System and Method for Strategizing Interactions With A Client Base

Abstract

The present disclosure describes novel systems and methods that can be utilized to evaluate and/or direct an interaction with a consumer database and/or evaluate a consumer database, where the consumer database contains information about consumers and particular products and/or services held or used by the consumers. The interactions may be, for example, determining a strategy for sales, marketing, cross-selling, and/or retaining one or more of the consumers. The evaluations may include, for example, hierarchically ranking the consumers and/or determining a clustering of the consumers.

We claim: 
     
         1 . A system for determining an interaction strategy with at least a first consumer, comprising:
 a computer database with first information about plural consumers and second information about predetermined products, wherein the plural consumers include a first consumer, and wherein each of the plural consumers is associated with a current product mix comprising certain ones of the predetermined products independent of an association of another consumer with the predetermined products, and wherein the database is stratified into plural segments according to a predetermined criteria, and wherein each of the plural consumers is assigned to one of the plural segments according to the predetermined criteria;   a computer processor; and   a non-volatile non-transitory computer-readable storage medium containing a set of instructions that cause said computer processor to perform the steps of:   (a) individually for each one of the plural consumers:
 (i) calculating an aggregate first Residual Life Time Value (“RLTV”) estimate from the time variable products in the current product mix for said one consumer; 
 (ii) calculating an aggregate second RLTV estimate from the finite duration products in the current product mix for said one consumer; 
 (iii) calculating an aggregate third RLTV estimate from the aggregate first RLTV estimate and from the aggregate second RLTV estimate; and 
 (iv) calculating an aggregate Potential Life Time Value (“PLTV”) estimate from preselected products not in the current product mix for said one consumer; 
   (b) analyzing a distribution of the aggregate third RLTV estimates for the plural consumers;   (c) analyzing a distribution of the aggregate PLTV estimates for the plural consumers;   (d) evaluating the first consumer as a function of the distribution of the third aggregate RLTV estimates and as a function of the distribution of the aggregate PLTV estimates;   (e) determining an interaction strategy for the first consumer based on said evaluation of the first consumer; and   (f) providing an output of the interaction strategy for the first consumer.   
     
     
         2 . The system of  claim 1  wherein the set of instructions for said non-volatile non-transitory computer-readable storage medium further includes instructions for determining a matrix of values from the distribution of the aggregate third RLTV estimates for the plural consumers and from the distribution of the aggregate PLTV estimates for the plural consumers. 
     
     
         3 . The system of  claim 2  wherein the matrix comprises N number of rows encompassing a first range of quantities for the distribution of the aggregate third RLTV estimates and M number of columns encompassing a second range of quantities for the distribution of the aggregate PLTV estimates thereby creating a matrix of X cells where X=N*M. 
     
     
         4 . The system of  claim 3  wherein the first consumer is assigned to one of the X cells based at least in part on the evaluation of the first consumer. 
     
     
         5 . The system of  claim 4  wherein the interaction with the first consumer is determined based at least in part on the cell assignment. 
     
     
         6 . The system of  claim 4  wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are calculated at a first predetermined time and wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are recalculated at a second predetermined time. 
     
     
         7 . The system of  claim 6  wherein the first consumer is assigned to one of the X cells based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         8 . The system of  claim 7  wherein the interaction with the first consumer is determined based at least in part on a difference between the cell assignment of the first consumer based at least in part on the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer and the cell assignment of the first consumer based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         9 . The system of  claim 1  wherein the first consumer comprises a cluster of consumers wherein each member of the cluster meets a predetermined criteria for inclusion in the cluster. 
     
     
         10 . The system of  claim 1  wherein the interaction strategy for the first consumer is selected from the group consisting of: determining a sales strategy tailored for the first consumer, determining a cross-selling opportunity for the first consumer, determining a marketing strategy tailored for the first consumer, determining a strategy for retaining the first consumer, and combinations thereof. 
     
     
         11 . A system for determining an interaction strategy with at least a first consumer, comprising:
 a computer database with first information about plural consumers and second information about predetermined products, wherein the plural consumers include a first consumer, and wherein each of the plural consumers is associated with a current product mix comprising certain ones of the predetermined products independent of an association of another consumer with the predetermined products;   a computer processor; and   a non-volatile non-transitory computer-readable storage medium containing a set of instructions that cause said computer processor to perform the steps of:   (a) individually for each one of the plural consumers:
 (i) calculating an aggregate first Residual Life Time Value (“RLTV”) estimate from the time variable products in the current product mix for said one consumer; 
 (ii) calculating an aggregate second RLTV estimate from the finite duration products in the current product mix for said one consumer; 
 (iii) calculating an aggregate third RLTV estimate from the aggregate first RLTV estimate and from the aggregate second RLTV estimate; and 
 (iv) calculating an aggregate Potential Life Time Value (“PLTV”) estimate from preselected products not in the current product mix for said one consumer; 
   (b) analyzing a distribution of the aggregate third RLTV estimates for the plural consumers;   (c) analyzing a distribution of the aggregate PLTV estimates for the plural consumers;   (d) evaluating the first consumer as a function of the distribution of the third aggregate RLTV estimates and as a function of the distribution of the aggregate PLTV estimates;   (e) determining an interaction strategy for the first consumer based on said evaluation of the first consumer;   (f) determining a matrix of values from the distribution of the aggregate third RLTV estimates for the plural consumers and from the distribution of the aggregate PLTV estimates for the plural consumers; and   (g) providing an output of the interaction strategy for the first consumer.   
     
     
         12 . The system of  claim 11  wherein the matrix comprises N number of rows encompassing a first range of quantities for the distribution of the aggregate third RLTV estimates and M number of columns encompassing a second range of quantities for the distribution of the aggregate PLTV estimates thereby creating a matrix of X cells where X=N*M. 
     
     
         13 . The system of  claim 12  wherein the first consumer is assigned to one of the X cells based at least in part on the evaluation of the first consumer. 
     
     
         14 . The system of  claim 13  wherein the interaction with the first consumer is determined based at least in part on the cell assignment. 
     
     
         15 . The system of  claim 13  wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are calculated at a first predetermined time and wherein the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer are recalculated at a second predetermined time. 
     
     
         16 . The system of  claim 15  wherein the first consumer is assigned to one of the X cells based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         17 . The system of  claim 16  wherein the interaction with the first consumer is determined based at least in part on a difference between the cell assignment of the first consumer based at least in part on the aggregate third RLTV estimate for the first consumer and the aggregate PLTV estimate for the first consumer and the cell assignment of the first consumer based at least in part on the recalculated aggregate third RLTV estimate and the recalculated aggregate PLTV estimate. 
     
     
         18 . The system of  claim 11  wherein the first consumer comprises a cluster of consumers wherein each member of the cluster meets a predetermined criteria for inclusion in the cluster. 
     
     
         19 . The system of  claim 11  wherein the interaction strategy for the first consumer is selected from the group consisting of: determining a sales strategy tailored for the first consumer, determining a cross-selling opportunity for the first consumer, determining a marketing strategy tailored for the first consumer, determining a strategy for retaining the first consumer, and combinations thereof.