Systems and methods for tailoring marketing

• US 9,881,309 B2
• Filed: 03/11/2013
• Issued: 01/30/2018
• Est. Priority Date: 03/13/2012
• Status: Active Grant

• Current Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Chau, Lee, Fischer, Terrence, Mavromatis, Anthony, Smith, Andrew K., Varadachary, Venkat, Yuan, Henry
• Primary Examiner(s): Wu, Rutao
• Assistant Examiner(s): Tsui, Alfred H
• Application Number:
  US13/794,374
• Publication Number:
  US 20130246187A1
• Time in Patent Office: 1,786 Days
• Field of Search: None
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06Q 20/209 Specified transaction journal output feature, e.g. printed receipt or voice output
• CPC Class Codes: G06Q 20/384 using social networks
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0222 During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0236 Incentive or reward received by requiring registration or ID from user
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06Q 50/12 Hotels or restaurants

Abstract

The systems and methods described herein may be used to recommend an item to a consumer. The methods may comprise determining, based on a collaborative filtering algorithm, a consumer relevance value associated with an item, and transmitting, based on the consumer relevance value, information associated with the item to a consumer. A collaborative filtering algorithm may receive as an input at least one of: a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, a share of wallet, and/or the like.

Claims

1. A method, comprising:

creating, by a computer-based system and via an offer creation interface, a first offer for a first social media channel based on a first merchant rule of a merchant to award existing loyal customers, wherein the first offer is formatted for delivery in the first social media channel;

restricting, by the computer-based system and based on the creating, the first offer by removing offer data disfavored by a consumer;

associating, by the computer-based system and in response to the restricting the first offer, a delivery timeframe for the first offer in the first social media channel based on a preference defined by the merchant having a merchant system;

creating, by the computer-based system and via the offer creation interface, a second offer for a second social media channel based on a second merchant rule of the merchant to acquire new customers, wherein the second offer is formatted for delivery in the second social media channel;

restricting, by the computer-based system and based on the creating, the second offer by removing offer data disfavored by a consumer;

linking, by the computer-based system and in response to the restricting the second offer, a first social media profile to a transaction account profile, wherein the first social media profile is associated with the first social media channel;

linking, by the computer-based system and in response to the linking the first social media profile, a second social media profile to a transaction account profile, wherein the second social media profile is associated with the second social media channel;

determining, by the computer-based system and based on social data and in reply to the linking, how to display at least one of the first offer or the second offer to the consumer, wherein the determining comprises;

including criteria with the first offer, wherein the criteria includes keywords and metadata;

capturing social data about the merchant from the first social media channel via an API interfacing with the social media channel;

comparing, by the computer-based system and based on matching rules, the criteria with the social data from the social media channel about the merchant to determine a social media association between the criteria for the first offer and the social media data about the merchant, wherein the first offer is for use at the merchant;

increasing the rank of the first offer based on the extent of the association of the social data to the criteria;

more prominently displaying the first offer based on the increased rank of the first offer;

determining, by the computer-based system and based on a collaborative filtering algorithm, a consumer relevance value associated with the at least one of the first offer or the second offer,

wherein the collaborative filtering algorithm identifies offers that are relevant to one or more of the consumers,

wherein the consumer relevance value indicates the relevance of the first offer to the consumer,

wherein the consumer relevance value is based upon a plurality of offer to offer similarity values, content of the offer, an industry of the offer, a consumer profile, a transaction history associated with the consumer, social data, demographic data, clickstream data, and consumer feedback data,

wherein the offer to offer similarity value is based on pairings of offers at least one of occurring most often or are most strongly correlated,

wherein the offer to offer similarity value is determined based on at least one of a co-occurrence method or a cosine method,

wherein the offer to offer similarity value is between a plurality of merchants,

wherein the offer to offer similarity value is determined by comparing record of charges (ROCs) of a plurality of consumers at the plurality of merchants,

wherein merchant activity information corresponds to the merchant;

generating, by the computer-based system and using the consumer relevance value, an offer matrix having coefficients indicating that the offers are associated,

wherein each of the coefficients of the offer matrix comprises a record associated with one or more offers;

monitoring, by the computer-based system with a real time system and based on the determining, real time information about the consumer via global positioning system data from a web client of the consumer;

analyzing, by the computer-based system and with the real time system and based on the monitoring, the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the computer-based system and in response to the analyzing, the consumer relevance value based on and in response to the analyzing the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the computer-based system and based on the consumer relevance value, the first offer;

transmitting, by the computer-based system and based on the consumer relevance value, at least one of the first offer or the second offer to at least one of the first social media channel or the second social media channel, wherein the channel is based on a preference provided by a consumer.

