Degree | Type | Year | Semester |
---|---|---|---|
4313148 Marketing | OT | 0 | 2 |
You can check it through this link. To consult the language you will need to enter the CODE of the subject. Please note that this information is provisional until 30 November 2023.
There are no prerequisites
This module specializes you in an analytical environment with a business focus. You will learn to obtain quality data and the analytical techniques and tools that will allow you to make the best marketing decisions. Analyze markets, segments or consumers through innovative analysis and models that will reveal key insights to optimize marketing policies.
Block I: Data-driven Marketing
Data-driven marketing deals with the study of marketing problems from data, theories and experiments that study consumer behavior. It is an interdisciplinary line of knowledge (marketing sciences, applied microeconomics, industrial organization and statistical computing) that addresses topics such as: research on consumer choices and behavior, evaluation of business decisions based on data, development and application of small-scale and large-scale experiments, methods for using large amounts of data, computational methods for data analysis available on the Internet. The use of automatic learning techniques (Machine Learning) will be one of the pillars of this block of the module.
Block II: Consumer behavior marketing.
Behavioral marketing deals with the study of how individuals behave in relevant domains of consumption through knowledge arising from consumer neuroscience or neuromarketing. This area of marketing is interdisciplinary (psychology, neurology and behavioral economics). The use of biosensors will be one of the pillars of this block of the module. The use of neuroscientific and psychophysiological techniques will make it possible to analyze the effectiveness of marketing actions (advertising, product, packaging, brand, point of sale, web browsing,...).
Block I: Data-driven Marketing (5 ECTS - A. Morell, J. L. Vicario)
This part of the module is based on the development of mini-projects in the R environment of data analysis. Each mini-project develops a theme based on data marketing, taking into account real data from digital marketing companies (Airbnb, Tripadvisor, Amazon) or social media. They will work on machine learning concepts applied to marketing and will end with an introduction to Deep Learning.
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.
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 | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Lectures, case discussion and presentation of short essays | 75 | 3 | 1, 2, 3, 4, 10, 6, 7, 9, 13, 14, 15, 16, 11, 17, 5, 19, 18, 20 |
Type: Supervised | |||
Tutorials and follow-up of the essays to be carried out and of the cases of analysis | 50 | 2 | 4, 9, 15, 17, 5, 20 |
Type: Autonomous | |||
Assigned readings, preparation of assignments and practical exercises, study and elaboration of schemes | 100 | 4 | 2, 4, 8, 12, 15, 21, 5, 20 |
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).
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Attendance and participation in class discussions | 20% | 10 | 0.4 | 8, 13, 14, 15, 16, 17, 21, 5 |
Exercises for individual assessment | 40% | 3 | 0.12 | 10, 6, 12, 13, 14, 15, 16, 11 |
Individual or group exercises | 40% | 12 | 0.48 | 1, 2, 3, 4, 8, 10, 6, 7, 9, 12, 13, 14, 15, 16, 11, 17, 21, 5, 19, 18, 20 |
BLOCK II:
R software
R CLOUD
Biometric Gazepoint
Pupil Lab