Assigning customers to activities in marketing campaigns

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 evaluation module may be coupled to a response prediction module for making the determination. The assignment module does not reassign a customer to a marketing activity that the customer has previously been assigned to. If the assignment module identifies an assignment that leads to an optimum goal value, this assignment may be used when executing the campaign. 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.

We claim:  
     
         1 . A method of predicting values of marketing campaigns, the method comprising: 
 making an assignment of customers to marketing activities of a marketing campaign, the customers being intended targets of the marketing campaign;    making subsequent assignments of the customers to the marketing activities, each subsequent assignment comprising a reassignment of at least one of the customers to a different marketing activity, wherein a customer is not reassigned to a marketing activity to which it has previously been assigned; and    determining a first predicted value of the marketing campaign for each assignment of the customers to the marketing activities.    
     
     
         2 . The method of  claim 1 , wherein the first predicted value is selected from the group consisting of predicted costs of the marketing campaign, predicted profits of the marketing campaign, a predicted number of customers responding to the marketing activities, and combinations thereof.  
     
     
         3 . The method of  claim 1 , wherein the first predicted value is a predicted number of customers responding to the marketing activities, wherein determining the predicted number comprises at least in part using a response prediction model.  
     
     
         4 . The method of  claim 1 , further comprising defining a constraint for the marketing campaign and rejecting assignments of the customers to the marketing activities that are inconsistent with the constraint.  
     
     
         5 . The method of  claim 4 , wherein the constraint is selected from the group consisting of a limitation on the marketing campaign, a limitation on the marketing activities, a predicted number of customers responding to the marketing activities, and combinations thereof.  
     
     
         6 . The method of  claim 4 , wherein the constraint is selected from the group consisting of marketing campaign budget, predicted marketing campaign revenue, predicted marketing campaign profits, predicted marketing campaign costs, and combinations thereof.  
     
     
         7 . The method of  claim 4 , wherein a marketing activity comprises an offer to be made to at least some of the customers through a communication channel, wherein the constraint is one selected from the group consisting of a limitation on the communication channel, a limitation on the offer, and combinations thereof.  
     
     
         8 . The method of  claim 4 , wherein the constraint comprises that a particular customer not be assigned to a particular marketing activity.  
     
     
         9 . The method of  claim 4 , further comprising using the first predicted value for at least one of the assignments to select a second constraint for a marketing activity.  
     
     
         10 . The method of  claim 4 , wherein there are a plurality of constraints for the marketing campaign, further comprising using the first predicted value for at least one of the assignments to select one of the constraints to be eliminated from the marketing campaign.  
     
     
         11 . The method of  claim 1 , further comprising identifying the marketing activity having least impact on the first predicted value.  
     
     
         12 . The method of  claim 1 , further comprising removing the assignment of a customer from all marketing activities such that the customer is not assigned to any of the marketing activities.  
     
     
         13 . The method of  claim 1 , further comprising storing the assignments of the customers to the marketing activities in a binary map, wherein a flag can be set in the binary map for each possible assignment of the customers to the marketing activities.  
     
     
         14 . The method of  claim 1 , further comprising identifying a particular assignment of the customers to the marketing activities that has a maximum first predicted value.  
     
     
         15 . The method of  claim 14 , further comprising using the particular assignment to create a target group of customers.  
     
     
         16 . The method of  claim 15 , further comprising executing said marketing activity toward the target group.  
     
     
         17 . The method of  claim 14 , wherein a plurality of the assignments of the customers to the marketing activities have the maximum first predicted value, further comprising identifying a second predicted value of the marketing campaign and determining which of the plurality of assignments has a greater second predicted value.  
     
     
         18 . A system for predicting values of marketing campaigns, the system comprising: 
 data structures comprising customer objects representing customers that are intended targets of a marketing campaign;    data structures representing marketing activities of the marketing campaign that are to be directed at the customers;    program instructions comprising an assignment module that, when executed by a processor, makes an assignment of the customer objects to the marketing activities and that makes subsequent assignments of the customer objects to the marketing activities by reassigning at least one of the customer objects to a different marketing activity, wherein the assignment module does not reassign a customer object to a marketing activity to which the customer object has previously been assigned; and    program instructions comprising an evaluation module that, when executed by a processor, determines a predicted value of the marketing campaign for each assignment of the customer objects to the marketing activities.    
     
     
         19 . The system of  claim 18 , further comprising program instructions comprising a response prediction module that, when executed by a processor, predicts a number of customers that will respond to the marketing activities.  
     
     
         20 . The system of  claim 18 , further comprising a data structure representing a constraint on the marketing campaign, wherein the assignment module will reject assignments of the customer objects to the marketing activities that are inconsistent with the constraint.  
     
     
         21 . The system of  claim 18 , further comprising a binary map for storing the assignments of the customer objects to the marketing activities, wherein a flag can be set in the binary map for each possible assignment of the customer objects to the marketing activities.  
     
     
         22 . The system of  claim 18 , wherein the system creates a target group comprising at least some of the customer objects, wherein at least one of the marketing activities is to be directed at the target group.  
     
     
         23 . The system of  claim 18 , further comprising program instructions comprising an execution module that, when executed by a processor, executes said marketing activity toward the target group.  
     
     
         24 . The system of  claim 23 , further comprising program instructions comprising a response detection module that, when executed by a processor, detects responses to said marketing activity from the customers in the target group.  
     
     
         25 . Computer-readable medium with program instructions stored thereon that when executed perform the following functions for predicting values of marketing campaigns: 
 makes an assignment of customers to marketing activities of a marketing campaign, the customers being intended targets of the marketing campaign;    makes subsequent assignments of the customers to the marketing activities, each subsequent assignment comprising a reassignment of at least one of the customers to a different marketing activity, wherein a customer is not reassigned to a marketing activity to which it has previously been assigned; and    determines a first predicted value of the marketing campaign for each assignment of the customers to the marketing activities.    
     
     
         26 . The medium of  claim 25 , wherein the first predicted value is a predicted number of customers responding to the marketing activities, wherein determining the predicted number comprises at least in part using a response prediction model.  
     
     
         27 . The medium of  claim 25 , further comprising: 
 defines a constraint for the marketing campaign and rejects assignments of the customers to the marketing activities that are inconsistent with the constraint.    
     
     
         28 . The medium of  claim 25 , further comprising: 
 stores the assignments of the customers to the marketing activities in a binary map, wherein a flag can be set in the binary map for each possible assignment of the customers to the marketing activities.    
     
     
         29 . The medium of  claim 25 , further comprising: 
 creates a target group of customers.    
     
     
         30 . The medium of  claim 25 , further comprising: 
 executes said marketing activity toward the target group.    
     
     
         31 . The medium of  claim 25 , further comprising: 
 detects responses to said marketing activity from the customers in the target group.