Which machine learning technique is most commonly used by food retailers to predict customer churn based on purchasing patterns of perishable goods?

Machine learning is transforming how food retailers understand their customers. Advanced algorithms now analyze purchasing patterns to predict future buying behavior, recommend products, and reduce customer churn. But how much do you know about these AI applications in the food industry? Test your knowledge about how retailers are using machine learning to keep customers coming back for more!

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Random Forest algorithms, which can identify complex patterns between purchase frequency, basket variety, and seasonal food preferences
Simple linear regression, which focuses exclusively on the correlation between spending amount and customer retention
Reinforcement learning systems that directly interact with customers to influence their purchasing decisions
Convolutional neural networks primarily designed to analyze images of food products