Module and Programme Catalogue

Search site

Find information on

2020/21 Taught Postgraduate Module Catalogue

DESN5322M Data Analytics in Fashion Marketing-Global Fashion Management

15 creditsClass Size: 38

Module manager: Boshuo Guo
Email: B.Guo1@leeds.ac.uk

Taught: 1 May to 31 July, Semester 1 (Sep to Jan) View Timetable

Year running 2020/21

This module is not approved as an Elective

Module summary

This module provides students with the opportunity to gain knowledge methods and techniques of using data to answer fashion marketing questions and facilitate marketing decisions. From this module students will learn which data can be used to answer marketing questions; how to analyse quantitative marketing data; how to make decisions based on this data. This module provides students with fundamental knowledge of quantitative skills and techniques in the marketing context.

Objectives

The role of this module is to inform students in state-of-the-art methods and techniques for contemporary digital marketing.
Students will have the opportunity of learning:
* Which data can be used to answer what marketing questions;
* How to analyse quantitative marketing data;
* How to make management decisions based on the data.
Through this module students will gain a broad understanding of contemporary statistical skills, relevant to global fashion business and applicable to digital fashion marketing and management.

Learning outcomes
1. demonstrate the awareness and skills of collecting and using multiple resources of
data to answer fashion marketing questions.
2. demonstrate the ability of conducting statistical analysis on quantitative data.
3. demonstrate the ability of interpreting the results of quantitative analysis and appreciating what can and cannot be learned from the data.
4. demonstrate the basic skills of using a statistical software.
5. demonstrate the ability of knowing what to do when facing with a quantitative marketing opportunity in fashion industry, including structuring the marketing question, recommending appropriate data sources to use, conduct the quantitative analysis and interpreting the results.


Syllabus

Lectures on the following topics will be taught:
1. Marketing in a digital age and how data facilitate marketing decisions
2. Basic data analysis
3. Basic modelling

Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Delivery typeNumberLength hoursStudent hours
In Course Assessment11.001.00
Class tests, exams and assessment12.002.00
Lecture82.0016.00
Tutorial42.008.00
Private study hours123.00
Total Contact hours27.00
Total hours (100hr per 10 credits)150.00

Private study

1.Learn from the lecture notes (48 hours)
2.Read the core textbook, recommended textbook and latest research in this area (38 hours)
3.Learn to use STATA according to STATA online manual(22 hours)
4.Using STATA to practice the analysis in lecture notes and seminar notes(16hours)

Opportunities for Formative Feedback

Student progress will be monitored via attendance at lectures and tutorials together with completing the question sheet and the exam.

Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information


Coursework
Assessment typeNotes% of formal assessment
In-course AssessmentMock exam0.00
Total percentage (Assessment Coursework)0.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated


Exams
Exam typeExam duration% of formal assessment
Online Time-Limited assessment48 hr 100.00
Total percentage (Assessment Exams)100.00

Students will be given a business context and mock-up data. Students will answer 6 questions based on the business context and the data. Students will have 12 hours (students do not have to sit in a classroom for 12 hours: they can do the exam at home) to answer the 6 questions. Students can use statistical software during the exam. It worth 100% of the exam. A mock exam will be provided for students to practice..

Reading list

The reading list is available from the Library website

Last updated: 26/01/2021 08:29:17

Disclaimer

Browse Other Catalogues

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD

© Copyright Leeds 2019