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Webinar: Tips & Tricks for Customer Segmentation

Event Details

Webinar: Tips & Tricks for Customer Segmentation

Time: July 21, 2015 from 10am to 11am
Location: http://hubs.ly/y0YYFd0
Website or Map: http://hubs.ly/y0YYFd0
Phone: (619) 543-8880
Event Type: webinar
Organized By: Lisa Solomon
Latest Activity: Jul 21, 2015

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Event Description

Webinar: Tips & Tricks for Customer Segmentation

July 21, 10AM – 11AM PDT

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

 

Click to Register

 

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.

This webinar will be a step-by-step presentation that you can repeat on your own!

Included with Registration:

  • Webinar recording
  • 30 day software evaluation
  • Dataset used in presentation
  • Step-by-step instruction for you to try at home

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 targeting and segmentation and especially in targeted marketing.

 

Methods covered include:

  • Non-linear regression techniques
  • Decision Tree Techniques (CART)
  • Boosting (Stochastic Gradient Boosting)

 

Click to Register

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