2. The method of claim 1, wherein the collaborative filtering algorithm assigns the consumer relevance value based on social data, clickstream data, a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, a share of wallet, consumer feedback, information associated with an item usage, and information associated with a product usage.

3. The method of claim 1, further comprising generating, by the computer-based system, a ranked list of offers based upon a plurality of consumer relevance values.

4. The method of claim 1, further comprising transmitting, by the computer-based system, a ranked list of offers to at least one of the first social media channel or the second social media channel based on the preference provided by a user.

5. The method of claim 1, wherein the creating a first offer includes customizing the first offer based upon a merchant goal of the merchant, wherein the merchant goal comprises at least one of:

an acquisition goal and a loyalty goal.

6. The method of claim 1, wherein the creating a first offer includes customizing the first offer based on a business rule, wherein the business rules includes a holiday, a time of day, the consumer traveling, a merchant location in relation to a consumer location, and consumer feedback.

7. An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a computer-based system, cause the computer-based system to be capable of performing operations comprising:

creating, by the computer-based system and via an offer creation interface, a first offer for a first social media channel based on a first merchant rule of a merchant to award existing loyal customers, wherein the first offer is formatted for delivery in the first social media channel;

restricting, by the computer-based system and based on the creating, the first offer by removing offer data disfavored by a consumer;

associating, by the computer-based system and in response to the restricting the first offer, a delivery timeframe for the first offer in the first social media channel based on a preference defined by the merchant having a merchant system;

creating, by the computer-based system and via the offer creation interface, a second offer for a second social media channel based on a second merchant rule of the merchant to acquire new customers,

wherein the second offer is formatted for delivery in the second social media channel;

restricting, by the computer-based system and based on the creating, the second offer by removing offer data disfavored by a consumer;

linking, by the computer-based system and in response to the restricting the second offer, a first social media profile to a transaction account profile, wherein the first social media profile is associated with the first social media channel;

linking, by the computer-based system and in response to the linking the first social media profile, a second social media profile to a transaction account profile, wherein the second social media profile is associated with the second social media channel;

determining, by the computer-based system and based on social data and in reply to the linking, how to display at least one of the first offer or the second offer to the consumer, wherein the determining comprises;

including criteria with the first offer, wherein the criteria includes keywords and metadata;

capturing social data about the merchant from the first social media channel via an API interfacing with the social media channel;

comparing, by the computer-based system and based on matching rules, the criteria with the social data from the social media channel about the merchant to determine a social media association between the criteria for the first offer and the social media data about the merchant, wherein the first offer is for use at the merchant;

increasing the rank of the first offer based on the extent of the association of the social data to the criteria;

more prominently displaying the first offer based on the increased rank of the first offer;

determining, by the computer-based system and based on a collaborative filtering algorithm, a consumer relevance value associated with the at least one of the first offer or the second offer,

wherein the collaborative filtering algorithm identifies offers that are relevant to one or more of the consumers,

wherein the consumer relevance value indicates the relevance of the first offer to the consumer,

wherein the consumer relevance value is based upon a plurality of offer to offer similarity values, content of the offer, an industry of the offer, a consumer profile, a transaction history associated with the consumer, social data, demographic data, clickstream data, and consumer feedback data,

wherein the offer to offer similarity value is based on pairings of offers at least one of occurring most often or are most strongly correlated,

wherein the offer to offer similarity value is determined based on at least one of a co-occurrence method or a cosine method,

wherein the offer to offer similarity value is between a plurality of merchants,

wherein the offer to offer similarity value is determined by comparing record of charges (ROCs) of a plurality of consumers at the plurality of merchants,

wherein merchant activity information corresponds to the merchant;

generating, by the computer-based system and using the consumer relevance value, an offer matrix having coefficients indicating that the offers are associated,

wherein each of the coefficients of the offer matrix comprises a record associated with one or more offers;

monitoring, by the computer-based system with a real time system and based on the determining, real time information about the consumer via global positioning system data from a web client of the consumer;

analyzing, by the computer-based system and with the real time system and based on the monitoring, the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the computer-based system and in response to the analyzing, the consumer relevance value based on and in response to the analyzing the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the computer-based system and based on the consumer relevance value, the first offer;

transmitting, by the computer-based system and based on the consumer relevance value, at least one of the first offer or the second offer to at least one of the first social media channel or the second social media channel, wherein the channel is based on a preference provided by a consumer.

8. The article of claim 7, wherein the collaborative filtering algorithm receives as an input of at least one of:

a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, a share of wallet, consumer feedback, information associated with an item usage, or information associated with a product usage.

9. The article of claim 7, further comprising generating, by the computer-based system, a ranked list of offers based upon a plurality of consumer relevance values.

10. The article of claim 7, further comprising transmitting, by the computer-based system, a ranked list of offers to at least one of the first social media channel or the second social media channel based on the preference provided by a user.

