Marketing and Digital Technologies

The first module presents the marketing definition and relations between marketing, value and interactions among company, markets and stakeholders.

Marketing roots are presented looking at the basics of the discipline with a focus on segmentation, targeting and positioning. The module follows with an overview about the role of marketing framework for companies in the complex macroenvironmental context characterized by the system of elements (including technology and big data) that are continuosly changing markets and customer-company interaction.

The module closes with the presentation of marketing value co-creation driven like a framework supported by technologies favoring the actor to actor relationships within the network of actors where the customer is an element of the system

Hours of Total Learning: 6 hours

– Total Contact Hours: 6 hours
– Practice Hours: 4 hours
– Self-Study Hours: 15 hours

Lecturer: Prof. Roberto Bruni

The aim of this module is to describe the market analysis process in digital context. It enables participants understand the online consumer’s behavior, market trends and competitors that is the key to success for any e-commerce.

This course introduces the process of marketing analysis in web context through a combination of lectures, case studies and course project: definition of the research object, establishment of the research objectives, design of the research, collection and analysis of data and report of the research results.

Hours of Total Learning: 6 hours

– Total Contact Hours: 6 hours
– Practice Hours: 4 hours
– Self-Study Hours: 15 hours

Lecturer: Prof. Amor Messaoud

This module aims at an overview of the main statistical methods for data analysis in a marketing context.

All methods will be introduced focusing on both their main methodological aspects and on their application on real datasets, using the software XLStat. In particular, the Linear Regression Model will be used for the definition of the marketing plan.

Based on the same model, the Conjoint Analysis will be applied to define the scenarios and to estimate partial and total utility coefficients. Finally the use of Principal Component Analysis (PCA) will be illustrated by an application on marketing data.

Hours of Total Learning: 6 hours

– Total Contact Hours: 6 hours
– Practice Hours: N/D
– Self-Study Hours: 15 hours

Lecturer: Prof. Simona Balzano

The aim of this module is to describe machine learning and artificial intelligence methods commonly used in web application to characterize the behavior of online customers.

In particular, probabilistic decision rules and supervised classification algorithms will be considered, with examples in recommendation systems and user profiling.

Practical examples will guide course participants through their implementation and usage, highlighting their limits and capabilities

Hours of Total Learning: 6 hours

– Total Contact Hours: 6 hours
– Practice Hours: N/D
– Self-Study Hours: 15 hours

Lecturer: Prof. Mario Guarracino

The module intends to deepen the models for the analysis of consumer behavior and the factors that generally impact on the behavior of buyers and on the intentions and frequency of purchase. A particular

focus is placed on digital technologies from a double point of view:

1) how new technologies and tools have changed consumer behavior (from the perception of need to post-consumer satisfaction);

2) how the purchasing behavior in e-commerce is configured (analogy and differences with the instore purchase).

Hours of Total Learning: 5 hours

– Total Contact Hours: 5 hours
– Practice Hours: N/D
– Self-Study Hours: 12 hours

Lecturer: Prof. ………………..

This module provides students with a broad overview and understanding of the many elements, disciplines, and issues related to web applications and analytics.

As it makes no assumptions about any particular subject, students of any background should be able to cope with the course. Although the general contents of the module are broad, part of it has a strong focus on practical issues in terms of a web application, best-case scenarios, digital business models and strategies, and tools available to browse vast amounts of data. The general aim of this 8-hours long module is to ensure that students understand web applications, and consequently profound analytical approach, is the real world of the Internet.

Hours of Total Learning: 8 hours

– Total Contact Hours: 8 hours
– Practice Hours: N/D
– Self-Study Hours: 20 hours

Lecturer: Prof. Dusan Mladenovjic

Stemming from the general business plan the marketing plan is a crucial element of the company decision-making in determining its future actions and market success.

This, the module brings general understanding of the strong connections between business objectives and marketing goals as well as more specific training on how to develop marketing plans in the web context.

The students will learn to perform situation and competition analysis, develop marketing goals and define marketing strategy, analyze and understand target groups, determine marketing segments and marketing channels, combine sales strategy with other marketing communications strategies, create a roadmap, develop a financial plan and an evaluation plan necessary for final analyses of the achievements of set marketing goals.

They will learn to use a number of state-of-the art planning tools, such as for example Business Model Canvas, SWOT analysis and Customer Funnel.

Hours of Total Learning: 5 hours

– Total Contact Hours: 5 hours
– Practice Hours: N/D
– Self-Study Hours: 12 hours

Lecturer: Prof. Galjina Ognjanov