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ACCA Strategic Professional · Strategic Business Leader · Big data and data analytics

Verde Foods wants to group its 2 million loyalty-card customers into segments with similar purchasing behaviour, without predefined categories, so marketing can tailor offers. Which technique is most appropriate?

Clustering is most appropriate. It is an unsupervised machine learning technique that groups customers with similar buying behaviour without predefined labels, enabling tailored marketing. Classification needs labelled outcomes, while regression and time-series methods forecast values rather than discover segments.

  1. AClustering, an unsupervised machine learning techniqueCorrect
  2. BLinear regression to forecast total sales
  3. CClassification trained on labelled outcomes
  4. DTime-series forecasting of seasonal demand

Explanation

Grouping customers by similarity when no categories are predefined is clustering, an unsupervised technique. Classification needs labelled outcomes, regression predicts a numeric value, and time-series forecasting projects values over time.

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