Core Module Information
Module title: Digital Analytics Strategy (Hong Kong)

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: MKT11910
Module leader: Andrew Kincaid
School The Business School
Subject area group: Marketing
Prerequisites

Study or practical experience of marketing at an appropriate level.

Description of module content:

The module develops in-depth understanding of the theory, practice and managerial implications of using Digital Analytics as part of an organisation’s marketing strategy.
The syllabus will introduce you to key principles and challenges, including the analysis and evaluation of data from social media, websites and search marketing to improve marketing performance. You will engage with a range of literature to reflect critically on contemporary issues and evaluate the role of big data ethics in an organisational context. In addition, you will get hands-on experience in key Digital Analytics tools used by marketing practitioners, resulting in strong strategic and applied knowledge in Digital Analytics upon successful completion of the module.

Learning Outcomes for module:

LO1: Critically evaluate the role of Digital Analytics in business strategy.
LO2: Define and analyse commonly used Digital Analytics metrics and KPIs in the context of marketing objectives.
LO3: Demonstrate a critical understanding of the main tools and techniques involved in data-driven marketing.
LO4: Critically appraise the ethical implications of Digital Analytics on business practice.

Full Details of Teaching and Assessment
2022/3, Trimester 2, FACE-TO-FACE,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: FACE-TO-FACE
Location of delivery: HONG KONG
Partner:
Member of staff responsible for delivering module: Simone Kurtzke
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Learning & teaching methods including their alignment to LOs: Online delivery blends with face-to-face introduction and assessment briefings. A core textbook recommended. Students gain experience of a digital learning environment and planning study autonomously. The Module Leader gives online support, moderates a discussion and an exercise sourcing materials. Embedding of employability/PDP/scholarship skills: Students undertake an industry-developed Digital Analytics course that will equip them with practical skills in the main tool used in industry (formative). Students complete a
Moodle online workbook including class test covering the role and evaluation of key concepts, tools and techniques of digital analytics (Assignment 1). Students also write a critical essay on Digital Analytics based on a topic from a choice of three (Assignment 2). For both assignments they engage with both academic and practitioner sources to allow critical engagement and facilitate deep understanding of how theory applies to practice. Research/teaching linkages: The searching for appropriate sources in the above sourcing exercise and both assignments ensure familiarity with recent research. Supporting equality and diversity: The delivery mode is adaptable and suited to both full and part-time students. Internationalisation. Examples from Europe, the US and the Far East are used and student-generated examples are encouraged. Summative Assessment: Assignment 1 is an individual assessment (LO2, 3). It consists of a class test (a Moodle quiz for summative ‘take home’ assessment) covering the role and
evaluation of key concepts, tools and techniques of digital analytics (30%). Assignment 2 is an essay (3,000 words, 70%) based on a major issue of digital analytics (LO1, 4).

Formative Assessment:
Formative assessment takes place throughout the weeks of attendance. Students also undertake an industry-developed Digital Analytics course that will equip them with practical skills in the main tool used in industry (formative).

Summative Assessment:
Summative Assessment: Assignment 1 is an individual assessment (LO2, 3). It consists of a class test (a Moodle quiz for summative ‘take home’ assessment) covering the role and evaluation of key concepts, tools and techniques of digital analytics (30%). Assignment 2 is an essay (3,000 words, 70%) based on a major issue of digital analytics (LO1, 4).

Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Lecture 15
Face To Face Tutorial 15
Independent Learning Guided independent study 170
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Class Test 30 2,3 9 HOURS= 00.00
Essay 70 1,4 13 , WORDS= 3000
Component 1 subtotal: 30
Component 2 subtotal: 70
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader