System for individualized customer interaction

1. A method comprising:

receiving, by a customer locator module of an individualized customer interaction system that includes (i) one or more access points that are each associated with a different location, (ii) the customer locator module, (iii) a grocery cart on which a mobile customer interface computer including a cart-mounted display is mounted, and (iv) a shopping list prediction runtime module, identification data associated with a particular access point indicating that the particular access point has wirelessly communicated with the mobile customer interface computer while the grocery cart is at a location associated with the particular access point;

determining, by the customer locator module, that the mobile customer interface computer is located within a vicinity of the particular access point based at least on receiving the identification data associated with the particular access point;

accessing, by the shopping list prediction runtime module of the individualized customer interaction system, a customer model characterizing previous food purchasing interactions with the individualized customer interaction system during which the customer purchased one or more food items;

customizing, by the shopping list prediction runtime module of the individualized customer interaction system, using the customer model, food purchasing interaction data for the food purchasing interaction, the food purchasing interaction data characterizing one or more food items available for purchase at the location associated with the previous food purchasing interactions; and

while the grocery cart is at the location associated with the particular access point, displaying, by the cart-mounted display of the mobile customer interface computer that is mounted on the grocery cart, the customized food purchasing interaction data.

2. The method of claim 1 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

analyzing, using the customer model, characteristics of a request to determine a respective probability for each of a plurality of food items available for purchase during the food purchasing interaction;

selecting one or more of the plurality of food items based on the probabilities; and

generating food item suggestions that identify the selected food items.

3. The method of claim 2 , wherein the characteristics of the request comprise data identifying one or more of a day, date, or time of the request.

4. The method of claim 1 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

analyzing, using the customer model, characteristics of a request to determine a respective probability for each of a plurality of food items available for purchase during the food purchasing interaction;

selecting one or more of the plurality of food items based on the probabilities; and

customizing promotions identified in the food purchasing interaction data to include promotions for the selected food items.

5. The method of claim 1 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

receiving, during the food purchasing interaction, a request identifying a particular brand of food items; and

determining, using the customer model, a degree of brand loyalty for the customer for the particular brand.

6. The method of claim 5 , wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to suggest that the customer purchase food items of a different brand in a same category as the particular brand.

7. The method of claim 6 , wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to customize promotions identified in the food purchasing interaction data to include promotions for the food items of the different brand in the same category as the particular brand.

8. The method of claim 5 , wherein the request identifies a particular food item in a particular product category sold by the particular brand, and wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to suggest that the customer purchase other food items in different product categories sold by the particular brand.

9. The method of claim 1 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

determining, using the customer model, a value of a price sensitivity attribute for the customer, wherein the price sensitivity attribute measures how sensitive the customer is to prices; and

determining whether or not to include promotions in the food purchasing interaction data based on the value of the price sensitivity attribute.

10. The method of claim 1 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

determining, using the customer model, a value of an opportunistic index attribute for the customer, wherein the opportunistic index attribute measures a frequency with which the customer purchases items that are on sale; and

determining whether or not to include promotions in the food purchasing interaction data based on the value of the opportunistic index attribute.

11. An individualized customer interaction system comprising:

one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

receiving, by a customer locator module of the individualized customer interaction system, identification data associated with a particular access point, from among one or more access points that are each associated with a different location, indicating that the particular access point has wirelessly communicated with a mobile customer interface computer while a grocery cart on which the mobile customer interface computer is mounted is at a location associated with the particular access point;

determining, by the customer locator module, that the mobile customer interface computer is located within a vicinity of the particular access point based at least on receiving the identification data associated with the particular access point;

accessing, by a shopping list prediction runtime module of the individualized customer interaction system and, a customer model characterizing previous food purchasing interactions with the individualized customer interaction system during which the customer purchased one or more food items;

customizing, by the shopping list prediction runtime module of the individualized customer interaction system, using the customer model, food purchasing interaction data for the food purchasing interaction, the food purchasing interaction data characterizing one or more food items available for purchase at the location associated with the previous food purchasing interactions; and

while the grocery cart is at the location associated with the particular access point, displaying, by a cart-mounted display of a mobile customer interface computer that is mounted on the grocery cart, the customized food purchasing interaction data.

12. The system of claim 11 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

analyzing, using the customer model, characteristics of a request to determine a respective probability for each of a plurality of food items available for purchase during the food purchasing interaction;

selecting one or more of the plurality of food items based on the probabilities; and

generating food item suggestions that identify the selected food items.

13. The system of claim 12 , wherein the characteristics of the request comprise data identifying one or more of a day, date, or time of the request.

14. The system of claim 11 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

analyzing, using the customer model, characteristics of a request to determine a respective probability for each of a plurality of food items available for purchase during the food purchasing interaction;

selecting one or more of the plurality of food items based on the probabilities; and

customizing promotions identified in the food purchasing interaction data to include promotions for the selected food items.

15. The system of claim 11 , wherein the customizing the food purchasing interaction data for the food purchasing interaction comprises:

receiving, during the food purchasing interaction, a request identifying a particular brand of food items; and

determining, using the customer model, a degree of brand loyalty for the customer for the particular brand.

16. The system of claim 15 , wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to suggest that the customer purchase food items of a different brand in a same category as the particular brand.

17. The system of claim 16 , wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to customize promotions identified in the food purchasing interaction data to include promotions for the food items of the different brand in the same category as the particular brand.

18. The system of claim 15 , wherein the request identifies a particular food item in a particular product category sold by the particular brand, and wherein the customizing the food purchasing interaction data for the food purchasing interaction further comprises:

determining, based on the degree of brand loyalty for the customer, whether or not to suggest that the customer purchase other food items in different product categories sold by the particular brand.

19. A non-transitory computer program product encoded on one or more computer storage devices, the computer program product comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

receiving, by a customer locator module of an individualized customer interaction system that includes (i) one or more access points that are each associated with a different location, (ii) the customer locator module, (iii) a grocery cart on which a mobile customer interface computer including a cart-mounted display is mounted, and (iv) a shopping list prediction runtime module, identification data associated with a particular access point indicating that the particular access point has wirelessly communicated with the mobile customer interface computer while the grocery cart is at a location associated with the particular access point;

determining, by the customer locator module, that the mobile customer interface computer is located within a vicinity of the particular access point based at least on receiving the identification data associated with the particular access point;

accessing, by the shopping list prediction runtime module of the individualized customer interaction system, a customer model characterizing previous food purchasing interactions with the individualized customer interaction system during which the customer purchased one or more food items;

customizing, by the shopping list prediction runtime module of the individualized customer interaction system, using the customer model, food purchasing interaction data for the food purchasing interaction, the food purchasing interaction data characterizing one or more food items available for purchase at the location associated with the previous food purchasing interactions; and

while the grocery cart is at the location associated with the particular access point, displaying, by the cart-mounted display of the mobile customer interface computer that is mounted on the grocery cart, the customized food purchasing interaction data.