This model can then be used to predict future orders based on the same pattern. This model is based on a machine learning algorithm called a recurrent neural network (RNN). RNNs are particularly well-suited for handling sequential data, such as customer orders. They learn from past data to predict future outcomes. The model’s accuracy is evaluated using a metric called precision and recall.

They have developed a proprietary algorithm that predicts the user’s dietary needs and preferences. This algorithm is based on a combination of factors, including user data, food trends, and expert knowledge. Hungryroot’s algorithm is designed to personalize the user’s experience by suggesting meals, snacks, and ingredients that align with their individual dietary needs and preferences.

This suggests that the SmartCart feature is driving customer engagement and loyalty. The company also highlights that customers who use SmartCart are more likely to spend more on their orders. This indicates that the SmartCart feature is not only driving engagement but also increasing customer spending.

In addition to providing an enhanced customer experience, SmartCart also offers a number of operational benefits. By considering inventory levels, SmartCart reduces food waste at Hungryroot facilities by 80% compared to traditional grocers. SmartCart is now available to all Hungryroot customers.