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Product Purchase Recommendations/Marketing Based on Recipe Database Disclosure Number: IPCOM000241710D
Publication Date: 2015-May-26
Document File: 4 page(s) / 126K

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A system and method for product purchase recommendations/marketing based on a recipe database is disclosed.

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This is the abbreviated version, containing approximately 35% of the total text.

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Product Purchase Recommendations/Marketing Based on Recipe Database

Disclosed is a system and method for product purchase recommendations/marketing based on a recipe database.

Companies are always looking for new ways to promote their products. The disclosed method enables food companies and grocery stores a new way to recommend products directly to a customer while the customer is shopping or planning their grocery list. Shoppers are provided with a tool that makes grocery shopping easier. With the disclosed method, companies can suggest products to their customers that they otherwise may not have purchased.

Effective Grocery shopping is a chore that requires time and planning. Maintaining shopping lists is a common task that nearly everyone either constantly does or has done at some point in their lives. Planning meals for a family for a week or longer often involves a significant amount of forethought and ingredient tracking. Looking up recipes, tracking which ingredients are already on-hand versus those that need to be purchased, and careful recording of a shopping list are common tasks. There are plenty of solutions to help a shopper maintain a grocery list, but this disclosed method helps reduce the time planning by dynamically creating a shopping list and recommending ingredients to purchase while shopping.

A shopping list is created and ingredients to purchase are recommended by cross

checking ingredients already purchased against a database of recipes. The method recommends purchasing specific ingredients to create the maximum number of recipes (meals). Shoppers no longer have to create and maintain detailed shopping lists. As

they select ingredients and add them to their cart, the algorithm suggests other ingredients to buy in order to maximize the number of meals they can create during the


Existing solutions allow shoppers to easily create and maintain their shopping lists, but the shopper still needs to plan all the recipes they plan to make. With this method, shoppers need only to select a few "starting ingredients" while in the store to receive

recommendations on ingredients that can be purchased to be able to create meals for the week. Even if they have not planned any meals before walking into the store, they can be confident that they can create enough meals for a week when they are finished shopping using this method.

The method could use virtually any user interface that could be exposed through any number of ways, such as, a personal mobile device, the store provided scanners for loyalty program shoppers, and wearable devices.


For example, a shopper in a grocery store has already placed the following items in their cart:

Butter, Chicken Thighs, Salt

The method takes these ingredients as input, compares them to a database of known


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recipes and makes the following recommendations:

Purchase 1 lemon to create Baked Lemon Chicken

Purchase flour and black pepper to create Fried Chicken