NUS
 
ISS
 

Analytics for Product Excellence

Analytics and AI for product innovation, demand forecasting and product activation. 

Overview

Part of -
Duration 4 days
Course Time
Enquiry Please contact ask-iss@nus.edu.sg for more details.
Successful products are built by combining consumer insights, analytics and AI to identify market opportunities, optimise product portfolios and accelerate business growth. As markets become increasingly competitive, organisations need professionals who can translate data into product innovation, investment decisions and commercial success. 

Analytics for Product Excellence is a practical, hands-on 4-day course designed for professionals who want to leverage consumer analytics, AI and machine learning to develop innovative products, optimise product portfolios and drive profitable growth. Through real-world case studies and hands-on exercises, participants will learn how to validate product concepts, forecast demand and and use AI to evaluate product strategies, compare alternatives and support product decisions.

By the end of the course, participants will be equipped to translate consumer insights into evidence-based product decisions that improve innovation, maximise revenue and accelerate business growth. 

Key Takeaways

By the end of this course, participants will be able to:

  • Identify product innovation opportunities using consumer insights, AI and data-driven business model design.
  • Apply demand forecasting and portfolio analytics to prioritise product investments.
  • Validate product concepts using experimentation and casual analytics techniques
  • Leverage AI and recommendation systems to personalise product experiences and drive product adoption.
  • Use Generative AI to generate, compare and evaluate product and portfolio strategies.
  • Translate product analytics into evidence-based product decisions and actionable strategies that improve innovation, commercialisation and business growth.



Who Should Attend

This course is designed for professionals involved in product management, innovation, marketing and digital transformation who wish to leverage analytics and AI to drive product innovation, commercialisation and business growth. It is particularly suitable for product managers, innovation and product marketing professionals, business analysts, digital transformation practitioners and strategy consultants.


Pre-requisitesParticipants should have a basic understanding of business data and an interest in applying analytics and AI to customer-related challenges. Prior completion of Data-Driven Consumer Business Models is preferred. Some familiarity with basic statistics and analytics as well as Python programming would be beneficial.


What to Bring

No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.

If you are bringing a laptop, please see below for the tech specs:

Minimum

Recommended

Operating Systems

• Windows 7, 8, 10 or
• Mac OS

Laptop running the latest
version of either Windows or
Mac OS

System Type

32-bit

64-bit

Memory

8 GB RAM

16+ GB RAM

Hard Drive

256 GB disk size

Others

• An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops) 
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out)

DirectX 10 graphics card for graphics hardware acceleration






What Will Be Covered

  • Product Innovation Analytics
    • Apply consumer insights, AI and experimentation techniques to identify market opportunities, develop new product concepts and validate business models while evaluating strategic product alternatives and investment decisions.
  • Portfolio Planning Analytics
    • Use demand forecasting, portfolio analytics and simulation to optimise product investments and resource allocation through AI-assisted portfolio decision making.
  • Product Activation Analytics
    • Leverage recommendation systems, Generative AI and Retrieval-Augmented Generation (RAG) to personalise customer experiences, recommend next-best product actions and accelerate product adoption



Fees & Subsidies

SkillsFuture Singapore (SSG) Funding 2026 (Effective 1 July)

Fee ComponentFull Course Fees

Singapore Citizens & PRs Aged 21 Years and Above (70% Funding Support)

Singapore Citizens Aged 40 Years and Above (90% Funding Support)Enhanced Training Support for SMEs (ETSS) (90% Funding Support)
Full Course FeeS$3,800.00

S$3,800.00

S$3,800.00S$3,800.00
SSG Funding-

S$2,660.00

S$2,660.00S$2,660.00
Nett Course FeeS$3,800.00

S$1,140.00

S$1,140.00S$1,140.00
9% GST on Nett Course FeeS$342.00

S$102.60

S$102.60S$102.60
Additional Funding if Eligible Under Various Schemes-

-

S$760.00S$760.00
Total Nett Course Fee Payable, Including GSTS$4,142.00

S$1,242.60

S$482.60S$482.60

 

Note:

  1. SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
  2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
  3. SME fees are applicable only to participants who are sponsored by small and medium enterprises.
  4. SSG funding is subjected to availability.



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Preparing for Your Course

NUS-ISS Course Registration Terms and Conditions

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NUS-ISS and Learner’s Commitment and Responsibilities

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WIFI Access

WIFI access will be made available to participants.

Venue

NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615

Click HERE for directions to NUS-ISS

In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

Course Confirmation

All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

General Enquiry

Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.




Course Resources

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