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Basic Predictions Library

Pre-built Predictive Models Ready For Your Use

Basic predictions are pre-generated predictive models created from third party data. Here's a list of currently available Basic Predictions:

Available on-platform now

  • State Affinity (State with Highest Predicted Affinity)
  • Predicted Gender
  • Predicted Generation
  • Predicted Education Level
  • Predicted Industry 
  • Predicted Responsiveness to Direct Mail
  • Predicted Responsiveness to Email
  • Predicted Responsiveness to SMS
  • Predicted Responsiveness to Phone
  • Predicted Responsiveness to Social Media

Available upon request

  • Predicted Affinity for Investing
  • Predicted Affinity for Children's Causes
  • Predicted Affinity for Children's Health Causes
  • Predicted Affinity for Educational Causes
  • Predicted Affinity for Catholic Causes
  • Predicted Affinity for Business Ownership
  • Predicted Affinity for Veterans' Causes
  • Predicted Affinity for Conservative Causes
  • Predicted Affinity for Liberal Causes
  • Predicted Affinity for International Aid Causes
  • Predicted Affinity for International Causes
  • Predicted Affinity for Health Causes
  • Predicted Affinity for Animal Welfare 
  • Predicted Affinity for Culinary Causes
  • Predicted Affinity for Wildlife Preservation/Conservation 
  • Predicted Affinity for Science 
  • Predicted Affinity for Arts & Culture
  • Predicted Affinity for Health Causes
  • Predicted Affinity for Local Community Causes
  • Predicted Affinity for Religious Causes
  • Predicted Affinity for Gardening
  • Predicted Level of Technology Adoption
  • Predicted Ethic Background/Affinity
  • Predicted Affinity for Agriculture

Interested in having any of the above basic predictions applied to your contact list? Get in touch with sucess@boodle.ai and we'll get back to you with next steps. 

Don't see quite what you're looking for on this list? Let us know! We can discuss potential solutions. 


What are Basic Predictions? 

Basic Predictions combine several data points in the record's matched information to arrive at a score that reflects relative known affinity. In other words, records with a score of 90 have more data points that reflect an affinity for X Instant Guidon, the records with a score of 35 have fewer, and records with a score of 0 having no data points that reflect an affinity. All records with the same score have approximately the same number of data points showing affinity.  The scores are assigned to show the relative difference. We don't provide more granular scores (89 vs 90 vs 91) because we don't feel confident enough to discriminate between records at that level of detail.