Module Directory

This module aims to demonstrate the benefits of using a systematic and analytical approach to marketing decision-making.

An analytical approach will enable students to:

- use and execute data analytic techniques and case studies to understand how to solve marketing analytics problems in a scientific and process-driven manner.

- understand how the "first principles" of marketing strategy help firms organise the analytics opportunities and challenges that exist in today's data era.

The aims of this module are:

• To equip students with an understanding of the key concepts of marketing analytics.


• To introduce key approaches and benefits of data visualization.


• To emphasize the benefits of learning and utilizing marketing analytics.


• To apply software tools, R and Tableau, to perform marketing analytics analyses.

By the end of this module, students will be expected to be able to:

1. Demonstrate an understanding of key foundations of marketing analytics.


2. Critically evaluate and develop analytical solutions to marketing challenges.


3. Analyse and interpret marketing data, such as customer and market insights.


4. Critically assess analytical approaches and techniques related to marketing analytics.


5. Exhibit the knowledge and abilities required to gather and process market data to make informed decisions.

The module is based on the premise that the majority of analytic challenges faced by marketing researchers, consultants, and managers relate to the customers, competitors, and resources. These issues may be effectively segregated into four marketing problems: managing customers' heterogeneity, managing customers' dynamics, managing sustainable competitive advantage, and managing resource trade-offs. The module will emphasise developing analytic competencies pertaining to solving such marketing problems. Students will learn various marketing analytics techniques in this module.

Overall, by completing this module, students will be on their way to making the ROI case for marketing expenditures that companies are increasingly asking from their executives.

Syllabus

• Introduction to Marketing Analytics.


• Managing Customer Heterogeneity: Cluster Analysis and Segmentation.


• Managing Customer Heterogeneity: Discriminant Analysis for Targeting and Classification, Perceptual Mapping and Positioning.


• Managing Customer Heterogeneity: Perceptual and Preference Mapping for Competitive Positioning.


• Managing Customer Dynamics: Using RFM Analysis for Customer Selection.


• Managing Customer Dynamics: Using Logistic Regression and Customer Lifetime Value for Customer Selection.


• Managing SCA: Survey Design and Testing to Derive Customer Insights.


• Managing SCA: Conjoint Analysis and Forecasting Sales for New Products and Pricing Decisions.


• Managing Resource Trade-Offs: Using Marketing Mix Models and Experiments to Optimize the Marketing Mix.

This module will be delivered via:

• One lecture per week.
• One coursework presentation day at the end of this module.

The "Tell-Show-Do" sequence will be used to provide students with hands-on experience, utilising the module materials, for making marketing decisions.

Lectures will cover the concepts and analytical models that students need to understand to bring a scientific approach to marketing. Students will have an opportunity to address real-world marketing challenges via the use of these principles and models, as well as the available technological tools.