How is this different from traditional product analytics training?

Traditional product analytics teaches you to use tools (Amplitude, Mixpanel) to track events and build dashboards. This AI-focused training teaches you to use AI to predict user behavior, automate insight discovery, and build intelligent product features. You'll learn behavioral segmentation (AI clustering), impact forecasting (AI prediction), and feedback synthesis (AI NLP) — capabilities beyond traditional event tracking.

What product analytics infrastructure do we need before this training?

Minimum: (1) Some form of event tracking (even basic GA4 or Mixpanel free tier), (2) User feedback channels (support tickets, NPS surveys, or reviews). Ideal: Product analytics platform (Amplitude, Heap, Mixpanel) with historical data. During Discovery, we'll assess your current setup and recommend quick-win improvements to maximize training value. Even basic event data enables powerful AI insights.

Can we learn to build AI product features even if we're not an AI company?

Yes! Module 4 is designed for non-AI-native products adding intelligent capabilities. You don't need a team of ML engineers. We'll show you how to: (1) Use pre-built AI APIs (OpenAI, Google AI) to add smart features quickly, (2) Build simple recommendation engines using collaborative filtering, (3) Partner with AI vendors for specialized capabilities. Goal: embed AI in your product to improve UX, not become an AI research company.

How do we avoid building AI features users don't want?

Critical concern addressed throughout the training. We teach AI feature validation: (1) Use AI analytics to identify high-frequency pain points first, (2) Prototype AI features using Wizard of Oz testing (manual behind the scenes), (3) Launch AI features to small user segments with opt-in/opt-out, (4) Measure adoption and satisfaction before full rollout. AI should solve real user problems, not be AI for AI's sake.

Is this training relevant for B2B SaaS or only consumer products?

Highly relevant for both. B2B SaaS examples in the training: AI usage insights identifying expansion opportunities, AI onboarding optimization reducing time-to-value, AI feature adoption tracking for CSM prioritization, AI feedback analysis from customer calls and support tickets. Consumer product examples: AI personalization, recommendation engines, smart notifications. We customize content to your business model during Content Customisation.

Training Solutions

TECH-PRODUCT

Cohort-basedSubsidy eligible

AI Product Development & Innovation

Product teams can deploy AI-powered user analytics, feature intelligence, and product roadmap optimization — improving retention by 20-35% and research velocity by 10x

Specialist training for product managers, designers, and innovation teams to leverage AI for user research, feature prioritization, product analytics, and AI-powered product features. Designed for SaaS companies and platforms seeking to build data-informed product roadmaps and embed AI capabilities into their offerings.

Duration3-4 days

InvestmentUSD $16,000 - $30,000

Best forProduct managers, product designers, growth PMs, and innovation leads building SaaS products, platforms, and AI-enabled features for technology companies

Start a Conversation Request Solution Brief

THE CHALLENGE

Sound familiar?

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Product decisions are based on gut feel and HiPPO opinions instead of data-driven user insights.

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We have 200+ feature requests in our backlog but no objective way to prioritize what to build next.

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User research is slow and expensive — we need AI to analyze feedback from support tickets, NPS surveys, and product reviews at scale.

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We don't know which features drive retention and which are ignored — usage data is buried in analytics tools.

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Our competitors are shipping AI features and we're falling behind, but we don't know where to start.

Trusted by enterprises across Southeast Asia

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OUTCOMES

What you'll achieve

Problems you'll solve

Product decisions driven by opinions instead of AI-powered user behavior analytics and feature intelligence
Feature prioritization lacking objective scoring based on impact, effort, and strategic alignment
User research constrained by manual interview and survey analysis instead of AI-powered feedback synthesis
Feature usage insights fragmented across analytics tools without unified product intelligence dashboards
Product innovation lagging competitors due to lack of AI-powered product capabilities

Value you'll gain

Product-Market Fit: Improve retention by 20-35% through AI-driven feature prioritization and user insights
Research Velocity: Analyze 10x more user feedback using AI sentiment analysis and theme extraction
Conversion Optimization: Increase trial-to-paid conversion by 15-30% using AI funnel analysis and intervention triggers
Feature ROI: Identify high-value features driving retention using AI usage correlation analysis
Competitive Advantage: Ship AI-powered product features differentiating your offering in the market

OUR PROCESS

How we deliver results

Step 1

Product Analytics Assessment

Audit current product analytics setup, user feedback channels, and product roadmap process to identify AI enhancement opportunities.

Step 2

Tool Configuration

Set up AI product analytics platforms (Amplitude, Mixpanel, Heap) with AI features enabled, or build custom AI models using your product data.

Step 3

Hands-On Delivery

Multi-day programme building AI-powered user segmentation, feature prioritization frameworks, feedback analysis systems, and AI product feature prototypes.

Step 4

AI Product Strategy Development

Teams develop data-driven product roadmaps using AI insights and design AI-powered features to embed in your product offering.

Step 5

Implementation & Iteration

30-day coaching to deploy AI product analytics, launch roadmap experiments, and measure impact on retention, conversion, and engagement KPIs.

What you'll receive

Product AI Readiness Assessment with analytics gap analysis
AI-driven product roadmap with data-backed feature prioritization
AI user analytics dashboards and behavioral segmentation models
Prototypes of AI-powered product features ready for development
Individual learning certificates and competency assessments
30-day post-programme coaching and experiment support

Best for

Product managers, product designers, growth PMs, and innovation leads building SaaS products, platforms, and AI-enabled features for technology companies

IS THIS RIGHT FOR YOU?

Finding the right fit

This is ideal for you if...

SaaS product teams seeking to build data-driven roadmaps using AI user insights
Product managers overwhelmed by feature requests lacking objective prioritization frameworks
Growth teams optimizing conversion funnels and retention using AI behavioral analytics
Products seeking competitive differentiation through AI-powered features and personalization

Consider another option if...

Products with zero event tracking or user data (set up basic analytics first)
Teams seeking general product management training rather than AI-specific capabilities
Organizations unwilling to make data-driven decisions (cultural resistance to analytics)

See yourself in the list above?

Let's Talk

CURRICULUM

What you'll learn

2 days total

Use AI to segment users, analyze behavior patterns, and identify power users, at-risk users, and expansion opportunities.

What you'll be able to do

Build AI-powered user segmentation clustering users by behavior patterns (not just demographics)
Analyze user journeys to identify critical activation moments and conversion drop-off points
Create cohort retention analysis tracking user engagement trends over time
Implement AI propensity scoring predicting which users will upgrade, churn, or refer others
Design product analytics dashboards showing real-time user segment health and trends