module specification

Understanding and Managing Marketing Information introduces students to data-based marketing decision making and provides students with the practical experience of using Excel and SPSS to analyse, present and interpret marketing data. The module adopts an applied, problem-solving approach and aims to equip students with the relevant quantitative and information management skills required by employers within the marketing industry.

The module examines how market, consumer and transactional data can be transformed into information to aid marketing mix decision making and improve the effectiveness of the marketing effort.

The module aims to:

1. Develop an understanding of the nature and scope of marketing information and provide students with an analytical and practical understanding of data-based marketing decision making within the organisational and industry context.

2. Introduce students to a range of numerical techniques to describe, model and interpret business, financial and marketing data to enhance marketing effectiveness and inform marketing mix decision making.

3. Provide students with the practical experience of using Excel and/or SPSS to analyse and interpret market and consumer data to support the marketing processes and inform decision making in a marketing management setting.

4. Introduce students to the measurement and control of companies via budgeting and corporate reporting requirements.

5. Enhance the employability of marketing students by providing opportunities for developing analytical, numerical, problem-solving, interpretation, reporting, team working and presentation skills.

Understanding the nature of demand for products and the influence of market structures (4 weeks)
The laws of supply and demand for products/ services; The influence of market structures on price and supply. Macroeconomic objectives and their impact on organisations.

Understanding Marketing Information Needs (2 weeks):
Information Requirements to Support Consumer and B2B Marketing Decision Making; Data Types; Sources of Marketing Data, Information and Intelligence; Data Collection Methods.

Identifying, Describing and Interpreting Marketing Data and Information (6 weeks):
Sampling Methods; Attitude Measurement, Questionnaire Design and Scaling; Tabulation and Presentation; Descriptive Statistics: Measures of Location and Spread to Describe the Target Consumer, Spending Patterns, and Market Penetration and Opportunities; Presenting and Reporting Findings to an Audience.
Modelling Marketing Data and Identifying Relationships (7 weeks):
Correlation, Linear OLS and Multiple (Stepwise) Regression to measure the Impact of Marketing Communications, Price or Product Decisions on Short-term Performance; Time Series Analysis to Forecast Sales, Profit, Yields, Market Share or Customer Retention. Understanding Cross-tabulations and Chi-square Tests of Independence and Goodness of Fit

Understanding Financial Information (7 weeks):
Interpreting Statements of Financial Activity; Income Statements; Understanding Limited Company Annual Financial Statements; Financial ratios, Introduction to Cost Accounting: Budgeting and Cash Flows, and Methods of Investment Appraisal such as Customer Lifetime Value Estimation, Net Present Values, the Internal Rate of Return and Payback Period for Marketing Planning, Management and Control.

Learning and teaching are structured around three hours of class contact time per week.  The in-class sessions take the form of a 1.5 hour lecture and a 1.5 hour seminar; in some weeks the 1.5 hour seminar will take place in the ICT labs to provide students with the practical experience of using Excel and SPSS to analyse, present and interpret market and consumer data.

To ensure the module meets the needs of the marketing industry, it is delivered by experts in the fields of Marketing Management, Marketing Communications, Market and Consumer Research, and Quantitative Business and Marketing Analysis. In addition, subject specialists are invited to deliver the accounting content of the module.

The lectures are interactive and adopt an applied problem-based approach to learning to introduce students to the theories and methods in the context of marketing challenges and decision making. Whilst the lectures are used to deliver core content, students will be expected to actively contribute to the sessions.

The seminars focus on problem-solving, the application of quantitative marketing decision making techniques, and developing interpretation skills to meet specific marketing information requirements. Sessions are designed to facilitate learning through group-based practical activities, interpretation and reporting exercises, discussions, role-play and presentations, and student-tutor feedback.

The computer-based seminars introduce learners to Excel and / or SPSS for marketing data analysis, and offer further opportunities for developing interpretation skills.

Independent and group learning is supported through the module's virtual learning environment hosted on WebLearn. Here students can access resources such as: lecture notes, exercises and activities, study guides, data sets, videos, self-test quizzes with solutions, coursework briefs, guidelines and feedback, as well as links to further resources. Learners are also encouraged to actively engage with the subject, their peers, and the tutors through the module's online discussion threads and blogs (where new questions and challenges are posted weekly), and chat room facility.

Reflective learning is incorporated into the module and students are advised to keep a journal of experiences and personal development to analyse and reflect on the effectiveness of their learning.

On completing the module students should be able to:

1. Understand the economic influences that customers and competitors may exert on the organisation and how this may be impacted by the market structure in the industry sector. Additionally, an understanding of the impact of government will be gained.

2. Appreciate the need for data analysis and the means by which marketing data are      transformed to inform decision making in each of the marketing mix dimensions; and be able to compute, interpret, and report on, a range of descriptive statistics to improve customer understanding and optimise market segmentation, consumer targeting and product or service positioning.

3. Apply linear analyses, including correlation, ordinary least squares regression, time series and stepwise regression, to model, evaluate and understand how product and service quality, pricing decisions, distribution choices, and advertising and promotions influence customer satisfaction and long-term performance.

