This Customer Segmentation using SAS Enterprise Miner training course covers segmentation analysis in the context of business data mining. Topics include the theory and concepts of segmentation, as well as the main analytic tools for segmentation: hierarchical clustering, -means clustering, normal mixtures, RFM cell method, and SOM/Kohonen method. The course focuses more on practical business solutions rather than statistical rigor. Therefore, business analysts, managers, marketers, programmers, and others can benefit from this course.
By attending Customer Segmentation using SAS Enterprise Miner workshop, delegates will learn to:
- Understand and apply both attitudinal and behavioral segmentation tools and techniques on customer data
- Use descriptive as well as predictive segmentation
- Profile and validate segments
- Evaluate stability of segments over time
- Assign probability of segment membership to observations
- Create segments based on product affinity
- Select variables for segmentation
- Reduce dimensionality of data before segmentation
- Analyze textual data (such as customer comments) for segmentation
- Use segmentation results to build predictive models
- Segment time-series data.
- Some prior exposure to SAS is useful, but not required.
The Customer Segmentation using SAS Enterprise Miner class is ideal for:
- Anyone who wants to learn how to segment customers based on attitude, preference, or transaction data to develop effective targeted marketing communications and promotions for each segment; develop cross-sell and up-sell strategy based on customers' purchase patterns across product classes; track and develop models for predicting customer migration from bad to good segments; or develop, deploy, and monitor comprehensive customer segmentation systems in their enterprise