MARKETING ANALYTICS, METRICS AND PERFORMANCE - 2024/5

Module code: MAN3222

Module Overview

This course deals with concepts, methods, and applications of marketing metrices and analytics. Unlike most marketing courses that focus on conceptual material, this course will provide analytic skills to translate conceptual understanding into metrices, key performance indicators and data visuals (e.g., charts) to guide operational and strategic marketing strategies and decisions  a skill in increasing demand in organizations today. The philosophy in this course embraces three main principles: learning by doing, end user modeling and delivering/communicating action-oriented marketing recommendations to business clients. Each topic has a software implementation along with a case study on a relevant business problem or opportunity. In short, students will analyse primary and/or secondary data to understand: - What is going on (Descriptive analytics: marketing metrices and performance measurement) - Why is it happening (Diagnostic analytics) - What is likely to happen (Predictive analytics) - What to do about it (Marketing decisions) The course will be of particular value to students planning careers in marketing and management consulting. The course is designed for students with some background in basic marketing concepts and statistics. Addressing different learning styles, the following teaching methods are applied in this course: Pre-readings, Lectures, Class Exercises, Class Discussions, Real World Cases, Group Assignments.

Module provider

Surrey Business School

Module Leader

HASSAN Mohamed Sobhy (SBS)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 84

Lecture Hours: 22

Seminar Hours: 11

Guided Learning: 11

Captured Content: 22

Module Availability

Semester 2

Prerequisites / Co-requisites

N/A

Module content

Content:


  • Marketing metrices

  •  Data visualisation

  •  Google analytics

  •  Hypotheses development and testing

  • Independent sample t-test

  •  Paired-sample t-test

  •  One-sample t-test  

  • ANOVA

  •  Correlation

  •  Regression analysis

  •  Conjoint analysis

  • Cluster analysis

  •  Multi-dimensional scaling


Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Group coursework 35
Coursework Individual coursework 65

Alternative Assessment

Individual report: (This is only used if students did not pass the group project or cannot complete the group project).

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate: Understand and critically analyse various methods of marketing analytics, Appreciate the importance and contributions of marketing analytics to decision quality and business performance, Gain some basic, practical knowledge on how to analyse marketing-related data sets and ¿ Appreciate the importance of teamwork when marketing decisions are made based on data, information, and insights. T

hus, the summative assessment for this module consists of:


  • Group coursework (35%) (addresses learning outcomes: 1, 2 and 3)

  • Individual coursework (65%) (addresses learning outcomes: 2, 4 and 5)



Formative assessment

It will be conducted in weekly seminars where the members of each group are asked to report their progress and share issues with the seminar tutor. The submission of a group contribution sheet, together with the report, is compulsory whereby all members of a group are required to specify their contribution percentage. Feedback Feedback will be provided via the following channels In-class group discussions during seminars Weekly ONLINE LIVE lecture (1 hour)  Weekly Seminar (1 hour)  Discussion forum to facilitate discussion of various topics  One-to-one mentoring  Generic and ongoing feedback on reports  Emails  Office hours

Module aims

  • Provide students with the opportunity to learn and apply key methods of marketing analytics.
  • Provide students with a practical experience of applying key methods in measuring, managing, analysing, and presenting marketing-related datasets and relevant marketing performance metrices.
  • Develop student ability to effectively work as a team whereby they coordinate and communicate with other individuals, and appreciate the importance of teamwork in analysing marketing-related datasets and presenting relevant marketing metrics.

Learning outcomes

Attributes Developed
001 Learn about different marketing metrices to measure marketing performance. K
002 Understand how marketing metrices, analytical techniques and computer models can enhance marketing decision-making. K
003 Learn to view marketing phenomena and processes in ways that are amendable to decision modelling. CP
004 Evaluate and use a number of statistical methods for analysing marketing-related datasets. PT
005 Use a software tool kit that will enable you to apply marketing analytics to real marketing decision problems. P

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The core delivery method involves a combination of 2-hours lecture and 1-hour seminar each week. Lectures will be held to discuss various methods for analysing data. Seminars will be held to apply these methods covered in lectures and will be partially allocated to support students preparation for coursework. Q&A forums will be set up to facilitate the discussion of various topics (e.g. Group Report, Methods; Case studies).

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MAN3222

Other information

This module contributes to the development of three pillars of Surrey¿s Curriculum Framework: Employability: this module empowers students to address real marketing decision problems and opportunities through case studies and hands-on exercises using a variety of software and tools adopted by practitioners. Digital Capabilities: Students are expected to learn several software tools (e.g., SPSS, Tableau) and applications to address marketing problems and opportunities through data-driven marketing decisions. Resourcefulness and Resilience: this module improves students¿ self-efficacy through development of digital, teamwork, analytical, communication and problem-solving skills.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2024/5 academic year.