Module Details

Module Code: MGMT8047
Title: Business Metrics
Long Title: Business Metrics
NFQ Level: Advanced
Valid From: Semester 1 - 2016/17 ( September 2016 )
Duration: 1 Semester
Credits: 5
Field of Study: 3450 - Business & Management
Module Delivered in: 1 programme(s)
Module Description: This module focuses on management decision making in business marketing. It includes analysis of data requirements, key marketing, management and financial & investment metrics e.g. customer lifetime value. The student will become proficient and confident in using spreadsheets to analyse data to support marketing decision making.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Discuss key management and marketing investment issues and the role of analytics in marketing finance today.
LO2 Analyse and measure success or failure in financial terms in respect of sales and marketing.
LO3 Develop a plan for the implementation of a marketing analytics process and systems in a business.
LO4 Develop a data requirements document and instigate a data development and management plan for the marketing analytics as applied to marketing management.
LO5 Develop key performance metrics in marketing investment decision making using quantitative tools and software.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
None.
 
Indicative Content
Management Decision Making
Nature of management decision making in internet age. Changes in markets and in management practice /marketing campaigns / budgets and customer investment analysis. Data in management / quantity problem / need for data analysis to guide management decision making.
Marketing Management Metrics
Brand Management and Promotion, Comparative Marketing, Customer Loyalty. Introduction to metrics. 'Branding' / 'Testing' / 'Churn' / 'Customer Satisfaction' / 'Take'. Balanced Scorecard approach.
Decision Support for Marketing, Investment and Finance
Change in business finance. Financial Data. Key Models for Financial Decision Making (Profitability, NPV, Return on Marketing Investment - framework, Stress Testing - sensitivity analysis, payback analysis. Customer Lifetime Value (definition), Value Based Marketing, Short term gains versus Long term relationships, Customer Lifecycle Management.
Data Design and Management
Data Analysis, Design Issues and Collection. Building models with data, necessary data infrastructure, database implementation and management issues, data quality culture. Data scale/scope/complexity.
Module Content & Assessment
Assessment Breakdown%
Coursework40.00%
End of Module Formal Examination60.00%

Assessments

Coursework
Assessment Type Project % of Total Mark 40
Timing Week 10 Learning Outcomes 2,3,5
Assessment Description
Management decision support case study analysis. This will require use of software tools and analytical techniques in order to reach conclusion. Supported by practical learning in laboratory.
End of Module Formal Examination
Assessment Type Formal Exam % of Total Mark 60
Timing End-of-Semester Learning Outcomes 1,2,3,4,5
Assessment Description
End-of-Semester Final Examination
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Class room lecture - theory Every Week 2.00 2
Lab Contact spreadsheet modelling, google analytics Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Study Every Week 2.00 2
Lecturer Supervised Learning (Non-contact) Non Contact Spreadsheet modelling, google analytics Every Week 2.00 2
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Independent & Directed Learning (Non-contact) Non Contact Study and spreadsheet modelling Every Week 4.00 4
Lecture Contact Lecture Every Week 2.00 2
Lab Contact Practical Spreadsheet Work Every Week 1.00 1
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 3.00
 
Module Resources
Recommended Book Resources
  • Wayne C Winston. (2013), Data Analysis & Business Modelling, 1st. Microsoft, [ISBN: 0735669139].
  • P Farriss, N Bendle, P Pfeiffer, D Reibstein. (2010), Marketing Metrics, 2nd. Pearson Prentice Hall.
  • M Jeffrey. (2010), Data Driven Marketing, John Wiley, [ISBN: 978-047050454].
Supplementary Book Resources
  • Jim Sterne, D Scott. (2010), Social Media Metrics, John Wiley, Hoboken, N.J., [ISBN: 0470583789].
  • Andrew King. (2011), Website Optimization, O'Reilly, Farnham, [ISBN: 0596515081].
  • Avinash Kaushik. (2010), Web analytics 2. 0, Wiley, Hoboken, N.J., [ISBN: 0470529393].
  • Alastair Day. Mastering Financial Modelling in Microsoft Excel: A practitioner's guide to applied corporate finance, [ISBN: 0273708066].
  • Keith Ward. (2004), Marketing finance, Elsevier Butterworth-Heinemann, Oxford, [ISBN: 0750657707].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_BBUSS_8 Bachelor of Business (Honours) 1 Elective