11. The article of claim 7, further comprising re-ranking, by the computer-based system, a ranked list of offers based upon a merchant goal, wherein the merchant goal comprises at least one of:

an acquisition goal and a loyalty goal.

12. The article of claim 7, further comprising re-ranking, by the computer-based system, an offer in response to:

at least one of a holiday, a time of day, the consumer traveling, a merchant location in relation to a consumer location, or consumer feedback.

13. A system comprising:

a processor,

a tangible, non-transitory memory configured to communicate with the processor,

the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to be capable of performing operations comprising;

creating, by the processor and via an offer creation interface, a first offer for a first social media channel based on a first merchant rule of a merchant to award existing loyal customers, wherein the first offer is formatted for delivery in the first social media channel;

restricting, by the processor and based on the creating, the first offer by removing offer data disfavored by a consumer;

associating, by the processor and in response to the restricting the first offer, a delivery timeframe for the first offer in the first social media channel based on a preference defined by the merchant having a merchant system;

creating, by the processor and via the offer creation interface, a second offer for a second social media channel based on a second merchant rule of the merchant to acquire new customers, wherein the second offer is formatted for delivery in the second social media channel;

restricting, by the processor and based on the creating, the second offer by removing offer data disfavored by a consumer;

linking, by the processor and in response to the restricting the second offer, a first social media profile to a transaction account profile, wherein the first social media profile is associated with the first social media channel;

linking, by the processor and in response to the linking the first social media profile, a second social media profile to a transaction account profile, wherein the second social media profile is associated with the second social media channel;

determining, by the processor and based on social data and in reply to the linking, how to display at least one of the first offer or the second offer to the consumer, wherein the determining comprises;

including criteria with the first offer, wherein the criteria includes keywords and metadata;

capturing social data about the merchant from the first social media channel via an API interfacing with the social media channel;

comparing, by the processor and based on matching rules, the criteria with the social data from the social media channel about the merchant to determine a social media association between the criteria for the first offer and the social media data about the merchant, wherein the first offer is for use at the merchant;

increasing the rank of the first offer based on the extent of the association of the social data to the criteria;

more prominently displaying the first offer based on the increased rank of the first offer;

determining, by the processor and based on a collaborative filtering algorithm, a consumer relevance value associated with the at least one of the first offer or the second offer,

wherein the collaborative filtering algorithm identifies offers that are relevant to one or more of the consumers,

wherein the consumer relevance value indicates the relevance of the first offer to the consumer,

wherein the consumer relevance value is based upon a plurality of offer to offer similarity values, content of the offer, an industry of the offer, a consumer profile, a transaction history associated with the consumer, social data, demographic data, clickstream data, and consumer feedback data,

wherein the offer to offer similarity value is based on pairings of offers at least one of occurring most often or are most strongly correlated,

wherein the offer to offer similarity value is determined based on at least one of a co-occurrence method or a cosine method,

wherein the offer to offer similarity value is between a plurality of merchants,

wherein the offer to offer similarity value is determined by comparing record of charges (ROCs) of a plurality of consumers at the plurality of merchants, wherein merchant activity information corresponds to the merchant;

generating, by the processor and using the consumer relevance value, an offer matrix having coefficients indicating that the offers are associated,

wherein each of the coefficients of the offer matrix comprises a record associated with one or more offers;

monitoring, by the processor with a real time system and based on the determining, real time information about the consumer via global positioning system data from a web client of the consumer;

analyzing, by the processor and with the real time system and based on the monitoring, the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the processor and in response to the analyzing, the consumer relevance value based on and in response to the analyzing the offer parameters, the delivery time frame, the offer to offer similarity value, the offer matrix and the real time information about the consumer;

adjusting, by the processor and based on the consumer relevance value, the first offer; and

transmitting, by the processor and based on the consumer relevance value, at least one of the first offer or the second offer to at least one of the first social media channel or the second social media channel, wherein the channel is based on a preference provided by a consumer.

14. The system of claim 13, wherein the collaborative filtering algorithm receives as an input of at least one of:

a transaction history associated with the consumer, a demographic of the consumer, a consumer profile, a type of transaction account, a transaction account associated with the consumer, a period of time that the consumer has held a transaction account, a size of wallet, a share of wallet, consumer feedback, information associated with an item usage, or information associated with a product usage.

15. The system of claim 13, further comprising generating, by the processor, a ranked list of the offers based upon a plurality of consumer relevance values.

16. The system of claim 13, further comprising transmitting, by the processor, a ranked list of offers to at least one of the first social media channel or the second social media channel based on the preference provided by a user.

17. The system of claim 13, further comprising re-ranking, by the processor, a ranked list of offers based upon a merchant goal, wherein the merchant goal comprises at least one of:

an acquisition goal and a loyalty goal.