Which mathematical clustering technique was first widely adopted by major retailers in the early 2000s for advanced customer segmentation and targeted marketing campaigns?

In today's data-driven retail environment, mathematics plays a crucial role in customer analytics and marketing campaign optimization. Statistical models and algorithms help retailers extract meaningful insights from vast amounts of customer data. This poll tests your knowledge about a significant mathematical technique that revolutionized how retailers segment their customers and personalize their marketing strategies.

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K-means clustering
Hierarchical clustering
DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
Gaussian mixture models