System for individualized customer interaction
A method and system for using individualized customer models when operating a retail establishment is provided. The individualized customer models may be generated using statistical analysis of transaction data for the customer, thereby generating sub-models and attributes tailored to customer. The individualized customer models may be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning (such as selecting parameters for a promotion or simulating results of a promotion), to customer interaction (such as providing a shopping list or providing individualized promotions).
1. A computer-implemented method comprising:
determining, by one or more computers, whether a particular customer hoarded products of a particular product category during a past promotion at a retail establishment;
based on determining that the particular customer hoarded the products of the particular product category during the past promotion, classifying, by the one or more computers, a behavior of the particular customer with respect to the hoarding of the products during the past promotion, from among a plurality of possible types of hoarding behaviors, based at least on transaction data from before, during and after the past promotion;
determining, by the one or more computers, to offer a future promotion to the particular customer based on classifying the behavior of the particular customer with respect to the hoarding of the products during the past promotion from among a plurality of possible types of hoarding behaviors; and
in response to the determining to offer the future promotion to the particular customer, offering the future promotion to the particular customer.
2. The method of claim 1 , wherein the past promotion was a sale or a coupon offering.
3. The method of claim 1 , wherein the determining whether a particular customer hoarded products of a particular product category during a past promotion at a retail establishment comprises determining whether the particular customer acquired a greater number of the products of the particular product category during the past promotion than the particular customer would have acquired had the past promotion not occurred.
4. The method of claim 1 , wherein the classifying the behavior of the particular customer during the past promotion comprises:
determining a total amount that the particular customer actually spent on the products of the particular product category during a time period that includes the past promotion and a period of time after the past promotion;
determining a total amount that the particular customer would have spent on the products of the particular product category during the time period had the past promotion not occurred; and
comparing the total amount that the particular customer actually spent to the total amount that the particular customer would have spent.
5. The method of claim 4 , wherein the classifying the behavior of the particular customer during the past promotion comprises:
classifying the behavior of the particular customer during the past promotion from among a plurality of possible types of hoarding behaviors when the total amount that the particular customer actually spent is greater than the total amount that the particular customer would have spent without the past promotion.
6. The method of claim 4 , comprising:
determining an individual replenishment rate for the particular customer and for the particular product category; and
selecting a duration of the period of time after the past promotion based on the individual replenishment rate for the particular customer and for the particular product category.
7. The method of claim 4 , comprising:
determining an amount of revenue lost during the past promotion by the retail establishment for the particular customer based on comparing the total amount that the particular customer actually spent to the total amount that the particular customer would have spent.
8. The method of claim 7 , comprising:
comparing the amount of revenue lost during the past promotion by the retail establishment for the particular customer, to a predefined unacceptable loss threshold; and
wherein the behavior of the particular customer during the past promotion is classified from among the plurality of possible types of hoarding behaviors when the amount of revenue lost does not exceed the predefined unacceptable loss threshold.
9. The method of claim 1 , wherein the classifying the behavior of the particular customer during the past promotion from among a plurality of possible types of hoarding behaviors comprises:
determining a total amount that the particular customer actually spent on the products of the particular product category during a time period that includes a period of time after the past promotion only;
determining a total amount that the particular customer would have spent on the products of the particular product category during the time period had the past promotion not occurred; and
comparing the total amount that the particular customer actually spent to the total amount that the particular customer would have spent.
10. A nontransitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
determining whether a particular customer hoarded products of a particular product category during a past promotion at a retail establishment;
based on determining that the particular customer hoarded the products of the particular product category during the past promotion, classifying a behavior of the particular customer with respect to the hoarding of the products during the past promotion, from among a plurality of possible types of hoarding behaviors, based at least on transaction data from before, during and after the past promotion;
determining to offer a future promotion to the particular customer based on classifying the behavior of the particular customer with respect to the hoarding of the products during the past promotion from among a plurality of possible types of hoarding behaviors; and
in response to the determining to offer the future promotion to the particular customer, offering the future promotion to the particular customer.
11. The nontransitory computer storage medium of claim 10 , wherein the classifying the behavior of the particular customer during the past promotion comprises:
determining a total amount that the particular customer actually spent on the products of the particular product category during a time period that includes the past promotion and a period of time after the past promotion;
determining a total amount that the particular customer would have spent on the products of the particular product category during the time period had the past promotion not occurred; and
comparing the total amount that the particular customer actually spent to the total amount that the particular customer would have spent.
12. The nontransitory computer storage medium of claim 11 , wherein the classifying the behavior of the particular customer during the past promotion comprises:
classifying the behavior of the particular customer during the past promotion from among a plurality of possible types of hoarding behaviors when the total amount that the particular customer actually spent is greater than the total amount that the particular customer would have spent without the past promotion.
13. The nontransitory computer storage medium of claim 11 , wherein the operations comprise:
determining an individual replenishment rate for the particular customer and for the particular product category; and
selecting a duration of the period of time after the past promotion based on the individual replenishment rate for the particular customer and for the particular product category.
14. The nontransitory computer storage medium of claim 11 , wherein the operations comprise:
determining an amount of revenue lost during the past promotion by the retail establishment for the particular customer based on comparing the total amount that the particular customer actually spent to the total amount that the particular customer would have spent.
15. A system comprising:
one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
determining whether a particular customer hoarded products of a particular product category during a past promotion at a retail establishment;
based on determining that the particular customer hoarded the products of the particular product category during the past promotion, classifying a behavior of the particular customer with respect to the hoarding of the products during the past promotion, from among a plurality of possible types of hoarding behaviors, based at least on transaction data from before, during and after the past promotion;
determining to offer a future promotion to the particular customer based on classifying the behavior of the particular customer with respect to the hoarding of the products during the past promotion from among a plurality of possible types of hoarding behaviors; and
in response to the determining to offer the future promotion to the particular customer, offering the future promotion to the particular customer.
16. The system of claim 15 , wherein the plurality of types of hoarding behaviors comprises a good hoarding behavior type, a bad hoarding behavior type, and a neutral hoarding behavior type.