Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Value at Risk Segmentation and Retention Campaigns
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Value at Risk Segmentation and Retention Campaigns
Data MiningMarket Research

Value at Risk Segmentation and Retention Campaigns

Editor SDC
Editor SDC
2 Min Read
SHARE

In Propensity Based Segmentation customers are grouped according to propensity scores, such as churn scores, cross selling scores etc., as estimated by respective classification (propensity) models. Propensity scores can also be combined with other segmentation schemes to better target marketing actions.

In Propensity Based Segmentation customers are grouped according to propensity scores, such as churn scores, cross selling scores etc., as estimated by respective classification (propensity) models. Propensity scores can also be combined with other segmentation schemes to better target marketing actions. The Value at Risk segmentation scheme is developed by combining propensities with Value Segments to prioritize retention actions. 

 

Churn models estimate the churn propensity for each customer, indicating the likelihood of churn. Through simple computations and binning, customers can then be assigned to distinct groups based on their churn score. For instance, appropriate cut-off values can be selected and customers can be divided into groups of low, medium and high churn likelihood as a result of a churn model. 

 

When value segments are cross-examined with churn propensity segments we have the Value at Risk segmentation, a compound segmentation which can be used for prioritizing retention campaigns. An example of this segmentation is shown in the following figure. 

 

Six compound segments are created after combining the Low-Medium-High value segments with the Low-Medium-High risk segments (the segments of Low and Medium value segments are collapsed to final segments 5 and 6).

 

 

Clearly, segment 1 the most critical one as it contains high value customers with increased risk of terminating their relation with the organization. For this segment, retention is a high priority.

TAGGED:churn modelcrmdata mining
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

protecting patient data
How to Protect Psychotherapy Data in a Digital Practice
Big Data Exclusive Security
data analytics
How Data Analytics Can Help You Construct A Financial Weather Map
Analytics Exclusive Infographic
AI use in payment methods
AI Shows How Payment Delays Disrupt Your Business
Artificial Intelligence Exclusive Infographic
financial analytics
Financial Analytics Shows The Hidden Cost Of Not Switching Systems
Analytics Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

The Social Solutions Model

3 Min Read

Cash-hungry state agencies finding megamillions in revenue by drilling for money with Teradata

4 Min Read
data mining approach
Data Mining

How A Data Mining Approach For Search Engine Optimization Works

9 Min Read

My Interview with Ajay Ohri

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?