Which mathematical technique is most commonly used in retail analytics to identify natural groupings of customers with similar purchasing behaviors?

In today's data-driven retail environment, mathematical models power the analytics that help businesses understand customer behavior patterns. From predictive algorithms to statistical analysis, mathematics provides the foundation for extracting meaningful insights from vast amounts of retail data. This poll tests your knowledge of how mathematical concepts are applied in modern retail analytics to transform raw data into actionable business intelligence.

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K-means clustering
Simpson's paradox analysis
Euler path optimization
Fibonacci sequence forecasting