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Data Engineering Use Case in the Charity Sector

Predictive Analysis in Cause Marketing

Introduction:
The company provides modeling and segmentation services to improve fundraising appeals efficiency and is personalizing campaigns that present higher donor interactions and outcomes.

Challenge:

  • With over 140 million donations and over 40 million individuals, the predictive modeling demands were mounting.
  • Provide more effective and accurate predictive models to differentiate itself in a competitive market.

Solution:

  • Coming to their rescue by providing an automated, highly accurate, fast, and cost-effective predictive modeling solution, powered by AWS, their team experienced a 10% improvement in accuracy right out of the box with no fine-tuning.
  • One day for anybody in the organization to build and test a new model, down from one to two weeks before.
  • Consistent and accurate campaigns with a deeper understanding of the science.
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