SEO, SEA & analytics
Advanced Google Analytics 4: make data reliable and analyze with AI
Check the quality of your data collection, analyze in depth and use AI to diagnose and recommend.
- Duration
- 7 h · 1 day
- Level
- Advanced
- Format
- On site · Remote · Blended
- Max. group size
- 12 participants
Overview
This day is for those who already use Google Analytics 4. It starts with the technical verification of the implementation and data reliability, continues with advanced analysis using explorations, segments and audiences, and ends with using AI to structure a diagnosis and formulate recommendations, with its limits.
Who this program is for
- Web analysts
- Marketing managers
- Analytics consultants
Prerequisites
- First practice with Google Analytics 4
Learning objectives
- Check data reliability before analyzing
- Check events, conversions and traffic sources
- Understand modeling, consent and collection limits
- Analyze with funnels, journeys and comparisons
- Create segments and audiences
- Use AI to diagnose and recommend, knowing its limits
Detailed curriculum
2 modules · 7 h · 1 day
Day 1
Make data reliable
30% theory · 70% practice
- Validate the technical implementation
- Consistency of events, conversions and sources
- Modeling and consent mode
- Collection limits and data exports
- Quality control protocol
🛠 Hands-on workshops
Collection audit1.5 h
Audit the reliability of a GA4 property.
✅ Deliverable : An audit report
Advanced analysis and AI
30% theory · 70% practice
- Explorations: funnels, journeys, comparisons
- Segments, audiences and triggers
- Connect AI to data and ask good questions
- Structure a diagnosis and recommendations
- Limits: privacy, interpretation, errors
🛠 Hands-on workshops
Assisted diagnosis2 h
Produce a diagnosis with the help of AI, then validate it.
✅ Deliverable : A validated diagnosis
Tools and technologies
ChatGPTGoogle Analytics 4Google Tag Manager
Teaching methods
- Alternating input sessions and workshops on real accounts and sites
- Case studies and diagnostic exercises
- Sharing of best practices between participants
- Feedback and personalized recommendations
Assessment
- Hands-on exercises on a real or fictional site
- Case studies corrected as a group
- Knowledge-check quiz
Required equipment
- A computer with an internet connection
- Access to a GA4 property with data
Resources provided
- Course materials and repository of corrected exercises
Career outcomes
- A data quality control protocol
- A structured diagnosis with recommendations
- Rules for using AI in analytics