DATA-DRIVEN DIGITAL MARKETING LAB - 1

The DATA-DRIVEN DIGITAL MARKETING LAB course is included among the related and supplementary courses within the Marketing Management study path, with the aim of deepening topics related to the management of online marketing in a rapidly evolving market context.
In order to respond to new consumer purchasing behaviours, companies are increasingly integrating online and offline activities, making it necessary to train professionals who can combine strategic vision with analytical rigour. The course is specifically designed to meet this need: thanks to joint teaching by instructors with expertise in their respective disciplines, students will simultaneously acquire specific digital marketing skills and specific statistical data analysis skills, both of which are essential for interpreting digital metrics and supporting evidence-based decisions.
This interdisciplinary approach, which organically integrates the two areas of knowledge rather than treating them separately, constitutes the distinctive feature of the course and enables students to develop a data-driven approach to digital marketing strategy, both at the strategic and operational levels.

At the end of the course, students will know:
• the main tools and logics of digital marketing, with particular reference to content marketing, email marketing, online consumer behaviour analysis, and the definition and measurement of KPIs;
• the key metrics for evaluating digital performance and the criteria for interpreting them from a strategic perspective;
• the fundamentals of statistical analysis applied to marketing data and the main quantitative analysis techniques that can be used in real decision-making contexts;
• the functionalities of the R software environment for importing, cleaning, exploring, and analysing marketing datasets.
At the end of the course, students will be able to:
• work with real datasets of different kinds, assessing their structure, quality, and relevance in relation to the analysis objective;
• independently select the relevant data and choose the most appropriate statistical methods according to the business decision to be supported;
• implement quantitative analyses using R software and interpret the results from a marketing perspective;
• translate analytical results into strategic and operational recommendations relating to content marketing campaigns, email marketing activities, and consumer behaviour understanding;
• reason in an integrated way by combining digital marketing and statistical analysis skills, simulating the decision-making process typical of a professional context.
Independent judgement – At the end of the course, students will be able to:
• critically assess the quality and adequacy of the available data in relation to an analysis objective, recognising both their limitations and potential;
• justify the methodological choices made — both in terms of data selection and statistical methods adopted — in relation to the marketing decision-making problem addressed.
Communication skills – At the end of the course, students will be able to:
• present the results of a data-driven analysis clearly and effectively;
• produce reports and visualisations that make the results of statistical analyses conducted with R accessible and easy to interpret;
• communicate in an integrated way the quantitative and strategic dimensions of a digital marketing decision, connecting data, methods, and operational implications.

A solid knowledge of a basic academic course in marketing is required, as well as familiarity with the topics covered in the statistics for marketing course.

• Digital marketing plan
• User persona and customer journey
• Online communication: owned, paid, and earned media
• Content marketing
• KPIs
• PCA
• Cluster analysis
• Multiple linear regression
• Logistic regression
• Theory and techniques of content analysis

The textbook and readings will be communicated during the first day of class and will be available in the file entitled “course presentation” on the Moodle platform.

Learning assessment is carried out through a written exam based on a business case. Students are provided with the business context, the marketing decision to be supported, and a dataset to work on. Starting from these elements, they will be required to: assess the available data and their relevance to the stated objective; independently choose the most appropriate statistical analysis technique; carry out the analysis using R software; answer the marketing question by justifying their methodological choices and commenting on the results obtained with explicit reference to the processed data.
The assessment therefore evaluates not only the technical correctness of the analysis, but also the students’ judgement in selecting the appropriate approach and the quality of the reasoning that connects quantitative results to the marketing decision.
Students are required to bring their own laptop to the exam.

written

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

The grading system (how the grades will be assigned) is the same for attending or non-attending students:
A. scores in the 18-22 range will be awarded in the presence of:
- sufficient knowledge and ability to understand applied in relation to the programme;
- sufficient ability to apply knowledge and understanding and judgment;
- sufficient communication skills, especially in relation to the use of specific language relating to the subject;
B. scores in the 23-26 range will be awarded in the presence of:
- good knowledge and ability to understand applied in relation to the programme;
- good ability to apply knowledge and understanding and judgement;
- good communication skills, especially in relation to the use of specific language relating to the subject;
C. scores in the 27-30 range will be awarded in the presence of:
- excellent knowledge and ability to understand applied in relation to the programme;
- excellent ability to apply knowledge and understanding and judgment;
- excellent communication skills, especially in relation to the use of specific language relating to the subject.

Lectures, group work, company guest talks, case studies.

English