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Foundations of Product Strategy ümit

Defining Product Strategy and Strategic Alignment üm

Outcome-Driven Objectives and Hypothesis-Driven Planning

Market Intelligence and Opportunity Discovery ümit

Market Research Essentials for Product Strategy

Competitive and Ecosystem Analysis

Insight to Strategy: Value Proposition and Positioning

Customer Insight Synthesis and Jobs-to-Be-Done

Crafting Value Propositions and Strategic Positioning

Prioritization, Portfolio Bets, and Roadmapping

Prioritization Frameworks and Data-Driven Decision Making

Strategic Roadmaps and Portfolio Governance

Validation, Metrics, and Feedback Loops

Experiment Design and Evidence Generation

Measuring Product-Market Fit and Sustainable Advantage

Capstone Application

Capstone: Build a Coherent Product Strategy

Knowledge Checks

Quiz: Foundations and Alignment

Quiz: Market Research and Segmentation

Quiz: Competitive Analysis and Positioning

Quiz: Prioritization and Roadmapping

Quiz: Validation, Metrics, and PMF

Course Wrap-Up and Feedback

Survey: Course Feedback

Turn uncertainty into advantage with Data-Driven Product Strategy: Segmentation, Value Propositions, Prioritization. This hands-on course teaches product leaders and cross-functional teams how to translate market signals into clear strategic choices—who to serve, what to build, how to price, and when to bet. You will learn to connect company mission and portfolio goals to measurable outcomes, then use rigorous market research, segmentation, and competitive analysis to uncover high-leverage opportunities. From Jobs-to-be-Done insights to pricing hypotheses and positioning statements, you’ll craft value propositions that win. You’ll also master prioritization frameworks like RICE and expected value, build outcome-based roadmaps, and set governance rhythms that keep strategy and execution aligned. Finally, you’ll design experiments tied to North Star metrics and guardrails, measure product-market fit with retention and unit economics, and establish feedback loops for continuous strategy. By the end, you will produce a cohesive, defensible product strategy and a validation plan that reduces risk while accelerating impact.

Data-Driven Product Strategy: Segmentation, Value Propositions, Prioritization

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            <p>Turning insight into advantage requires more than a backlog of features. This course equips product leaders and cross-functional teams to build data-driven strategies that compound over time—anchored in clear segmentation, sharp value propositions, and rigorous prioritization. You will learn how to connect company mission and business models to product bets through strategic alignment, define North Star metrics and outcome-based objectives, and plan with explicit hypotheses that reduce uncertainty before scaling. Throughout, we emphasize evidence-weighted decision making, so you can move confidently from market signal to portfolio choice without succumbing to research theater or feature thrash.</p>

<p>We start with the foundations of product strategy, distinguishing strategy from vision, roadmaps, and execution while studying case snapshots of compounding versus drifting strategies. Next, you’ll develop market intelligence: when and how to use interviews, surveys, ethnography, and desk research; quantify TAM, SAM, and SOM bottom-up; and segment markets by jobs-to-be-done, needs, behaviors, and willingness to pay. You’ll synthesize customer insights into causal narratives, map jobs across functional, emotional, and social dimensions, and translate them into opportunity solution trees. From there, you will craft precise value propositions and strategic positioning—including pricing and packaging choices grounded in willingness-to-pay—forming narratives that align product, marketing, and go-to-market.</p>

<p>The course then turns to prioritization, portfolio bets, and roadmapping. You will compare frameworks such as RICE, ICE, expected value, and cost of delay; balance horizons across core, adjacent, and transformational initiatives; and score opportunities with explicit confidence in research quality. We cover sequencing, platform dependencies, option value, and capacity planning, as well as governance rhythms like QBRs, stage gates, and kill criteria to keep portfolios adaptive. Finally, you’ll design robust experiments—concierge tests, prototypes, A/B tests, and quasi-experiments—tie leading and lagging indicators to strategy, and use guardrail metrics to prevent local optimizations.</p>

<p>To ensure real-world application, the capstone challenges you to select a target segment, articulate jobs-to-be-done and unmet needs, craft a value proposition and positioning, build a quantitative prioritization model and outcome-based roadmap, and define validation experiments with clear success metrics and stop rules. Knowledge checks throughout reinforce foundations, market research, competitive analysis, prioritization, and measurement. By the end, you will have a coherent, defensible product strategy and a repeatable operating system for sensing, learning, and deciding—so your teams can ship what matters and win where it counts.</p>
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