Behavioural Analytics Masterclass
- Design an event tracking plan with consistent naming, properties and user identifiers.
- Analyse conversion funnels and identify the steps with the largest drop-off.
- Build cohort retention tables and interpret retention curves.
- Segment users by behaviour and link segments to service or product actions.
- Design and evaluate an A/B test with a clear hypothesis, sample size and success metric.
- Apply consent, minimisation and anonymisation practices consistent with local personal data protection requirements.
- Foundations of Behavioural Analytics
- Behavioural versus attitudinal data
- Key behavioural metrics
- Analytics platforms and data sources
- Tracking Design
- Event taxonomies and properties
- User identity across channels
- Data quality validation
- Funnels, Paths and Retention
- Funnel analysis and drop-off diagnosis
- Path and journey analysis
- Cohort retention analysis
- Behavioural Segmentation
- Engagement and value segments
- Churn risk indicators
- Personalisation opportunities
- Experiments and Behavioural Insights
- A/B test design and analysis
- Nudges and choice architecture
- Ethical use of behavioural insights
- Privacy and Operationalising Insights
- Consent and data minimisation
- Gulf personal data protection requirements
- Embedding insights into product and service decisions
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Program Professional Framework
Behavioural Analytics Masterclass
Program Overview
Knowing what users and customers actually do across apps, websites and service channels is often more revealing than what they report in surveys. This masterclass covers behavioural analytics from data to action: event tracking design, funnels, cohort retention, path analysis, behavioural segmentation, controlled experiments and A/B testing, insights from behavioural economics, and privacy-respecting data practice under Gulf personal data protection laws. Participants learn to turn behavioural signals into design and service improvements.
Learning Outcomes
- ✓Design an event tracking plan with consistent naming, properties and user identifiers.
- ✓Analyse conversion funnels and identify the steps with the largest drop-off.
- ✓Build cohort retention tables and interpret retention curves.
- ✓Segment users by behaviour and link segments to service or product actions.
- ✓Design and evaluate an A/B test with a clear hypothesis, sample size and success metric.
- ✓Apply consent, minimisation and anonymisation practices consistent with local personal data protection requirements.
Target Audience
- Digital product managers and owners
- Customer experience and digital channel analysts
- Marketing analytics specialists
- UX researchers and designers
Detailed Program Modules
01Foundations of Behavioural Analytics
- Behavioural versus attitudinal data
- Key behavioural metrics
- Analytics platforms and data sources
02Tracking Design
- Event taxonomies and properties
- User identity across channels
- Data quality validation
03Funnels, Paths and Retention
- Funnel analysis and drop-off diagnosis
- Path and journey analysis
- Cohort retention analysis
04Behavioural Segmentation
- Engagement and value segments
- Churn risk indicators
- Personalisation opportunities
05Experiments and Behavioural Insights
- A/B test design and analysis
- Nudges and choice architecture
- Ethical use of behavioural insights
06Privacy and Operationalising Insights
- Consent and data minimisation
- Gulf personal data protection requirements
- Embedding insights into product and service decisions
Training Methodology
Applied Project & Assessment
Applied Project
Participants analyse behavioural data for a digital service: tracking plan review, funnel and retention analysis, behavioural segments, an A/B test proposal with sample size and a privacy checklist, presented as an improvement roadmap.
Assessment
Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.


