System for recommending a meal kit based upon a user food item purchase history and related methods

A meal kit recommendation server comprising:

• a processor and an associated memory configured to
• obtain a food item purchase history associated with a given user,
• obtain a current geographic location of the given user based upon a user device associated with the given user,
• obtain a preferred store location from among a plurality of store locations based upon the current geographic location;
• provide the food item purchase history and use-by dates of food ingredients as inputs to a training model and apply machine learning to generate a recommended meal kit for purchase at the preferred store location, the meal kit comprising a recipe and corresponding ones of the food ingredients portioned for the recipe, each of the food ingredients being purchasable individually in portions not corresponding to the recipe, the recommended meal kit being generated so that at least one of the corresponding food ingredients at the preferred store location is stocked at a relatively high quantity relative to other ones of the plurality of store locations and has a use-by date closer than other food ingredients relative to a current date,
• generate a digital promotion for the recommended meal kit, the digital promotion having a promotional value associated therewith,
• adjust the promotional value based upon the current location of the given user and the corresponding use dates so that the promotional value increases with distance of the given user from the preferred store location and so that the promotional value increases closer to the use-by dates relative to the current date, and
• communicate the recommended meal kit and the digital promotion to a user device associated with the given user.

A method of recommending a meal kit comprising:

• using a meal kit recommendation server to
• obtain a food item purchase history associated with a given user,
• obtain a current geographic location of the given user based upon a user device associated with the given user,
• obtain a preferred store location from among a plurality of store locations based upon the current geographic location,
• provide the food item purchase history and use-by dates of food ingredients as inputs to a training model and apply machine learning to generate a recommended meal kit for purchase at the preferred store location, the meal kit comprising a recipe and corresponding ones of the food ingredients portioned for the recipe, each of the food ingredients being purchasable individually in portions not corresponding to the recipe, the recommended meal kit being generated so that at least one of the corresponding food ingredients at the preferred store location is stocked at a relatively high quantity relative to other ones of the plurality of store locations and has a use-by date closer than other food ingredients relative to a current date,
• generate a digital promotion for the recommended meal kit, the digital promotion having a promotional value associated therewith,
• adjust the promotional value based upon the current location of the given user and the corresponding use-by dates so that the promotional value increases with distance of the given user from the preferred store location and so that the promotional value increases closer to the use-by dates relative to the current date, and
• communicate the recommended meal kit and the digital promotion to a user device associated with the given user.

A non-transitory computer readable medium for recommending a meal kit, the non-transitory computer readable medium comprising computer executable instructions that when executed by a processor cause the processor to perform operations comprising:

• obtaining a food item purchase history associated with a given user;
• obtaining a current geographic location of the given user based upon a user device associated with the given user;
• obtaining a preferred store location from among a plurality of store locations based upon the current geographic location;
• providing the food item purchase history and use-by dates of food ingredients as inputs to a training model and apply machine learning to generate a recommended meal kit for purchase at the preferred store location, the meal kit comprising a recipe and corresponding ones of the food ingredients portioned for the recipe, each of the food ingredients being purchasable individually in portions not corresponding to the recipe, the recommended meal kit being generated so that at least one of the corresponding food ingredients at the preferred store location is stocked at a relatively high quantity relative to other ones of the plurality of store locations and has a use-by date closer than other food ingredients relative to a current date;
• generating a digital promotion for the recommended meal kit, the digital promotion having a promotional value associated therewith;
• adjusting the promotional value based upon the current location of the given user and the corresponding use-by dates so that the promotional value increases with distance of the given user from the preferred store location and so that the promotional value increases closer to the use-by dates relative to the current date;
• and
• communicating the recommended meal kit and the digital promotion to a user device associated with the given user.