BASS Social Anthropology and Data Analytics

Year of entry: 2023

Course unit details:
Global Market Research

Course unit fact file
Unit code SOST20051
Credit rating 20
Unit level Level 2
Teaching period(s) Semester 1
Offered by School of Social Sciences
Available as a free choice unit? Yes

Overview

Most larger firms which conduct market research are global in reach. They either sell globally, or use supply chains which cross the globe.  Here we analyse data on market trends at the retail side where consumers buy products. Market researchers usually divide these consumers into small subgroups called “segments”. National government-funded data can aid in these analyses. These are free secondary data on consumer goods, services, and background socio-demographics. We use these data to augment existing within-firm customer data. At the global level, firms must specify the information they need before they can begin using several countries’ data at once.

This course helps with how a firm chooses variables, groups the individual cases, discovering the key consumer segments. We cover 1-3 countries and seek to use multicountry data sets.  Students also read case-studies in key journals that cover brand development and company strategy, ie European Journal of Marketing, International Journal of Market Research, International Conference on Information Fusion, and International Marketing Review.

Aims

The unit aims:

  1. to introduce global market research as a data-driven area.
  2. to stress opportunities for connecting free government data and the analysis of market trends in consumption.
  3. to explore data on consumer choices, trends, and market segmentation.
  4. to explore associations between demographic background and marketing outcomes.
  5. using case studies, we aim to address real-world issues and debates in global marketing research.
  6. to look at segments as predictors in a multi-country setting.
  7. to conduct a simple regression analysis across three countries.
  8. looking at association rules, evaluate market segmentation according to its effects.

Learning outcomes

Knowledge and Understanding:

  • students will be able to plan the scope of a study of market segments.

Intellectual skills:

  • students will distinguish exploratory from explanatory methods of association and modelling in global market research.
  • students will critically evaluate marketing case studies in terms of how well data was handled, and how clearly the issue of associations was treated.
  • students will become experts on specific segmentation techniques for market research in multiple countries.

Practical Skills:

  • students will be able to prepare diagrams using closely-guided use of secondary datasets.
  • skills in using R software, using marketing data from countries including UK, USA, and India.

Transferable skills and personal qualities:

  • students in this class will study ‘critical analysis of causal arguments’ and thus become more aware of causal and associational claims, in the context of handling data.

Teaching and learning methods

There will be a mixture of lectures and tutorials.

Please note the information in scheduled activity hours are only a guidance and may change.

We plan for 11 week, each with 2 one-hour presentation sessions, which include substantial student input and discussion; plus an additional one-hour weekly practical involving computer or small-group work.

Employability skills

Analytical skills
Group/team working
Oral communication
Problem solving
Research
Written communication

Assessment methods

Method Weight
Written assignment (inc essay) 70%
Set exercise 30%

Feedback methods

You get informal feedback on two figures (diagrams) that you construct yourself.

The School of Social Sciences (SoSS) is committed to providing timely and appropriate feedback to students on their academic progress and achievement, thereby enabling students to reflect on their progress and plan their academic and skills development effectively. Students are reminded that feedback is necessarily responsive: only when a student has done a certain amount of work and approaches us with it at the appropriate fora is it possible for us to feed back on the student’s work. The main forms of feedback on this course are written feedback responses to assessed essays and exam answers.

We also draw your attention to the variety of generic forms of feedback available to you on this as on all SoSS courses. These include: meeting the lecturer/tutor during their office hours; e-mailing questions to the lecturer/tutor; asking questions from the lecturer (before and after lecture); presenting a question on the discussion board on Blackboard; and obtaining feedback from your peers during tutorials.

Recommended reading

There is a core textbook, Chapman, Chris, and Elea McDonnell Feit (2015), R for Marketing Research and Analytics (London: Springer). Notably chapter 4 if you wish to do pre-reading.

Those who want to use computers more can study this Healy, Kieran (2018) Data Visualization (Princeton:  Princeton University Press), Chapter 4.

Study hours

Scheduled activity hours
Lectures 20
Tutorials 10
Independent study hours
Independent study 170

Teaching staff

Staff member Role
Wendy Olsen Unit coordinator

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