Which mathematical innovation revolutionized retail personalization algorithms by enabling more accurate prediction of consumer preferences across diverse product categories?

The intersection of mathematics and retail has transformed how companies approach personalization. Advanced algorithms now analyze consumer behavior to create tailored shopping experiences at unprecedented scales. This trivia question explores a significant breakthrough in retail personalization algorithms that changed how mathematical models are applied to consumer behavior prediction.

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Tensor factorization models that can simultaneously process multiple dimensions of consumer preference data
Binary classification trees that segment customers into precisely 16 distinct purchasing personas
Euclidean distance calculations that measure exact physical proximity between shoppers and products
Quadratic programming optimization that maximizes store layout efficiency based on foot traffic patterns