Webinar: Tips & Tricks for Customer Segmentation, July 21

We show customer segmentation of a German banking database, using different attributes to identify segments likely to be good credit risks. We will use CART and other algorithms like gradient boosting.

Salford Systems Webinar: Tips & Tricks for Customer Segmentation

Registration: hubs.ly/y0YY6s0

*Alternative link: info.salford-systems.com/customer-segmentation-webinar

July 21, 10AM - 11AM PDT

If the time is inconvenient, please register and we will send you a recording.

Abstract: Customer segmentation is the process of dividing a client database into distinct groups of individuals who share common characteristics. Knowing how different groups of customers act is key to a marketing strategy and can be implemented using modern data mining and machine learning techniques.

In this webinar, we will demonstrate customer segmentation of a German banking database. Attributes such as credit history, employment, age, and gender will be used to identify segments likely or unlikely to be good credit risks.

CART (Classification and Regression Trees) will be used as a way to cluster similar records and extract the conditions under which these customers are classified. Other algorithms, such as gradient boosting, will be used in conjunction with the insights drawn from CART.

Who should attend:
  • Attend if you want to implement data science techniques even without a data science, statistical or programming background.
  • Attend if you want to understand why data science techniques are so important in targeted marketing.

Methods covered include:
  • Non-linear regression techniques
  • Decision Tree Techniques (CART)
  • Boosting (Stochastic Gradient Boosting)