Multinational Industrial Supplier Saves $200M Per Year With AI-based Customer Churn Prediction

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A national manufacturing company wanted to build a more effective churn-prediction model – quickly. But with 10,000+ clients and vast amounts of data, they needed a new, more automated means of building their churn model. Download our case study and learn:

  • How they used dotData to identify 50+ predictive signals
  • How they used this information to recover over $200M per year in Revenue.
  • Read how they did it all 10X faster than with previous methods.

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