Most product managers already have access to more data than they know what to do with — dashboards full of numbers, KPIs updated in real time, and analytics platforms tracking every click. Yet many still make decisions on instinct, because raw data and genuine insight are not the same thing. Data-Driven Product Management is the discipline that closes that gap, turning dashboards and metrics into decisions a team can actually defend. The Data-Driven Product Management Training Course, delivered by The British Academy for Training and Development, is built for product professionals who want their roadmap grounded in evidence rather than the most persuasive voice in the room.

This course treats data as a decision-making tool, not a reporting obligation. Participants learn how to build dashboards that surface what actually matters instead of burying it in vanity metrics, how to choose KPIs and product metrics that genuinely reflect business and customer health, and how to run A/B testing that produces clean, trustworthy results rather than misleading ones. The course also looks closely at retention — often the single most honest signal a product has — and how to read it alongside acquisition and engagement data to understand the full picture. Participants leave with a practical, hands-on approach to using analytics throughout the

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

• Apply Data-Driven Product Management principles to guide roadmap and prioritisation decisions
• Build dashboards that highlight meaningful signals instead of vanity metrics
• Select and track KPIs and product metrics that genuinely reflect product health
• Design and interpret A/B tests that produce reliable, actionable results
• Analyse retention data to understand genuine long-term product performance
• Distinguish correlation from causation when interpreting analytics
• Translate data and customer insights into confident, defensible product decisions
• Build a sustainable analytics practice that informs decisions continuously, not occasionally

Target Group

• Product managers and product owners seeking to strengthen data-driven decision-making
• Data analysts and business intelligence professionals working closely with product teams
• Growth and marketing professionals relying on product metrics and retention data
• Heads of product embedding analytics into product strategy and prioritisation
• UX researchers and customer insight professionals working alongside product data
• Professionals transitioning from intuition-led to evidence-led product management

• Why Data-Driven Product Management Matters
• The difference between having data and genuinely using it to decide
• Common traps: vanity metrics, dashboard overload, and analysis paralysis
• Building Dashboards That Actually Inform
• Structuring dashboards around decisions, not just available data
• Avoiding dashboards nobody actually checks or trusts
• Choosing the Right KPIs and Product Metrics
• Selecting KPIs that reflect genuine business and customer health
• Aligning product metrics with strategic goals rather than convenient numbers
• Running Effective A/B Testing
• Designing tests with clear hypotheses and statistically sound structure
• Avoiding common A/B testing mistakes that produce misleading results
• Understanding and Improving Retention
• Reading retention data as one of the most honest signals of product health
• Identifying where and why customers disengage over time
• From Analytics to Product Decisions
• Translating dashboard insight into prioritised, defensible roadmap decisions
• Balancing quantitative data with qualitative customer insight
• Avoiding Common Data Interpretation Mistakes
• Distinguishing correlation from causation in product analytics
• Recognising when data is misleading rather than simply incomplete
• Communicating Data-Driven Decisions to Stakeholders
• Presenting analytics and KPI-based decisions clearly to leadership
• Defending data-backed trade-offs under stakeholder pressure
• Building a Sustainable Analytics Practice
• Embedding regular data review into everyday product routines
• Keeping dashboards, KPIs, and testing practices relevant as the product evolves