Product Management Course with AI - IIM Ranchi

• Describe product strategy and its characteristics, and explain product managers’ pivotal role in strategy formulation.
• Discuss the importance of market research in strategy development and understand the key frameworks for product strategy, such as Ansoff’s Matrix and BCG.
• Learn how to drive strategic planning, implementation, and control processes to align product goals with business objectives.

• Understand the value creation in product development, value proposition design, and mapping. Also, explore strategies for value communication.
• Discuss the difference between traditional and contemporary value delivery models and the importance of co-creation and customer involvement.
• Describe Porter’s Value Chain and its applications, and also discuss how to align product features with customer needs.

Learners design a centralized Remote Work OS for distributed teams, create user personas, define collaboration workflows, build MVP roadmaps, identify success metrics, and develop enterprise adoption strategies.

• Discuss Innovation and its importance. Learn idea-generation techniques like Brainstorming and SCAMPER.
• Learn about idea validation, the screening process and how to develop a minimum viable product.
• Explore what intellectual property is, along with a business model canvas for product ideation.

• Understand buyer persona mapping and its importance.
• Discuss the design thinking process and its applications and explore low-fidelity prototyping techniques.
• Understand user experience design principles, interaction design, and prototyping tools. Also, learn how to create customer journey mapping for problem-solving.

• Define product strategy and its core competencies, such as Identifying and leveraging strengths.
• Understand how to build Strategic Business units (SBUs) and how to make competitive strategies for product positioning.
• Learn how to align strategy with market needs and gaps.

Learners design an AI-powered resume optimization platform, create personas, define recommendation workflows, prioritize AI features and develop monetization strategy.

• Describe the prototype development methods, tools, testing, and validation.
• Learn about Agile methodology and Scrum.
• Explore various feature prioritisation techniques like MoSCow and Kano and learn how to integrate continuous feedback into development.

• Understand go-to-market strategy, test marketing, its purpose, and implementation. Also,  explore the steps to develop and execute a GTM plan.
• Learn about the timing and execution of a product launch strategy. Also, explore the adoption and diffusion of innovations.
• Understand how to manage product launches with agile frameworks.

• Learn the difference between Market Orientation and Competitor Orientation, and understand the concept of product positioning and its best practices.
• Define Points of Parity (POP) and Points of Difference (POD) and understand how to use messaging frameworks for product success.
• Learn about the competitive strategy for emerging markets and how to refine positioning using market trends.

Learners design a healthcare-focused CRM solution, define patient engagement workflows, map integration requirements, prioritize features, create adoption strategy, define success metrics, and identify privacy/compliance considerations.

• Understand the basics of branding and how to build a strong brand identity.
• Learn to develop brand equity, designing a brand positioning and brand architecture.
• Understand the concept of brand mapping and building brand perception with visual and verbal identity in competitive markets.

• Learn about product pricing strategies, understand the reference and psychological pricing methods, and explore cost’s role in pricing decisions.
• Understand what value-based pricing, price sensitivity, price wars, and ethics in pricing are.

Learners design a smart budgeting and expense-management app, define financial workflows, build reporting and analytics capabilities, create monetization strategy, define retention loops, and identify key product metrics.

• Understand the disruptive innovation models and characteristics of disruptive products. Learn to map innovation in established markets.
• Learn how to overcome status quo bias in customers and bridge the strategic gap with innovation.
• Explore strategic planning for disruptive products and the risks involved.

• Understand the meaning of product analytics and its role and explore how it is applied to decision-making.
• Learn about the characteristics of high-quality analytics and various scientific methods for product analytics. Then, use analytics to identify the market gap.

• Get an overview of exploratory, descriptive, and casual analytics and learn about direct exploratory methods, such as Focus Groups and in-depth Interviews.
• Learn about indirect exploratory and observation methods in product development and integrating analytics into product strategy.

• Describe various measurement and scaling techniques and understand the difference between Discrete and continuous measurement scales.
• Learn how to ensure reliability and validity in data collection and design questionnaires for product research.
• Explore different data collection techniques for product metrics.

• Understand data preparation techniques and how to handle missing values using imputation techniques.
• Learn what data coding is and how to arrange data for suitable analysis. You can also explore secondary data analytics and gather insights.
• Learn about various survey analytics techniques and analyse data for product development insights.

• Explain what descriptive analytics is and understand its application in product decisions.
• Perform correlation analysis for identifying product trends and hypothesis testing.
• Describe the P-value/Significance value method for product insights. Discuss the common errors in testing and ways to avoid them.

• Discuss the difference between descriptive and predictive analytics, and explore how data can be used for predictive modeling.
• Learn to build and test various regression models while discussing their assumptions and limitations.

Learners design skill assessment flows, recommendation systems, learning pathways, engagement frameworks and user-success metrics.

• Discuss various reasons for applying analytics in product development. Learn conjoint analysis and understand the conjoint study process using Microsoft Excel.
• Calculate the importance of product features and validate a conjoint model for market fit.
• Explain the process of calculating market share for new products and demonstrate conjoint data analysis using XLSTAT.

