ACE3078 : Data & Marketing Analytics
- Offered for Year: 2020/21
- Module Leader(s): Dr Luca Panzone
- Owning School: Natural and Environmental Sciences
- Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: | 10 |
ECTS Credits: | 5.0 |
Aims
Businesses have increasing availability of data useable for marketing research, often unexploited because of limited technical knowledge. This module provides learners with innovative methods to analyse marketing outcomes and generate insights for effective decision making. This module examines the importance of managing marketing data in effective marketing decision making. It presents the role of marketing metrics within the organisation and establishes how an understanding of a range of measurement techniques can enable organisations to achieve marketing insights and strategic decision making. It provides an appreciation of how measurement techniques, aligned to business objectives, can establish and determine the effectiveness of marketing activities. It outlines the value of using appropriate data sources to enable effective marketing analysis, and of employing appropriate analytic tools and techniques to ensure effective marketing decision making.
Outline Of Syllabus
Introductory multivariate statistics – Conditional dependence
Introductory multivariate statistics – Correlation and causality
Metrics and analytics
Measuring effectiveness
Regression analysis – Marketing models
Regression analysis – Demand models
Choice modelling
Interdependence techniques
Teaching Methods
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Scheduled Learning And Teaching Activities | Lecture | 5 | 2:00 | 10:00 | Asynchronous lecture material |
Guided Independent Study | Assessment preparation and completion | 1 | 10:00 | 10:00 | Preparation for individual report1 |
Guided Independent Study | Assessment preparation and completion | 1 | 37:00 | 37:00 | Preparation for individual report2 |
Scheduled Learning And Teaching Activities | Practical | 4 | 2:00 | 8:00 | Online laboratories |
Guided Independent Study | Skills practice | 1 | 10:00 | 10:00 | Practice in use of statistical software |
Guided Independent Study | Independent study | 1 | 25:00 | 25:00 | Background reading |
Total | 100:00 |
Teaching Rationale And Relationship
This module provides learners with innovative methods to analyse marketing outcomes and generate insights for effective decision making.
The materials will be introduced through a strong introductory phase that uses friendly and motivating learning material, followed by a development phase that:
• Presents real-life examples, replicable in the private sector;
• Explain the practical implications and real-life meanings of the results.
Practicals will allow students to integrate and apply their understanding of the taught materials.
Assessment Methods
Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.
The format of resits will be determined by the Board of Examiners
Other Assessment
Description | Semester | When Set | Percentage | Comment |
---|---|---|---|---|
Report | 1 | M | 20 | Report based on detailed statistical analysis of data (1500 words) |
Report | 1 | M | 80 | Report based on detailed statistical analysis of data (1500 words) |
Assessment Rationale And Relationship
The two assignments have distinct aims:
1) Ability to apply knowledge and critically analyse results (Report 1);
2) Knowledge of the theory behind a method to solve a real research question developed by the student (Report 2).
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- ACE3078's Timetable