NICF- Customer Analytics
NUS Institute of Systems Science
How long?
- 3 days
- in person
What are the topics?
NUS Institute of Systems Science
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Comprehensive course analysis
Essentials
- What do past participants have to say about the course?
Full
- How many participants were promoted within three years after graduation?
- How did this course affect participants' professional trajectories?
- How many participants got their salary increased within two years after completing the program?
- What do past participants have to say about the course?
Who should attend
- Marketing practitioners and data analysts preferably with more than two years of experience
- Professionals who have an active interest in customer analytics
- Marketing Managers, CRM Managers and Marketing Analysts
- Business Development Managers, Senior Business Analysts and Business Analysts
- Data Managers, Senior Data Analysts, Senior Information Analysts, and Information Analysts
About the course
This is a course designed to help participants understand and analyse their existing customer base across the customer life-cycle from acquisition to retention and develop strategies to reach out to them to deepen the relationship. Overall customer management framework are taught. Participants learn to apply analytical techniques that help in segmenting, profiling and ranking customers on various metrics. They also learn to how to reduce data volume by dimension reduction techniques, handle various types of behavioral data in a structured manner for creating analytical tools for customer management.
This is a hands-on course that teaches you how to use different analytical techniques to solve different business objectives. Topics will be taught using practical workshops using software like SPSS Statistics, SPSS Modeller, JMP and Excel.
Key Takeaways
At the end of the course, participants will be able to:
- Understand the customer management life-cycle and the infrastructure to manage it.
- Apply dimension reduction techniques (PCA/Factor analysis) to identify core dimensions/factors based on various customer characteristic/ behaviour/product holding variables to arrive at efficient solution for decision making. This method also helps to manage large number of variables for other analytics techniques like prediction etc.
- Develop multivariate customer segmentation using all types of variables/features or factors to design and execute marketing strategies profitably. For example, the most profitable customer segment might receive special treatment than other customer segments
- Apply customer profiling so that customer segments are better understood, behaviourally (e.g. how much they spend per month, how long have they been buying from the business) and touchpoints they access for appropriate strategy formulation for targeted marketing for deepening relationship
- RFM analysis both for segmentation and other customer development strategies
What Will Be Covered
- Introduction to Customer Management Framework
- Customer Life Cycle
- CRM infrastructure and strategy
- Dimension Reduction Techniques
- Segmentation using Cluster Analysis
- Persona Modelling (Profiling) and RFM Analysis
Experts
Rita Chakravarti
Rita as a seasoned analytics professional has 25+ years of experience in Financial Services, Insurance and Market Research specializing in Scoring (operational & regulatory), Risk Management, Marketing Analytics, Analytics Strategy Development, Analytics Infrastructure, Analytics team managem...
Nirmal Raja Palaparthi
Nirmal is an Analytics professional with 18 years of experience in building practices from ground up in Asia. He has Co-founded and successfully exited from two Analytics companies. The first was Fractal Analytics, India’s leading third party analytics provider and the second: Mobius Innovations,...
Dave Hufton
David Hufton graduated from Kings College, Cambridge in 1975, and went on to complete an MSc in Statistics at Imperial College, London. Since then he has worked for a wide spectrum of companies during his forty years in Industry, including Aerospace companies, IT companies Government Departments ...
Eric Tham
Eric has about 15 years of analytics and data science experience in the financial services, start-ups and web analytics. Prior joining ISS, he was an Enterprise Data Scientist with Thomson Reuters and was also director of quantitative data science in a China fintech start-up with 4 million users....
Prakash Chandra Sukhwal
Prakash is an Associate Lecturer in Institute of Systems Science, National University of Singapore (NUS-ISS). He taught for various analytics modules at School of Information Systems, SMU Singapore for nearly three years prior to joining NUS-ISS. He holds a MS degree in IT in Business Analytics ...
Rajnish Tuli
16 years of experience in marketing insights and analytics across Asia, with special focus on consumer, retailing, brand research and policy development and evaluation. Expertise to integrate data from multiple sources. Extensively worked on segmentation, brand positioning, pricing decision, ROI,...
NICF- Customer Analytics at NUS Institute of Systems Science
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