• Discuss the importance of consumer behaviour in product management and the factors affecting it.
• Understand customer research using techniques like factor analysis and discuss the principle component of factor analysis for product insights.
• Demonstrate factor rotation for behaviour insights. Learn to create new product insights and explore the application of consumer analytics in market segmentation.

• Discuss Web analytics and its importance, and learn about A/B testing with the demo.
• Understand the customer basket analysis for cross-selling and lifetime value analysis for product retention.
• Explore digital product analytics tools and perform real-time web analytics for product optimisation.
• Learn to build effective dashboards for digital products.

• Discuss what digital marketing funnel and various display advertising techniques are, along with their best practices and principles.
• Understand what Search Engine Marketing is and how to make social media marketing strategies for products. Discuss Facebook and LinkedIn marketing strategies with differences and applications.
• Learn conversion optimisation and how to improve ROI for digital ads. Also, understand how to measure campaign effectiveness with analytics.

• Discuss the channels of distribution and the difference between direct and indirect channels.
• Understand the importance of product packaging and how to develop a distribution network for product reach.
• Understand the role of customer support in the product lifecycle and various service strategies for product growth. Learn how to handle product discontinuation, returns, and refunds.

• Understand the role of storytelling in product management and developing persuasive messaging for product success.
• Learn how to communicate through data visualisation and also understand the basics of visual storytelling for product promotion.
• Explore various storytelling tools and use them to improve customer engagement.

• Google & Fitbit: Merging Data with Wearable Technology
  Analyse Google’s acquisition of Fitbit and its strategic implications for expanding into the health and fitness market.
• Microsoft & LinkedIn: Integrating Professional Networks
  Examine Microsoft’s acquisition of LinkedIn and how it leverages the integration to enhance its enterprise solutions.
• Uber & Postmates: Expanding Delivery Services
  Investigate Uber’s acquisition of Postmates and the strategic benefits of expanding its delivery services portfolio.
• Salesforce & Slack: Transforming Business Communication
  Understand Salesforce’s acquisition of Slack and its strategy to enhance collaboration and integrate with its CRM offerings.

• Learn the use of Agentic AI and Autonomous Agents
• Work on multi-agent systems in product design
• Build AI agents for onboarding, support, and task execution
• Learn to design agentic-ai workflows and decision trees
• Learn how to evaluate metrics for autonomous behaviour

• Learn platform economics and API-first product strategies
• Design developer platforms and product ecosystems
• Understand network effects and multi-sided marketplace models
• Build platform growth strategies and ecosystem roadmaps
• Analyze real-world platform products such as AWS, Stripe, Salesforce, and Shopify

• Develop executive stakeholder management and influence skills
• Learn product investment and portfolio management frameworks
• Make strategic product continuation and sunsetting decisions
• Build executive communication and product storytelling capabilities
• Present product strategies using board-level decision-making frameworks

• Google & Fitbit: Analyze Google’s acquisition of Fitbit and its strategic implications for expansion into health and fitness.
• Microsoft & LinkedIn: Examine Microsoft’s acquisition of LinkedIn and its integration with enterprise solutions.
• Uber & Postmates: Investigate Uber’s acquisition of Postmates and strategic benefits of delivery-service expansion.
• Salesforce & Slack: Understand Salesforce’s acquisition of Slack and its strategy to enhance collaboration and integrate with CRM offerings.

• Learn how Product Managers can use AI tools for research, ideation, PRD writing, roadmap planning, and stakeholder communication.
• Create reusable AI prompts and templates for product discovery, user stories, feature prioritization, and reporting.
• Use AI to analyze customer feedback, competitor insights, survey responses, and market opportunities.
• Build practical AI-assisted workflows to improve product management productivity.

• Understand how AI features such as copilots, assistants, personalization, recommendations, and automation improve product experiences.
• Design AI-first user journeys for onboarding, support, analytics, learning, and task completion.
• Learn conversational UX, human-AI collaboration patterns, feedback loops, and trust-building mechanisms.
• Manage hallucination risk through clear UX, user controls, fallback flows, and human review.

• Identify a real product problem where AI can improve user experience or business outcomes.
• Create an AI-powered product concept with personas, PRD, user journey, roadmap, success metrics, and risk controls.
• Design simple AI workflows with prompts, inputs, outputs, and human approval points.
• Present the final AI product strategy, MVP concept, and business impact.

• Understand how AI products move from prototype to real-world launch.
• Plan release readiness with engineering, data, security, business, and customer-facing teams.
• Manage beta launches, staged rollouts, user feedback, adoption tracking, and post-launch improvements.
• Translate AI limitations into clear product requirements, user communication, and launch plans.

• Track key AI product metrics such as accuracy, relevance, latency, reliability, adoption, and user satisfaction.
• Understand risks such as hallucinations, model drift, data drift, and changing user behavior.
• Design feedback loops for issue reporting, product improvements, and quality review.
• Use dashboards and stakeholder updates to monitor AI product performance after launch.

• Define guardrails for privacy, safety, compliance, hallucinations, and sensitive use cases.
• Set up human review, escalation paths, audit trails, and governance documentation.
• Use AI to improve PM workflows such as PRDs, user stories, roadmap updates, product documentation, and stakeholder reporting.
• Build career-ready artifacts that demonstrate AI-assisted product thinking, launch planning, and responsible product execution.