Access this on-demand session to learn how data-driven segmentation helps organisations uncover meaningful patterns in the transactional and descriptive data they already hold. By going beyond basic reporting and simple RFM analysis, segmentation techniques such as cluster analysis reveal subtle groupings, behaviours and trends that traditional methods often miss.

The session demonstrates how to explore data in IBM SPSS predictive analytics software, perform cluster analysis and evaluate different solutions to identify the most useful segmentation model. You will see practical examples of how organisations use these techniques to profile stores within a retail chain, detect unusual customer behaviour and discover hidden groups within their customer or supporter base. The session also provides guidance on how to get started with your own data and how to apply segmentation models to new records over time.

Ideal for teams looking to strengthen their customer insight capabilities, this on-demand session offers a practical, accessible introduction to segmentation for more targeted decisions and more relevant services and communications.

During just one hour you will learn:

• How you can use IBM SPSS predictive analytics software to explore your data and perform cluster analysis
• How data-driven segmentation can be used to reveal the changing profiles of your customer/supporter base over time
• How to interpret the results of data clustering and find the ‘optimal’ solution
• Practical advice on how to get started with the data you already have
• How other organisations use data-driven segmentation to drive better decision-making