In which decade did retailers first widely adopt mathematical predictive analytics for consumer behavior forecasting?

The intersection of mathematics and retail has revolutionized how businesses make decisions and engage with customers. Predictive analytics—applying mathematical models to forecast future behavior—has become a cornerstone of modern retail strategy. While today's AI-driven approaches make headlines, the foundation of data-driven decision making in retail has fascinating historical roots. Test your knowledge about when retailers first began systematically applying mathematical models to consumer behavior!

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1950s, when operations research techniques developed during WWII were first applied to retail inventory management
1980s, when point-of-sale systems and scanner data enabled the first large-scale collection of consumer purchasing patterns
1970s, when mainframe computers allowed department stores to analyze seasonal sales trends mathematically
1990s, when the rise of e-commerce created the first digital footprints for mathematical consumer analysis