Dynamic incentive generator

Patent metadata

Field	Value
Publication number	US-10929865-B2
Application number	US-201816205338-A
Country	US
Kind code	B2
Filing date	Nov 30, 2018
Priority date	Nov 30, 2018
Publication date	Feb 23, 2021
Grant date	Feb 23, 2021

Abstract

Embodiments provide dynamic consumer incentive generation by generating a combination discount offer that provides a total discount value to a customer in response to verifying that the customer executes a commercial activity at each of different (first and second) ones of a discount grouping plurality of businesses, in response to determining that it is probable as a function of historic purchasing data that the customer will purchase an item from the first business when they make a purchase from the second business; and allocating different portions of the total discount value as costs to the first and second businesses that have different values determined as a function of a difference between a first probability that the customer will purchase an item from the first business and a second probability that the customer will purchase an item from the second business.

First claim

What is claimed is:

1. A computer-implemented method, comprising:
a first computing node determining a plurality of discount grouping subset businesses type values by applying textual analysis to text data descriptive of a plurality of candidate businesses, and defining a discount grouping plurality of businesses as a subset of the plurality of candidate businesses that each have complementary business type values as a function of determining common linkages to purchase data values of the determined business types within consumer purchasing event knowledge base data; and
a second computing node that is linked to the first computing node within a computing environment:
generating a combination discount offer that provides a total discount value to a customer in response to verifying that the customer executes a commercial activity at each of a first business and a second business of the discount grouping plurality of businesses, and in response to determining that it is probable as a function of historic purchasing data that the customer will purchase an item from the first business when they make a purchase from the second business;
determining average spending amounts at each of the first and the second businesses by the customer as a function of the historic purchasing data;
determining a first portion of the total discount value in an amount “f(A)” according to the expression “f(A)=c(A) p(B)/(c(A) p(B)+c(B) p(A))”, wherein “p(A)” is a first probability that the customer purchases an item from the first business when the customer purchases an item from the second business, “p(b)” is a second probability that the customer purchases an item from the second business when the customer purchases an item from the first business, “c(A)” is the determined average spending amount at the first business by the customer as a function of the historic purchasing data and “c(B)” is the determined average spending amount at the second business by the customer as a function of the historic purchasing data;
allocating the first portion of the total discount value as a first cost to the first business and a second portion of the total discount value as a second cost to the second business, wherein the first portion and the second portion have different values that are determined as a function of a difference in value between the first probability that the customer will purchase an item from the first business and the second probability that the customer will purchase an item from the second business; and
pushing a message comprising the generated combination discount offer to a mobile device of the customer.

2. The method of claim 1 , further comprising:
presenting the combination discount offer for approval to at least one of the first business and the second business;
finalizing the combination discount offer for presentment to a consumer in response to receiving an approval of the presented combination discount offer from the at least one of the first business and the second business; and
terminating the combination discount offer from presentment in response to not receiving the approval of the presented combination discount offer from the at least one of the first business and the second business.

3. The method of claim 1 , further comprising:
limiting an amount of the first portion of the total discount value allocated to the first business to a total amount spent by the customer at the first business over a specified time period.

4. The method of claim 1 , wherein the commercial activity executed by the customer at the first business is selected from the group consisting of a social network service check-in activity at a geographic location of the first business, making a reservation at the first business, agreeing to pay for parking upon entry into a parking facility of the first business, entering a store of the first business, and purchasing a ticket to an event at the first business.

5. The method of claim 1 , further comprising:
defining the discount grouping subset plurality as a function of determining that the discount grouping subset businesses have geographic locations that are located proximate to a predicted travel route of a consumer to the geographic location of one of the discount grouping subset businesses.

6. The method of claim 1 , further comprising:
integrating computer-readable program code into a computer system comprising a processor, a computer readable memory in circuit communication with the processor, and a computer readable storage medium in circuit communication with the processor; and
wherein the processor executes program code instructions stored on the computer-readable storage medium via the computer readable memory and thereby performs the generating the combination discount offer, and the allocating the first portion of the total discount value as the first cost to the first business and the second portion of the total discount value as the second cost to the second business.

7. The method of claim 6 , wherein the computer-readable program code is provided as a service in a cloud environment.

8. A system, comprising:
a first processor;
a computer readable memory in circuit communication with the first processor;
a computer readable storage medium in circuit communication with the first processor; and
a second processor in circuit communication with the first processor;
wherein the first processor executes program instructions stored on the computer-readable storage medium via the computer readable memory and thereby:
determines a plurality of discount grouping subset businesses type values by applying textual analysis to text data descriptive of a plurality of candidate businesses; and
defines a discount grouping plurality of businesses as a subset of the plurality of candidate businesses that each have complementary business type values as a function of determining common linkages to purchase data values of the determined business types within consumer purchasing event knowledge base data; and
wherein the second processor executes program instructions and thereby:
generates a combination discount offer that provides a total discount value to a customer in response to verifying that the customer executes a commercial activity at each of a first business and a second business of the discount grouping plurality of businesses, and in response to determining that it is probable as a function of historic purchasing data that the customer will purchase an item from the first business when they make a purchase from the second business;
determines average spending amounts at each of the first and the second businesses by the customer as a function of the historic purchasing data;
determines a first portion of the total discount value in an amount “f(A)” according to the expression “f(A)=c(A) p(B)/(c(A) p(B)+c(B) p(A))”, wherein “p(A)” is a first probability that the customer purchases an item from the first business when the customer purchases an item from the second business, “p(b)” is a second probability that the customer purchases an item from the second business when the customer purchases an item from the first business, “c(A)” is the determined average spending amount at the first business by the customer as a function of the historic purchasing data and “c(B)” is the determined average spending amount at the second business by the customer as a function of the historic purchasing data;
allocates the first portion of the total discount value as a first cost to the first business and a second portion of the total discount value as a second cost to the second business, wherein the first portion and the second portion have different values that are determined as a function of a difference in value between the first

Assignees

• IBM

Inventors

• Johnson Benjamin L
• Pinel Florian
• Byron Donna K
• Dimascio Carmine
• Ewen Christie

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06Q30/0224 Primary

  based on user history · CPC title

• G06N20/00

  Machine learning · CPC title

• G06N5/02

  Knowledge representation; Symbolic representation · CPC title

• G06N7/005

  Physics · mapped topic