A team of researchers from the University of Maryland (UMD) has developed a new computational model that can predict which retail consumer packaged goods (CPGs) a consumer will choose based on their past purchases. The model, called the "Discrete Choice Model," is based on the discrete choice theory, commonly used in economics to model consumer behavior.

One of the key reasons for developing this model was to predict product preferences for Advil and Excedrin, two popular pain relievers. By studying the choice patterns of consumers, researchers aimed to gain insights into the factors influencing their decisions and potentially develop more targeted marketing strategies.

The Discrete Choice Model considers various attributes associated with the products, including price, brand loyalty, product features, store environment, and the consumer's preferences for these attributes. The model is also designed to account for factors like the consumer's level of knowledge and engagement with the products.

To evaluate the model's accuracy, researchers conducted experiments where consumers were provided with hypothetical scenarios and asked to choose between different brands of pain relievers. The results showed that the Discrete Choice Model was able to predict the consumers' choices with remarkable accuracy, demonstrating its effectiveness in capturing consumer preferences and choice patterns.

This new computational model has various potential applications in the marketing and retail industries. By understanding the factors influencing product choices, businesses can develop more targeted marketing campaigns and make informed decisions about product design, pricing strategies, and store layouts. Ultimately, this can lead to increased sales and a better understanding of consumer behavior.