Degree | Type | Year |
---|---|---|
4313148 Marketing | OT | 0 |
You can view this information at the end of this document.
There are no prerequisites
The course "Data-Driven and Behavioral Marketing" provides comprehensive and advanced training in analytical techniques and neuromarketing for strategic marketing decision-making. Students will acquire skills in data analysis using emerging technologies and develop a deep understanding of consumer behavior through neuroscience. This dual approach ensures solid and practical preparation to face current and future challenges in the field of marketing.
Block I: Data-Driven Marketing
This block focuses on equipping students with practical skills in data analysis using Machine Learning and Artificial Intelligence techniques to solve marketing problems based on real data. Through mini-projects with the R environment, they will apply their knowledge to data from companies like Airbnb, Tripadvisor, and Amazon. Students will learn to implement advanced classification and prediction models such as Random Forests, Neural Networks, and Recommendation Systems to analyze and predict consumer behavior, as well as conduct sentiment analysis, ultra-segmentation, and brand engagement on social media platforms.
Block II: Consumer Behavior Marketing
In this block, students will explore the use of neuroscience to understand and predict consumer behavior. By conducting research projects using biosensors and techniques like Eye Tracking and galvanic skin response, students will evaluate the effectiveness of various marketing actions (web pages, packaging, logos, mobile apps,...). This interdisciplinary approach combines knowledge from psychology, neurology, and behavioral economics to provide a deep and applied understanding of consumer behavior.
Block I: Data-Driven Marketing and Artificial Inteligence (5 ECTS – A. Morell, J. L. Vicario)
This part of the module is based on the development of mini-projects in the R data analysis environment. Based on a programming strategy supported by generative AI (Co-pilot), each mini-project develops a topic on data-driven marketing, considering real data from digital marketing companies or synthesized data. Concepts of machine learning applied to marketing will be worked on, concluding with an introduction to the use of Artificial Intelligence to support campaign definition.
Block II: Marketing of consumer behavior (5 ECTS - P. López, G. Lamberti)
This part of the module is based on the development of a mini-research project in neuromarketing through the use of biosensors based on their experimental design, data capture and analysis.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Lectures, case discussion and presentation of short essays | 75 | 3 | 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20 |
Type: Supervised | |||
Tutorials and follow-up of the essays to be carried out and of the cases of analysis | 50 | 2 | 4, 5, 9, 15, 17, 20 |
Type: Autonomous | |||
Assigned readings, preparation of assignments and practical exercises, study and elaboration of schemes | 100 | 4 | 2, 4, 5, 8, 12, 15, 20, 21 |
Teaching methodology
A whole set of teaching methodologies are combined:
Note: 15 minutes of a class will be reserved, within the calendar established by the center / degree, for the complementation by the students of the Surveys of evaluation of the performance of the teaching staff and of evaluation / module.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Attendance and participation in class discussions | 20% | 10 | 0.4 | 5, 8, 13, 14, 15, 16, 17, 21 |
Exercises for individual assessment | 40% | 3 | 0.12 | 6, 10, 11, 12, 13, 14, 15, 16 |
Individual or group exercises | 40% | 12 | 0.48 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 |
This subject/module does not offer the option for comprehensive evaluation.
Assessment
A. General information abou assessment rules
This module is structured in different sections that are in charge of different professors. The final grade of the module are the average grades of both sections.
This module does not offer the option for comprehensive evaluation.
It is considered that the module has been approved if:
If the module is not approved, the coordination of the master's degree will offer the student the possibility of re-evaluating the parts that make up the module and that have not been passed if the grade is greater than or equal to 3.5, according to the evaluation of the professors. modules and coordination. If the student passes the reassessment, the maximum mark that will be obtained in the re-assessed part will be 5. The re-assessment calendar will be made public along with the list of module marks.
The note of each part of the module
The student will have a mark of Not Assessed if he does not attend at least 80% of the face-to-face classes (a control will be kept with a signature sheet) or if he does not carry out at least 50% of the continuous assessment activities. Each professor will specify in this guide the way in which he will evaluate the students. If not specified in the guide, these evaluation standards will be delivered on the first day of class in writing.
B. Calendar of evaluation activities
The dates of the evaluation activities (midterm exams, exercises in the classroom, assignments, ...) will be announced well in advance during the semester.
The date of the final exam is scheduled in the assessment calendar of the Faculty.
"The dates of evaluation activities cannot be modified, unless there is an exceptional and duly justified reason why an evaluation activity cannot be carried out. In this case, the degree coordinator will contact both the teaching staff and the affected student, and a new date will be scheduled within the same academic period to make up for the missed evaluation activity." Section 1 of Article 115. Calendar of evaluation activities (Academic Regulations UAB). Students of the Faculty of Economics and Business, who in accordance with the previous paragraph need to change an evaluation activity date must process the request by filling out an Application for exams' reschedule https://eformularis.uab.cat/group/deganat_feie/application-for-exams-reschedule
Grade Review Procedure
Coinciding with the final exam, the day and medium in which the final grades will be published will be announced. In the same way, the procedure, place, date and time of the review of exams will be informed in accordance with the regulations of the University.
Recovery Process
“To participate in the recovery process, students must have been previously evaluated in a set of activities that represents a minimum of two thirds of the total grade for the subject or module.” Section 3 of Article 112 ter. Recovery (UAB Academic Regulations). Students must have obtained anaverage grade for the subject between 3.5 and 4.9.
All students are required to perform the evaluation activities. If the student's grade is 5 or higher, the student passes the course and it cannot be subject to further evaluation. If the student grade is less than 3.5, the student will have to repeat the course the following year. Students whohave obtained a grade that is equal to or greater than 3.5 and less than 5 can take a second chance exam. The lecturers will decide the type of the second chance exam. When the second exam grade is greater than 5, the final grade will be a PASS with a maximum numerical grade of 5. When the second exam grade is less than 5, the final grade will be a FAIL with a numerical grade equal to the grade achieved in the course grade (not the second chance exam grade).
A student who does not perform any evaluative task is considered “not evaluable”, therefore, a student who performs a continuous assessment component can no longer be qualified with a "not evaluable".
The date of the retake exam will be posted in the calendar of evaluation activities of the Faculty. Students who take this exam and pass, will get a grade of 5 for the subject. If the student does not pass the retake, the grade will remain unchanged, and hence, student will fail the course.
Irregularities in the assesment process
In spite of other disciplinary measures deemed appropriate, and in accordance with current academic regulations, "in the case that the student makes any irregularity that could lead to a significant variation in the grade of an evaluation activity, it will be graded with a 0, regardless of the disciplinary process that can be instructed. In case of various irregularities occur in the evaluationof the same subject, the final grade of this subject will be 0". Section 10 of Article 116. Results of the evaluation. (UAB Academic Regulations).
BLOCK II:
R software
R CLOUD
Biometric Gazepoint
Pupil Lab
Name | Group | Language | Semester | Turn |
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(TEm) Theory (master) | 30 | Spanish | second semester | afternoon |