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Data Analytics for Customer Insights and Strategy


14 to 15 December 2017


9.00 am to 5.00 pm


Data Analytics Consulting Centre
Department of Statistics and Applied Probability
Computer Laboratory 2 (S16-05-102)
Faculty of Science
6 Science Drive 2
Singapore 117546


This course uses data analytics to analyse customer lifetime value, identify high value customers, and customers to upsell and cross-sell to. This enables businesses to devise customer retention campaigns, customer profiling and segmentation strategies and product marketing strategies by deriving actionable insights through descriptive statistics, RFM modelling, etc.

Who Should Attend?

If you are required to apply a data-driven approach to derive customer and product marketing insights and strategies, or to apply analytics for improved business processes and decision-making, this course is for you!

• Customer insights analysts 
• Data analysts 
• Data engineers 
• Data managers 
• Marketing analysts
• Product managers 
• Technology professionals

Participants should be familiar with computers and basic statistics.


Participants will acquire the following skills at the end of the course:

Applying RFM modelling to identify customers to upsell and cross-sell to

Applying RFM modelling to identify high value customers

Applying statistical techniques for customer profiling and segmentation

Applying statistical techniques for product recommendation strategies


Participants will enjoy an introductory course fee of $1,500 (excluding GST). 
This includes course materials, lunch and tea breaks.

Early bird

$ 1,350
(excluding GST) 
  • Before 14 November 2017

Participants who complete the course will be awarded a Certificate of Participation.

NUS Faculty of Science reserves the right to postpone or cancel the workshop by giving seven (7) days notice prior to the start of the workshop.

If the Faculty cancels the course, you will be notified and refunded your course fees in full.


The course will cover the following topics:

• Introduction to data analytics
• Introduction to RFM modelling
• Customer profiling and segmentation
• Introduction to Customer Lifetime Value
• Introduction to Market Basket Analysis
• Introduction to Association Rule Mining
• Product marketing strategies 

The course will include hands-on practicals on the application of statistical techniques, RFM modelling, Market Basket Analysis and Association Rule Mining.


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