4. Interpret the financial statements of a limited company, appreciate the principles of cost accounting, including investment appraisal to evaluate the attractiveness of alternative investments or measure Customer Lifetime Value, and apply budgeting methods in a marketing planning and management context.

5. Use statistical software such as Excel and SPSS to analyse, present and interpret market and consumer data to gain insights and inform the marketing process.

Skills Development
The module also provides opportunities for developing the following range of key skills: Analysing Data, Application of Knowledge and Presenting Data, Communicating / Presenting, Problem Solving and Decision Making, Self / Time Management, Self-Assessment / Reflection, Digital Literacy and IT Skills, and Numeracy / Quantitative Skills.

The module has two assessment opportunities. The first coursework takes the form of a 60-minute unseen, closed book, in-class test worth 30% of the module mark. The test will take place in week 27; covers accounting-based material and may involve students working through problems on Excel.

The second and final assessment component requires the completion of a 3000-word, individual portfolio of work and is weighted at 70%. In addition to the set portfolio activities and tasks, students need to prepare a personal statement to reflect on their learning and development. All assessed tasks and activities, including the reflective statement, contribute to the component grade. The deadline for the overall portfolio is week 28 but students are expected to build the portfolio in stages. Some activities will be completed on WebLearn, others may be achieved in the seminars, and at least 2 problem-based tasks will require the independent preparation of a short report or memo.

To ensure the portfolio remains on track and to provide opportunities for feedback and intervention, interim deadlines for the completion of certain tasks are specified. Formative and (indicative) summative feedback will normally be given within 15 working days of the deadline.

The interim deadline dates by which portfolio tasks need to be completed are:

Week 07 – Class-based activity focusing on Industry structures, information needs and data collection   methods.

Week 13 – Individual analysis of cross-sectional market and / or consumer data using a software package and to prepare a memo or short report for a client to present findings and recommendations.

Week 20 – Short activity assessing correlation, regression and / or time series forecasting. Students will be expected to interpret the findings.

Week 26 – Problem-based tasks requiring the application of multiple regression analysis to a marketing problem. Students will need to use a software package to generate output and prepare a memo or report to present findings and conclusions in a marketing context.

Week 28 – Reflective Statement and submission of completed portfolio.

Summary of Assessed Learning Outcomes and Skills

Reassessment
Students who have attempted all assessments but failed the module overall are normally entitled to a reassessment. Reassessments for this module are managed through WebLearn and involve:

• completing a time-constrained, individual test (coursework 1), and / or
• reworking and resubmitting the portfolio (coursework 2).

The reassessment coursework deadline is stated on Metranet (Quick Links: Term Dates).

Essential Reading:

Sloman etc (2013) ‘Economics for Business’, 6th Edition, FT Prentice Hall, Pearson (ebook available)
http://www.pearsoned.co.uk/bookshop/detail.asp?item=100000000505897
9780273792475

Waters, D. (2011) ‘Quantitative Methods for Business’, 5th Edition, FT Prentice Hall, Pearson (ebook available)
http://www.pearsoned.co.uk/bookshop/detail.asp?item=100000000370117
9780273739470

Dyson, J. R. (2010) ‘Accounting for Non-Accounting Students’, 8th Edition, FT Prentice Hall, Pearson (ebook available)
http://www.pearsoned.co.uk/bookshop/detail.asp?item=100000000281571
9780273722977

Brassington, F. and Pettitt, S. (2013) ‘Essentials of Marketing’, 3rd Edition, FT Prentice Hall, Pearson (ebook available)
http://catalogue.pearsoned.co.uk/educator/product/Essentials-of-Marketing/0273727648.page
9780273727644

Supplementary Reading:

Burns, A. C. and Bush, R. F. (2012) ‘Basic Marketing Research with Excel: International Version’, 3rd Edition, Pearson

Farris, P. W., Bendle, N. T., Pfeifer, P. E. and Reibstein, D. J. (2009) ‘Key Marketing Metrics: The 50+ metrics every manager needs to know’, 1st Edition, FT Prentice Hall, Pearson

Malhotra, N.K. (2011) ‘Basic Marketing Research: Integration of Social Media’, 4th Edition (International Version), FT Prentice Hall, Pearson

Oakshott L. (2012) ‘Essential Quantitative Methods for Business, Management and Finance’, 5th Edition, Palgrave Macmillan

Recommended SPSS Resources:

Allen, P. and Bennett, K. (2010) ‘PASW Statistics by SPSS: A Practical Guide Version 18’, 1st Edition, Cengage Learning

Green, S.B. and Salkind, N.J. (2011) 'Using SPSS for Windows and Macintosh. Analyzing and Understanding Data: International Edition', 6th Edition, Prentice Hall, Pearson

Pallant, J. (2010) 'SPSS Survival Manual. A Step by Step Guide to Data Analysis', 4th Edition, Open University Press

Additional Reading:

Glautier, M., Underdown, B. and Morris, D. (2011) ‘Accounting: Theory and Practice’, 8th Edition, Pearson

Rowntree D. (2004) ‘Statistics Without Tears: A Primer for Non-Mathematicians’ (Allyn & Bacon Classics Edition), Pearson