ADAN21 - APPLIED DATA ANALYTICS

The course provides the methodological and operational skills to select and apply basic data analysis techniques to support digital marketing decisions.
Students will apply the techniques and concepts learned through a final group project, working on a specific case using realistic data and real data from social media.
At the end of the course, students will be able to:
Understand the analytical context of digital marketing—identify the main information needs related to audiences, user behavior, and digital advertising campaign performance. Understand the difference between descriptive, diagnostic, prescriptive, and predictive analytics and the types of business questions they can answer.
Identify the main data sources in digital marketing—recognize and distinguish the most relevant data sources, such as social media platforms and web analytics tools.
Use Google Analytics to analyze e-commerce data—navigate the Google Analytics interface, interpret predefined reports on user behavior and e-commerce performance, and extract useful insights to support marketing decisions.
Apply descriptive analysis techniques — process corporate datasets and data from e-commerce and social media using Microsoft Excel, mastering the main aggregation, filtering, and statistical synthesis functions.
Design visual reports and interactive dashboards — use Microsoft Excel features to build effective and readable visual representations of data, designed to answer specific business questions and understand the target audience.
Apply clustering techniques for customer segmentation — use a no-code, open tool (KNIME) to apply unsupervised segmentation methods to marketing data, interpret the results, and translate them into actionable recommendations for customer profiling.
These skills will be applied in an integrated manner as part of an end-of-course project.
Dublin Descriptors
Applied Knowledge and Understanding
Students will be able to select and apply basic data analysis techniques to support digital marketing decisions. Specifically, they will be able to identify the main information needs related to audiences, user behavior, and the performance of digital advertising campaigns, recognize the main industry data sources, and apply descriptive analysis and clustering techniques for customer segmentation.
Making judgments
Students will be able to choose the most appropriate analysis technique based on the type of data available and business demand, and critically evaluate the results obtained.
Communication skills
Students will be able to design visual reports and interactive dashboards in Microsoft Excel, creating effective and readable representations designed to communicate audience insights to business stakeholders.
Learning skills
Students will become familiar with the tools used in the course—Google Analytics, Microsoft Excel, and KNIME—developing a methodological foundation that will allow them to independently extend their analytical skills to new digital marketing tools and contexts.