Classifications are the most frequently used—and most useful—prediction types.

Classifications are predictions that separate data into groups. Binary Classification produces “yes-no” or “in-out” answers when there are only two choices. Multi-Class Classification applies when there are three or more possibilities and shows probabilities for each.

Binary Examples

  • Churn – Which customers are in danger of leaving? If you knew, you could implement targeted retention tactics such as special offers or customer service outreach.
  • Conversion – Which prospects are most likely to be ready to move to the next stem in the buying cycle? Knowing means focusing sales resources on the best leads.
  • Risk – Which populations are likely to experience negative outcomes? Understanding helps guide actions to mitigate risks.

Multi-Class Examples

  • Cross-Sell/Up-Sell – Which customers are most likely to buy which additional products or services? Targeting them with the right offers lifts sales with high efficiency.
  • Personalization – Which content will resonate with which person? Optimizing websites, social media, and email is easy when you know.
  • Ad Targeting – Which prospects are most likely to respond to your multiplicity of ads and media? Spending is more effective when you know your audiences.

The take-away: Classifications are among the most accessible and highest-return prediction types for AutoML. Predictions on each row include not only the classes, but the probabilities associated with each. Think of a burning classification question and Squark can help you begin predicting right away.

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