Portfolio Modeling and Campaign Optimization

• US 20090254413A1
• Filed: 04/07/2008
• Published: 10/08/2009
• Est. Priority Date: 04/07/2008
• Status: Abandoned Application

• Current Assignee: Liberty Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: American Express Travel Related Services Company, Inc. (American Express Company)
• Inventors: Chang, Shen Y., Maynard, Justin Andrew, Malik, Anuja, Chang, Lulinyu Laura, Haggerty, Kathleen B., Varadachary, Venkat
• Application Number:
  US12/098,897
• Publication Number:
  US 20090254413A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0211 Determining the effectiveness of discounts or incentives
• CPC Class Codes: G06Q 30/0215 Including financial accounts
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0229 Multi-merchant loyalty card systems

Abstract

In an embodiment of the invention, historical data related to multiple members of a customer loyalty program is gathered. A set of loyalty behavior models is developed for an individual member of the loyalty program is developed based on the historical data. For each campaign in a plurality of marketing campaigns, at least one combination of offers is inserted into each loyalty behavior model to output a plurality of net profit scores for the individual member, wherein each combination of offers outputs a separate net profit score. For each campaign in the plurality of campaigns, a combination of offers having the highest net profit score for the campaign is selected. The campaign having the highest net profit score of the plurality of campaigns is selected, and marketing materials for the selected campaign and combination of offers is transmitted to the individual member.

Claims

1. A method for managing a customer loyalty program for an individual member of the customer loyalty program, comprising:

gathering historical data related to multiple members of the customer loyalty program;

developing a set of loyalty behavior models for the individual member based on the historical data;

for each campaign in a plurality of campaigns, inserting at least one combination of offers into each loyalty behavior model to output a plurality of net profit scores for the individual member, wherein each combination of offers outputs a separate net profit score;

for each campaign in the plurality of campaigns, selecting the combination of offers having the highest net profit score for the campaign, wherein the net profit score for the selected combination of offers becomes the campaign'"'"'s net profit score;

selecting the campaign having the highest net profit score of the plurality of campaigns; and

transmitting marketing materials for the selected campaign and combination of offers to the individual member.

2. The method of claim 1, wherein the historical data includes data received as a result of at least one prior campaign.

3. The method of claim 2, wherein the data received as a result of at least one prior campaign includes data related to responses of multiple consumers to at least one specific offer.

4. The method of claim 2, wherein the data received as a result of at least one prior campaign includes at least one of campaign enrollment fee data, duration data, campaign enrollment date data, a response indicator, response channel data, threshold data, and cap data.

5. The method of claim 1, wherein the historical data related to multiple members of the customer loyalty program includes at least one of loyalty program enrollment data, reward-related data, customer profile data, historical transaction data, spend capacity data, spend ability data, and program value proposition data.

6. The method of claim 1, wherein an offer in the combination of offers is at least one of a campaign fee offer, a duration offer, a channel to respond offer, a threshold offer, and a cap offer.

7. A method for targeting a customer loyalty program member for a marketing campaign, comprising:

gathering historical data related to multiple customer loyalty program members;

developing a set of loyalty behavior models for a given campaign based on the historical data;

developing a set of baseline behavior models based on the historical data;

for each individual of a plurality of individuals, inserting at least one combination of offers of the individual into each loyalty behavior model for the given campaign, wherein a separate campaign net profit score is output for each individual;

for each individual of the plurality of individuals, inserting at least one attribute of the individual into the baseline behavior model, wherein a separate baseline net profit score is output for each individual;

comparing a highest campaign net profit score for each individual to the baseline net profit score for the individual;

from the plurality of individuals, selecting at least one individual having a campaign net profit score that is higher than the baseline net profit score for the individual; and

transmitting marketing materials for the given campaign to the selected at least one individual.

8. The method of claim 7, wherein the historical data includes data received as a result of at least one prior campaign.

9. The method of claim 8, wherein the historical data further includes data related to customer loyalty program members who did not participate in the at least one prior campaign.

10. The method of claim 9, wherein developing the baseline behavior model comprises developing the baseline behavior model based on the data related to customer loyalty program members who did not participate in the at least one prior campaign.

11. The method of claim 7, wherein the baseline net profit score is a measure of the expected profitability of the individual if the individual does not participate in the given campaign.

12. The method of claim 7, wherein the at least one attribute is one of the group consisting of:

loyalty program enrollment status, historical transaction, spend ability, program value proposition, age, gender, location, spend capacity, income, and spend ability.

