Predicting marketing campaigns using customer-specific response probabilities and response values

• US 20040204975A1
• Filed: 06/27/2003
• Published: 10/14/2004
• Est. Priority Date: 04/14/2003
• Status: Abandoned Application

• Current Assignee: SAP AG (SAP SE)
• Original Assignee: SAP AG (SAP SE)
• Inventors: Witting, Thomas
• Application Number:
  US10/608,895
• Publication Number:
  US 20040204975A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements

Abstract

Methods and systems for assigning customers to steps in marketing campaigns. An assignment module assigns and reassigns the customers to the marketing activities. An evaluation module determines a predicted goal value of the marketing campaign for each assignment. The assignment module does not reassign a customer to a marketing activity that the customer has previously been assigned to. An execution module may execute campaign steps by performing marketing activities, and a response detection module may detect responses from the customers. The responses may be used in determining subsequent steps of the campaign. Creating sample target groups representative of the customers that are predicted to respond to a prior campaign step. The sample target group(s) may be used for predicting the outcome of subsequent campaign steps directed at the sample target group. Predicting outcomes of marketing campaigns using customer-specific response probabilities and response values.

Claims

1. A method of predicting outcomes of marketing campaigns, the method comprising:

determining a response probability for each of a plurality of customers, the customers being intended targets of a marketing campaign;

determining a response value for each of the customers that indicates a predicted value of a response to the marketing campaign by the customer; and

predicting an outcome of the marketing campaign using the response probability and the response value.

2. The method of claim 1, wherein the predicted value is at least one selected from the group consisting of predicted revenue from the customer and predicted profit from the customer.

3. The method of claim 1, wherein the predicted value is a predicted response cost associated with the customer.

4. The method of claim 1, wherein the predicted value is a predicted cost of contacting the customer in the marketing campaign.

5. The method of claim 1, wherein the response value is determined using a purchase history of the customer.

6. The method of claim 1, wherein a purchase history is not available for a customer, further comprising identifying at least one similar customer for which a purchase history is available and using the at least one similar customer'"'"'s purchase history to determine the response value.

7. The method of claim 1, wherein the marketing campaign is to be directed also at additional customers for which no response value is determined, further comprising using a default response value for the additional customers in predicting the outcome of the marketing campaign.

8. The method of claim 7, wherein the default response value is an average determined from responses to past marketing campaigns.

9. The method of claim 1, wherein the marketing campaign comprises at least first and second campaign steps, and wherein predicting the outcome of the marketing campaign further comprises:

using the response probabilities for the plurality of customers to predict a number of responses to be received if the first campaign step were performed toward the plurality of customers;

selecting a target group of customers from the plurality of customers using the response probabilities, the target group being substantially equal to the predicted number of responses; and

predicting an outcome of performing the second campaign step toward the target group.

10. The method of claim 9, wherein the target group initially is not equal to the predicted number of responses, further comprising adjusting the target group to be equal to the predicted number of responses.

11. The method of claim 9, wherein at least one campaign step in the marketing campaign comprises a plurality of alternative campaign elements, further comprising assigning the customers to the campaign elements using an optimizing algorithm.

12. The method of claim 11, wherein the optimizing algorithm assigns and reassigns the customers to the campaign elements while evaluating the predicted outcome of the marketing campaign, but does not reassign a customer to a campaign element to which the customer has previously been assigned.

13. The method of claim 9, wherein the response value is determined for a particular marketing step in the marketing campaign.

14. The method of claim 13, wherein the marketing step comprises contacting the customer by at least one selected from the group consisting of email, website advertisement, letter, telephone, fax and personal contact.

15. A system for predicting outcomes of marketing campaigns, the system comprising:

program instructions comprising a response prediction module that, when executed by a processor, determines a response probability for each of a plurality of customers, the customers being intended targets of a marketing campaign; and

program instructions comprising an evaluation module that, when executed by a processor, determines a response value for each of the customers that indicates a predicted value of a response to the marketing campaign by the customer, and that predicts an outcome of the marketing campaign using the response probability and the response value.

16. The system of claim 15, wherein the response value is determined using a purchase history of the customer.

17. The system of claim 15, wherein a purchase history is not available for a customer, wherein the response value is determined using a purchase history of at least one similar customer.

18. The system of claim 15, wherein the marketing campaign is to be directed also at additional customers for which no response value is determined, and wherein the evaluation module uses a default response value for the additional customers in predicting the outcome of the marketing campaign.

19. The system of claim 18, wherein the default response value is an average determined from responses to past marketing campaigns.

20. The system of claim 15, wherein at least one campaign step in the marketing campaign comprises a plurality of alternative campaign elements, further comprising:

program instructions comprising an assignment module that, when executed by a processor, assigns the customers to the campaign elements using an optimizing algorithm.

21. The system of claim 20, wherein the assignment module assigns and reassigns the customers to the campaign elements while evaluating the predicted outcome of the marketing campaign, but does not reassign a customer to a campaign element to which the customer has previously been assigned.

22. Computer software, tangibly embodied in at least one of a computer-readable medium and a propagated carrier signal, for predicting outcomes of marketing campaigns, the software comprising instructions to perform operations comprising:

determines a response probability for each of a plurality of customers, the customers being intended targets of a marketing campaign;

determines a response value for each of the customers that indicates a predicted value of a response to the marketing campaign by the customer; and

predicts an outcome of the marketing campaign using the response probability and the response value.