2021/22 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: Semester 2 (Jan to Jun) View Timetable
Year running 2021/22
This module is not approved as an Elective
Module summary
This module provides students with the opportunity to gain knowledge in 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
On completion of this module, students will have provided evidence of being able to:
1. Use multiple resources of data to answer fashion marketing questions.
2. Conduct statistical analysis on quantitative data.
3. Interpret results of quantitative analysis and understand what can and cannot be learned from the data.
4. Apply statistical software basic skills.
5. Know 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
Areas that will be taught during the module:
1. Marketing in a digital age
2. Basic data analysis, modelling and how data facilitate marketing decisions
3. New data tech in fashion marketing and design
Teaching methods
Delivery type | Number | Length hours | Student hours |
Class tests, exams and assessment | 1 | 24.00 | 24.00 |
Class tests, exams and assessment | 1 | 48.00 | 48.00 |
Lecture | 8 | 2.00 | 16.00 |
Tutorial | 4 | 2.00 | 8.00 |
Private study hours | 54.00 | ||
Total Contact hours | 96.00 | ||
Total hours (100hr per 10 credits) | 150.00 |
Private study
Private studies will include the following activities:1.Learn from the lecture notes (24 hours)
2.Read the core textbook, recommended textbook and latest research in this area (24 hours)
3.Learn to use STATA according to STATA online manual (3 hours)
4.Using STATA to practice the analysis in lecture notes and seminar notes (3 hours)
Opportunities for Formative Feedback
Student progress will be monitored via attendance at lectures and tutorials together with completing the mock online assessment and the online time-limit assessment.Methods of assessment
Coursework
Assessment type | Notes | % of formal assessment |
In-course Assessment | Mock Exam | 0.00 |
Total percentage (Assessment Coursework) | 0.00 |
Mock exam: Students will have a exam containing three tasks to test what they have learned from tutorials. Students will run required analysis with statistical software and interpret the analytical results
Exams
Exam type | Exam duration | % of formal assessment |
Online Time-Limited assessment | 48 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 websiteLast updated: 30/07/2021 16:02:12
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