13. A method for targeting a customer loyalty program member for a new type of marketing campaign, comprising:

gathering historical data related to multiple customer loyalty program members;

developing a set of baseline behavior models based on the historical data;

for each individual of a plurality of individuals, inserting at least one attribute of the individual into the set of baseline behavior models, wherein a separate baseline net profit score is output for each individual;

ranking each individual based on the baseline net profit score output for the individual;

from the plurality of individuals, selecting at least one individual based on the ranked baseline net profit scores; and

transmitting marketing materials for the new type of campaign to the selected at least one individual.

14. A system for managing a customer loyalty program for an individual member of the customer loyalty program, comprising:

a database configured to store historical data related to multiple members of the customer loyalty program;

a modeling system configured to develop a set of loyalty behavior models for the individual member based on the historical data in the database;

a processing system configured to evaluate, for each campaign in a plurality of campaigns, each loyalty behavior model using at least one permutation of offers and output a plurality of net profit scores for the individual member, wherein the processing system outputs a separate net profit score for each permutation of offers;

a first comparator system configured to compare the net profit scores output by the processing system and identify and output, for each campaign in the plurality of campaigns, the permutation of offers having the highest net profit score for the campaign and assign the net profit score for the selected combination of offers as the campaign'"'"'s net profit score;

a second comparator system configured to compare the assigned net profit scores of the plurality of campaigns and identify and output the campaign having the highest net profit score of the plurality of campaigns; and

a marketing system configured to transmit to the individual member marketing materials corresponding to the campaign and permutation of offers output by the second comparator system.

15. The system of claim 14, wherein the processing system is configured to

evaluate each loyalty behavior model using at least one permutation of offers to output a plurality of net profit scores for the individual member, wherein each permutation of offers results in a separate model net profit score, and wherein the processing system is further configured to output a combination of the plurality of model net profit scores as a campaign net profit score.

16. The system of claim 14, wherein the database is configured to store data received as a result of at least one prior campaign.

17. The system of claim 16, wherein the data received as a result of at least one prior campaign includes data related to responses of multiple consumers to at least one specific offer.

18. The system of claim 16, wherein the data received as a result of at least one prior campaign includes at least one of campaign enrollment fee data, duration data, campaign enrollment date data, a response indicator, response channel data, redemption pricing data, reward points offer data, threshold data, and cap data.

19. The system of claim 14, wherein an offer in the permutation of offers is at least one of a campaign fee offer, a duration offer, a channel to respond offer, a redemption pricing offer, a reward points offer, a threshold offer, and a cap offer.

20. A system for targeting a customer loyalty program member for a marketing campaign, comprising:

a database configured to store historical data related to multiple customer loyalty program members;

a first modeling system configured to develop a set of loyalty behavior models for a given campaign based on historical data in the database;

a second modeling system configured to develop a set of baseline behavior models based on historical data in the database;

a first processing system configured to evaluate, for each individual in a plurality of individuals, each loyalty behavior model using at least one combination of offers of the individual and output a campaign net profit score for each individual;

a second processing system configured to process, for each individual in the plurality of individuals, the baseline behavior model using at least one attribute of the individual and output a baseline net profit score for each individual;

a comparator system configured to compare the campaign net profit score for each individual with the baseline net profit score for the individual and identify and output at least one individual having a campaign net profit score higher than the corresponding baseline net profit score; and

a marketing system configured to transmit marketing materials for the given campaign to the at least one individual output by the comparator.

21. The system of claim 20, wherein the historical database is configured to store data received as a result of at least one prior campaign.

22. The system of claim 21, wherein the historical database is further configured to store data related to customer loyalty program members who did not participate in the at least one prior campaign, and wherein the second modeling system configured to develop a baseline behavior model utilizes the data related to customer loyalty program members who did not participate in the at least one prior campaign.

23. The system of claim 22, wherein the baseline net profit score is a measure of the expected profitability of the individual if the individual does not participate in the given campaign.

24. The system of claim 22, wherein the at least one attribute is one of the group consisting of:

customer profile, spend capacity, spend ability, and program value proposition.

25. A system for targeting a customer loyalty program member for a marketing campaign, comprising:

a database configured to store historical data related to multiple customer loyalty program members;

a modeling system configured to develop a set of baseline behavior models based on historical data in the database;

a processing system configured to process, for each individual in the plurality of individuals, the baseline behavior model using at least one attribute of the individual and output a baseline net profit score for each individual; and

a ranking system configured to rank the baseline net profit score.