy and social science domains. The fundamentals of web tracking technologies will be systematically covered, including basics of internet architecture and navigation, page tagging, and cookies. Students will understand technical issues that can reduce accuracy of data as well as security and privacy implications of web analytics. An overview of the major free and chargeable web analytics software tools will be given. Second, the key metrics used in web analytics and their segmentation by various criteria will be explained (page views, visits, visitors, unique visitors, bounce rate, etc.). Third, internet marketing foundations will be presented along with case studies of successful websites. Next, web analytics strategies will be examined, including segmentation, conversion tracking and attribution. Students will learn how to define Key Performance Indicators (KPI) to evaluate a website in reaching its business objectives. Students will learn how to present relevant findings and recommendations to decision makers. In the fourth part, students will get to know how search engines and search algorithms work, learn about on-site and off-site search engine optimization (SEO), and basics of paid search marketing. Next, the online advertising foundations will be addressed, including the role of display networks, audience targeting strategies, banner ad design, and pay-per-click. In the last part, students will learn how to apply web analytics to email marketing and social media campaigns, and how to set up analytics tools for multi-channel campaigns (e.g., mobile). Throughout the course students will be using Google Analytics (GA) as one of the tools. GA account creation, GA tracking code, filters, goals, and GA reports will be covered. GA integration with Google Ads will be also presented.

Intended learning outcomes:

Considering the study results of other courses on the study programme, this course covers activities based on which learning outcomes are expected as follows: 1. Comprehension: indicate, recognise, and explain foundations of web analytics and its application on various fields. 2. Application: plan, find, develop, calculate, and interpret key metrics and indicators used in web analytics for measuring different aspects of websites traffic. 3. Analysis: analyse, examine, arrange, compare, connect, and inspect the efficiency of internet campaigns based on web analytics data, and critically evaluate such data in relation to other methods for collecting and evaluating digital data. 4. Synthesis: compose, modify, rearrange, set up, propose, and explain an optimized solution using web analytics for website design and internet marketing.

Learning and teaching methods:

Lectures, exercises, individual and group assignments, oral presentation, group work with the instructor, project work, individual contact hours, e-learning (20 %).

Assessment

The final grade based on a written exam (100%) or two mid-term written examinations (60%) and a series of four short assignments (40%).

Obligatory literature

Additional literature