Which pioneering algorithm, introduced in the late 1990s, revolutionized retail personalization and is still considered the foundation of many modern recommendation systems?

Personalization algorithms have transformed how retailers engage with customers. These sophisticated systems analyze purchase history, browsing behavior, demographic data, and even social media activity to create tailored shopping experiences. As retailers compete for customer attention, the technology behind personalized recommendations has become increasingly sophisticated - but how much do you know about its evolution and impact on the retail landscape?

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Collaborative Filtering (used in early Amazon recommendations)
Neural Network Embedding (used in early Walmart systems)
Random Forest Classification (used in early Target campaigns)
Gradient Boosting Trees (used in early Best Buy recommendations)