Applied Digital Marketing Analytics
| Module title | Applied Digital Marketing Analytics |
|---|---|
| Module code | BEMM778 |
| Academic year | 2023/4 |
| Credits | 15 |
| Module staff |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 40 |
|---|
Module description
This introductory module will provide you with an insight into the tools and techniques needed to effectively measure digital marketing activity. With a focus on integrating data from web, social media and search platforms, this module will enable you to identify practical and actionable insights to support effective marketing planning. Using both real-world data and active scenarios, this module will address themes such as campaign performance, campaign testing, audience sentiment, search engine performance and user experience as well as considering how data visualisation can support better communication and drive engagement.
Alongside building a strong understanding of the extent and level of data available to modern marketers, this module will support you to develop applied analytical skills. These skill will be invaluable in helping you to evaluate and justify clear, evidence-led recommendations for organisations.
Module aims - intentions of the module
This module aims to introduce an applied approach to marketing analytics, focusing on the most common data sources and metrics used in marketing practice today. Taking you step by step through the practical application of analysis principles, this module will enable you to identify the meaningful patterns and indicators that support evidence-led decision making. By identifying reliable sources and maximising the effectiveness of the available data, you will learn how to use these findings appropriately and effectively to inform your future recommendations.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. collate, interpret, utilise and visualise data from a wide range of different sources
- 2. draw on knowledge of relevant tools and practice to identify and effectively analyse relevant data
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. demonstrate detailed knowledge of how to measure and monitor marketing effectiveness
- 4. effectively utilise marketing data to support organisational decision making
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 5. exhibit highly developed analytical and evaluative skills
- 6. identify the value of data and technology in supporting organisational success
Syllabus plan
Core themes considered in the module will include:
- Web analytics
- Algorithms: what we do and don’t know
- Search engine performance & optimisation
- Social media metrics and audience analysis
- Sentiment & trend analysis
- Customer journey analytics
- KPIs and performance metrics
- Campaign testing
- Data visualisation
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 18 | 132 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled learning and teaching activities | 10 hours | 10 x 1 hour whole cohort session |
| Scheduled learning and teaching activities | 8 hours | 8 x 1 hour seminar |
| Scheduled learning and teaching activities | 132 hours | Core and supplementary reading, individual assignments |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Seminar exercises | Via 8 hour seminars | 1-6 | Verbal and/or written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 0 | 100 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| In term test | 30 | 1 hour | 2,4 | Written |
| Exam | 70 | 2 hour (2000 word equivalent) | 1,2,3,5,6 | Written |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| In term test | 30% in term test 1 hour | 2,4 | Relevant reassessment period |
| Exam | 70% 2 hour exam (2000 word equivalent) | 1,2,3,5,6 | Relevant reassessment period |
Indicative learning resources - Basic reading
Recommended reading:
Sponder, M., & Khan, G. F. (2017). Digital analytics for marketing. Routledge.
Additional reading:
Flores, L. (2014) How to measure digital marketing: metrics for assessing impact and designing success. Basingstoke, Palgrave Macmillan.
Hemann, C. & Burbary, K. (2018) Digital marketing analytics: making sense of consumer data in a digital world. US, Pearson
Wexler, S., Shaffer, J. & Cotgreave, A. (2017) The big book of dashboards: visualizing your data using real-world business scenarios. Hoboken, Wiley.
Indicative learning resources - Web based and electronic resources
Additional reading will also be detailed on the module ELE pages.
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 25/07/2021 |
| Last revision date | 12/01/202 |
