About the Course
Organizations want product results they can prove, not just describe. In product analytics and metrics training, that means showing adoption, activation, retention, feature engagement, and revenue contribution through a coherent metric system built around KPI trees, North Star Metric thinking, cohort analysis, and experiment readouts. To do that well, you need to demonstrate product instrumentation literacy, metric definition discipline, funnel analysis capability, dashboard interpretation, and decision-ready reporting in a way that product, engineering, and leadership can all trust.
This course turns scattered analytics knowledge into a working system for product decisions. You will practice defining event schemas, building KPI trees, reading Amplitude or Mixpanel-style product dashboards, designing cohort and retention views, interpreting A/B test results, and writing product performance summaries that leadership can act on. You will also be introduced to advanced concepts such as predictive modeling for product behavior and AI-assisted analytics workflows at an operational awareness level, so you can frame their use without overstating implementation depth. This course teaches product analytics and metrics through practical exercises so you can measure feature adoption, identify drop-off, and communicate product impact with evidence.
Product teams often work with incomplete instrumentation, competing stakeholder priorities, and limited time to clean up historical data. This training is designed for professionals who must make sound product decisions under those constraints, using realistic datasets, pragmatic metric definitions, and workflows that fit cross-functional product environments rather than idealized analytics setups. It also addresses the pressure of digital-first reporting, where dashboards and metric narratives must be accurate, concise, and defensible across product reviews and executive meetings.
Target Audience
This course is designed for professionals who need to define product metrics, interpret user behavior, and report product impact with confidence.
- Product Managers responsible for KPI trees and roadmap decisions
- Product Analysts tracking activation, retention, and feature adoption
- Growth Product Managers measuring experimentation outcomes
- UX Researchers interpreting behavioral signals from product journeys
- Data Analysts building product dashboards and cohort views
- Analytics Managers governing metric definitions across product teams
- Digital Product Owners aligning feature releases to usage data
- Customer Insights Managers translating product data into action
- Engineering Managers supporting event instrumentation and data quality
- Executive Product Leaders reporting product performance to leadership
Course Objectives
This course equips you to plan, execute, and measure product analytics and metrics initiatives that improve product decisions, strengthen metric governance, and support strategic reporting.
- Assess current product performance using KPI trees, North Star Metric logic, and funnel analysis.
- Apply cohort analysis and segmentation to identify activation, retention, and drop-off patterns.
- Design event tracking requirements and a product metric dictionary for reliable reporting.
- Build dashboard views in tools such as Amplitude, Mixpanel, or Power BI.
- Calculate key product metrics including activation rate, retention, conversion, and churn.
- Evaluate experiments and feature releases using A/B testing results and statistical significance.
- Navigate stakeholder expectations around metric definitions, instrumentation quality, and reporting cadence.
- Synthesize findings into a product performance report and action plan for roadmap decisions.
Requirements & Prerequisites
Participants should have working familiarity with product management or product analysis concepts, basic spreadsheet use, and comfort reading dashboards or simple charts. No coding is required for completion, although prior exposure to SQL, event tracking concepts, or experimentation terminology will help you move faster through the applied exercises. The course is suitable for intermediate professionals who want to strengthen product analytics and metrics capability rather than start from zero.
Local Application and Business Return in your market
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn product analytics and metrics aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on calculation exercise using activation rate, retention curves, and cohort tables.
- Scenario simulation on a feature launch with competing KPI trade-offs.
- Diagnostic review using a KPI tree, event taxonomy, and metric dictionary checklist.
- Stakeholder mapping exercise for product, engineering, analytics, and leadership reporting.
- Case study analysis from SaaS, mobile apps, marketplaces, and digital platforms.
- Group workshop producing a dashboard wireframe and product metrics brief.
- Reflection exercise comparing current reporting habits against experimentation and instrumentation benchmarks.
Upcoming Sessions
Next available dates worldwide
No international sessions scheduled
Certification
Recognized credentials that advance your career
Participants who complete the Product Analytics and Metrics Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Effective Learning & Skill Development
- Build expertise with structured, outcome-driven learning.
- Equip individuals and teams with skills that grow with industry needs.
- Reinforce learning through real-world scenarios, case studies and practical exercises.
Career Growth & Professional Advancement
- Apply what you learn with a proven methodology that ensures lasting impact.
- Develop immediately usable skills that translate directly into workplace success.
- Gain the expertise needed for career advancement and leadership roles.
Training Optimization & Learning Excellence
- Tailor training to industry-specific challenges and organizational goals.
- Use data-driven insights and automation to enhance training effectiveness.
- Evaluate progress and ensure long-term learning success.
Tools and platforms relevant to this field
Examples local teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
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Amplitude Analytics AmplitudeUsed to analyze product events, retention, funnels, and cohorts so teams can understand how users move through a product.
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Mixpanel MixpanelUsed for event-based product analytics, funnel analysis, and segmentation to measure feature adoption and user behavior.
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Pendo PendoUsed to combine product analytics with in-app guides and feedback so teams can connect usage insights to product decisions.
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Google Analytics GoogleUsed for web and app measurement to track acquisition, engagement, and conversion signals that feed product reporting.
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Looker Google CloudUsed to build governed dashboards and metrics layers for leadership reporting and cross-functional self-service analytics.
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Tableau SalesforceUsed to visualize product performance trends and communicate KPI movement to executives and adjacent teams.
