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ACCA Strategic Professional · Strategic Business Leader · Machine learning, AI and robotics

Delmar Telecom wants to use AI to group its customers into segments based on usage patterns, with no predefined categories, to design new tariffs. Which approach is most appropriate?

Unsupervised learning, such as clustering, is most appropriate. The company has no predefined segments, so the algorithm must find natural groupings in unlabelled usage data. Supervised learning would require labelled categories that do not exist, and robotic process automation does not analyse patterns.

  1. AUnsupervised learning, such as clustering of unlabelled customer dataCorrect
  2. BSupervised learning using customers labelled with the correct segment
  3. CRobotic process automation of tariff letters
  4. DReinforcement learning with penalties for each lost customer

Explanation

Finding natural groupings in data with no predefined categories is the purpose of unsupervised learning such as clustering. Supervised learning needs labelled segments, which do not yet exist.

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