24753 Customer Analytics
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Subject handbook information prior to 2025 is available in the Archives.
Credit points: 6 cp
Result type: Grade and marks
Requisite(s): ((24 credit points of completed study in spk(s): C04379 Master of Business Analytics (Extension) OR 24 credit points of completed study in spk(s): C04380 Master of Business Analytics)) OR ((24734 Marketing Management OR 24834 Marketing Decision Making) AND 24710 Customer Experience and Behaviour)
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Anti-requisite(s): 240753 Customer Analytics
Description
Companies have become more focused on managing relationships throughout customer’s life cycle. At the same time, business decisions are more data-driven because of the exponential increase of customer and market data. Customer analytics involves analysing customer data and metrics to guide business decisions through segmentation, market basket analysis, and CRM, enhancing the marketing mix's effectiveness. In this subject, students learn a wide range of analytical skills and tools to help organisations understand customer behaviour to optimise product or service marketing.
Subject learning objectives (SLOs)
| 1. | Formulate appropriate analyses or models for identified business problems |
|---|---|
| 2. | Apply appropriate analytical methods and techniques to customer data to analyse a wide range of marketing problems |
| 3. | Develop managerial insights from analytical results |
| 4. | Communicate analytical findings and solutions to business problems to key stakeholders |
Contribution to the development of graduate attributes
It is imperative to create customer values by understanding customer needs and wants. With abundance of customer data and rapid advancement in technology, it enables firm to perform sophisticated empirical analyses of customer behaviours and to identify the ways to create and enhance the sources of customer values. It has also become increasingly important to know how marketing actions translate into revenue and profit growth. This subject develops students’ ability to use quantitative and analytical techniques to draw insights from information about customers, which will be linked to business strategy. This involves investigating customer data, building models of customer behaviours, predicting business related outcomes and providing possible solutions to the problems. It also helps students develop practical and advanced research skills to extract relevant information from large amounts of complex data to make improved business decisions such as market segmentation, customer relationship management and demand forecasting.
Teaching and learning strategies
The subject is based on dynamic and interactive lecture and workshop sessions. It is taught through a combination of lectures and workshops. The lectures present prominent marketing problems and illustrate analytical tools/techniques to solve those problems. The lectures involve critical debate with case studies. The workshops are built around in-class exercises with appropriate computer software including Excel, SPSS and/or R. The lectures and workshops will include time where students will work together to apply analytical methods into marketing problems. These classes are supplemented with both printed and electronic learning materials and resources which students are expected to have read prior to classes. The learning management system will be used to share information and encourage interaction between staff and students.
Feedback throughout the session will be given on a weekly basis, verbally and formatively by the instructors to clarify student’s understandings of key concepts and analytical skills. Further feedback will be provided on assessment items throughout the session.
Content (topics)
- Customer segmentation & profiling
- Market basket analysis
- Customer acquisition & Retention
- Customer Lifetime Value (CLV)
- Customer Relationship Management (CRM)
- Product recommendation
- Digital customer analytics
Assessment
Assessment task 1: Group Project (30% Group and 40% Individual)
| Intent: | Assessment 1A (Group 10%): Project proposal |
|---|---|
| Objective(s): | This addresses subject learning objective(s): 1, 2, 3 and 4 |
| Weight: | 70% |
| Length: | Assessment 1A: Project proposal - 300 words (proposal in template) and 15-20 questions (survey questionnaire) |
| Criteria: | Assessment 1A
Assessment 1B
Assessment 1C
|
Assessment task 2: Mid-term In-Class Quiz (Individual)*
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 30% |
| Criteria: |
*Note: Late submission of the assessment task will not be marked and awarded a mark of zero. |
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Required texts
There is no required textbook for this subject. Readings, lecture notes, and assignments will all be available on UTSOnline. Some materials may require copyright purchase.
References
Mike Grigsby (2016), Advanced Customer Analytics: Targeting, Valuing, Segmenting and Loyalty Techniques, Kogan Page Ltd, London UK.
Chapman, Chris and Elea McDonnell Feit (2019), R for Marketing Research and Analytics, 2nd Edition, Springer.
Malhtra, Naresh K. (2019), Marketing Research: An Applied Orientation, 7th Edition, Pearson Education
Coakes, Sheridan J. and Clara Ong (2012), SPSS: Analysis without Anguish (Version 20 for Windows), Milton, QLD: John Wiley & Sons Australia, Ltd