| CODE | CRC5620 | ||||||||||||
| TITLE | Marketing Research and Data Analytics | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| MQF LEVEL | 7 | ||||||||||||
| ECTS CREDITS | 10 | ||||||||||||
| DEPARTMENT | Corporate Communication | ||||||||||||
| DESCRIPTION | The need to understand markets, audiences and consumers is one of the pillars of effective marketing and decision-making. Marketing research and data analytics play a vital role in helping the organisation understand the consumer and markets thereby ensuring meaningful responses by management. The role of marketing research and data analytics are not simply to point out product-related problems, but rather to provide a unified framework for ensuring that the voice of the customer is heeded during the development of strategies and programmes. Study-Unit Aims: - To increase student’s confidence in designing and implementing a specific empirical research project. - To develop an understanding of the importance of assessing psychometric properties of measures of latent variables. - To enable the development of data analyses and interpreting capabilities. - To develop an understanding of the requirements for reporting research findings for the purpose of publication in a peer reviewed journal. - To encourage the capability to critically evaluate research done by others. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Identify the steps required for an effective research process. - Explain the core pillars of analytics and how these can provide insights and lead to better decision-making. - Propose the predictive analytics tools that can be used in different contexts. - Express the latest theories and best practices from academic experts and real-world practitioners. - Assess and justify the formulation of data-driven recommendations to inform the strategic business decisions that lead companies toward success. 2. Skills: By the end of the study-unit the student will be able to: - Demonstrate the fundamental skills needed to conduct robust and insightful market research - Choose the statistical tools required to undertake the necessary analytics - Evaluate different types of data and how this information can be visualized - Summarize and interpret the results of commonly used descriptive analytic approaches - Explore the potential uses of data once these are collected and interpreted with a view to answer what is likely to happen - Apply data sets and appraise their information and how these influence decision-making. Main Text/s and any supplementary readings: Market Research Main Text: - Churchill G. A. & Iacobucci D., Marketing Research: Methodological Foundations, South-Western College Pub, Last edition. Supplementary Readings: - Parasuraman A. Dhruv G. &, Krishnan R. Market Research, New York: Cencage Learning, Last edition. - Kerr A. W. Hall H. K. & Kozub S. A. Doing Statistics with SPSS, London: Sage Publications. Last edition. Data Analytics: Main Text: - Baesens B. (2014) Analytics in a Big Data World: The Essential Guide to Data Science and its Application. Wiley. Supplementary Readings: - Foreman J.W. (2013) Data Smart: Using Data Science to Transform Information into Insight, Wiley. - Linoff G.S., Bwerry M J A (2011) Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, Wiley. - Maheshwari A. (2018) Data Analytics Made Accessible,Kindle edition. - Siegel E. (2016) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Wiley. |
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| STUDY-UNIT TYPE | Lecture, Seminar & Independent Study | ||||||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Malcolm Bonello Noellie Brockdorff Albert Caruana (Co-ord.) Alan Caruana Mario Cassar Saviour Chircop Emanuel Said |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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