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BUSI40915: QUANTITATIVE MARKETING RESEARCH (ONLINE)

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 4
Credits 15
Availability Not available in 2024/2025
Module Cap
Location Durham
Department Management and Marketing

Prerequisites

  • None.

Corequisites

  • None.

Excluded Combinations of Modules

  • None.

Aims

  • As a profession, marketing is evolving. It is no longer based primarily on conceptual content, relying on mental models, deep insights and years of experience to formulate marketing decisions, the New Marketing instead resembles design engineering - it consists of putting together data, models, analysis, and computer simulations in order to learn about the marketplace and to design effective strategic marketing plans.
  • To provide a comprehensive introduction to Quantitative Marketing Research (or "Marketing Engineering"); the application of mathematical decision models in the formulation of marketing management decisions. Specifically, the module demonstrates how mathematical models and statistical techniques can be used to transform objective and subjective data about the marketing environment into informed management decisions and decision implementations.
  • Based around both Microsoft Excel and the SPSS statistical package, the module explores both the conceptual knowledge underpinning quantitative marketing decision models and the practical skills needed to generate those models and computer simulations. Participants MUST therefore be confident in both their own statistical abilities and IT skills and have a good working knowledge of Microsoft Excel.

Content

  • The Marketing Research Process
  • Geo-demographic Market Segmentation
  • Primary Data Collection and Analysis
  • Location Analysis & Demand Modelling
  • The Internet as a Data Collection Tool

Learning Outcomes

Subject-specific Knowledge:

  • By the end of this module, students will:
  • have an in-depth understanding and a critical appreciation of how and why Quantitative Market Research can enhance strategic marketing management decisions;
  • possess a specialist knowledge of the most common and successful quantitative marketing decision models;

Subject-specific Skills:

  • Upon successful completion of the module, the students will:
  • have acquired practical "hands on" experience in the generation and analytical application of quantitative marketing decision models in complex situations.

Key Skills:

  • Written communication; planning, organising and time management; problem solving and analysis; using initiative; computer literacy.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • The module is delivered via online learning, divided up into study weeks with specially produced resources within each week. Resources vary according to the learning outcomes but normally include: video content, directed reading, reflection through activities, opportunities for self-assessment and peer-to-peer learning within a tutor-facilitated discussion board. Tutors provide feedback on formative work and facilitate discussion board communication as well as being available for individual consultation as necessary (usually by email and Skype).
  • The summative assessment of the module is designed to test the acquisition and articulation of knowledge and critical understanding, and skills of application and interpretation within the business context.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Video content, directed reading, self-assessed assignments and guidance for further reading150 
Total150 

Summative Assessment

Component: Written AssignmentComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Written Assignment4,000 words (maximum)100Same

Formative Assessment

A written assignment of 1,500 words, or its multimedia equivalent, which may involve some group work.

More information

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