Course overview
This course introduces core statistical techniques in FastStats for both descriptive and predictive data modelling. You’ll learn how to use tools like Clustering, Decision Trees, and PWE models to profile customers, segment audiences, and uncover actionable insights.
The course covers creating and interpreting model outputs, using virtual variables, and analysing model reports. Ideal for marketers and analysts looking to deepen their understanding of data-driven decision-making and apply robust models to enhance targeting, engagement, and overall campaign effectiveness.
Who is it for?
This course is ideal for advanced FastStats users who have completed FastStats Analyser Advanced.
What's included?
Full course documentation is available, and the course is entirely hands-on, with practical exercises to reinforce learning. Learners who attend the live training will receive a certificate on completion.
- Introduction – what are the Modelling tools
- Cluster – creating groups based upon shared common characteristics
- Cluster Results – reviewing the calculations including the K-Means technique
- Cluster Output – creating a Virtual Variable from the Cluster analysis results
- Decision Tree – creating a series of selection rules that characterise customers of interest
- Decision Tree Results – reviewing the calculations and result displays
- Decision Tree Output – creating a Virtual Variable from the tree nodes
- Model Reports – compares and analyses the models including PWE
- Segmentation – how to examine the movement of records between groups
Course format
This course is only available live, as part of our scheduled courses and consists of 2 online sessions of approximately 3.5 hours each. For private training please contact the training team directly.